mirrors/opencv_contrib
1
0
Fork 0
Code Pull Requests Packages Releases Activity

vendor: OpenCV 5.0.0 snapshot at 755e50675d97db9b7d449d8bd6b09888646f6c6e

Browse Source
This commit is contained in:
Gitea Mirror Bot
2026-08-22 00:11:13 +08:00
commit 12022378a3
3872 changed files with 2513409 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files
modules/dpm/CMakeLists.txt
+5
View File
@@ -0,0 +1,5 @@
set(the_description "Object Detection")
ocv_define_module(dpm opencv_core opencv_imgproc opencv_objdetect OPTIONAL opencv_highgui WRAP python)
ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4512) # disable warning on Win64
modules/dpm/README.md
+37
View File
@@ -0,0 +1,37 @@
Cascade object detection with deformable part models
====================================================
The object detector described below has been initially proposed by P.F. Felzenszwalb in [1]. It is based on a Dalal-Triggs detector that uses a single filter on histogram of oriented gradients (HOG) features to represent an object category. This detector uses a sliding window approach, where a filter is applied at all positions and scales of an image. The first innovation is enriching the Dalal-Triggs model using a star-structured part-based model defined by a "root" filter (analogous to the Dalal-Triggs filter) plus a set of parts filters and associated deformation models. The score of one of star models at a particular position and scale within an image is the score of the root filter at the given location plus the sum over parts of the maximum, over placements of that part, of the part filter score on its location minus a deformation cost easuring the deviation of the part from its ideal location relative to the root. Both root and part filter scores are defined by the dot product between a filter (a set of weights) and a subwindow of a feature pyramid computed from the input image. Another improvement is a representation of the class of models by a mixture of star models. The score of a mixture model at a particular position and scale is the maximum over components, of the score of that component model at the given location.
The detector was dramatically speeded-up with cascade algorithm proposed by P.F. Felzenszwalb in [2]. The algorithm prunes partial hypotheses using thresholds on their scores. The basic idea of the algorithm is to use a hierarchy of models defined by an ordering of the original model's parts. For a model with (n+1) parts, including the root, a sequence of (n+1) models is obtained. The i-th model in this sequence is defined by the first i parts from the original model.
Using this hierarchy, low scoring hypotheses can be pruned after looking at the best configuration of a subset of the parts. Hypotheses that score high under a weak model are evaluated further using a richer model.
In OpenCV there is an C++ implementation of DPM cascade detector.
Usage
-----
```
// load model from model_path
cv::Ptr<DPMDetector> detector = DPMDetector::create(vector<string>(1, model_path));
// read image from image_path
Mat image = imread(image_path);
// detection
vector<DPMDetector::ObjectDetection> ds;
detector->detect(image, ds);
```
Examples
----------
```
// detect using web camera
./example_dpm_cascade_detect_camera <model_path>
// detect for an image sequence
./example_dpm_cascade_detect_sequence <model_path> <image_dir>
```
References
----------
[1]: P. Felzenszwalb, R. Girshick, D. McAllester, D. Ramanan Object Detection with Discriminatively Trained Part Based Models IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 32, No. 9, Sep. 2010.
[2]: P. Felzenszwalb, R. Girshick, D. McAllester Cascade Object Detection with Deformable Part Models IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2010.
modules/dpm/doc/dpm.bib
+18
View File
@@ -0,0 +1,18 @@
@article{Felzenszwalb2010a,
title={Object detection with discriminatively trained part-based models},
author={Felzenszwalb, Pedro F and Girshick, Ross B and McAllester, David and Ramanan, Deva},
journal={Pattern Analysis and Machine Intelligence, IEEE Transactions on},
volume={32},
number={9},
pages={1627--1645},
year={2010},
publisher={IEEE}
}
@inproceedings{Felzenszwalb2010b,
title={Cascade object detection with deformable part models},
author={Felzenszwalb, Pedro F and Girshick, Ross B and McAllester, David},
booktitle={Computer vision and pattern recognition (CVPR), 2010 IEEE conference on},
pages={2241--2248},
year={2010},
organization={IEEE}
}
modules/dpm/include/opencv2/dpm.hpp
+153
View File
@@ -0,0 +1,153 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2015, Itseez Inc, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Itseez Inc or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
// Implementation authors:
// Jiaolong Xu - jiaolongxu@gmail.com
// Evgeniy Kozinov - evgeniy.kozinov@gmail.com
// Valentina Kustikova - valentina.kustikova@gmail.com
// Nikolai Zolotykh - Nikolai.Zolotykh@gmail.com
// Iosif Meyerov - meerov@vmk.unn.ru
// Alexey Polovinkin - polovinkin.alexey@gmail.com
//
//M*/
#ifndef __OPENCV_LATENTSVM_HPP__
#define __OPENCV_LATENTSVM_HPP__
#include "opencv2/core.hpp"
#include <map>
#include <vector>
#include <string>
/** @defgroup dpm Deformable Part-based Models
Discriminatively Trained Part Based Models for Object Detection
---------------------------------------------------------------
The object detector described below has been initially proposed by P.F. Felzenszwalb in
@cite Felzenszwalb2010a . It is based on a Dalal-Triggs detector that uses a single filter on histogram
of oriented gradients (HOG) features to represent an object category. This detector uses a sliding
window approach, where a filter is applied at all positions and scales of an image. The first
innovation is enriching the Dalal-Triggs model using a star-structured part-based model defined by a
"root" filter (analogous to the Dalal-Triggs filter) plus a set of parts filters and associated
deformation models. The score of one of star models at a particular position and scale within an
image is the score of the root filter at the given location plus the sum over parts of the maximum,
over placements of that part, of the part filter score on its location minus a deformation cost
easuring the deviation of the part from its ideal location relative to the root. Both root and part
filter scores are defined by the dot product between a filter (a set of weights) and a subwindow of
a feature pyramid computed from the input image. Another improvement is a representation of the
class of models by a mixture of star models. The score of a mixture model at a particular position
and scale is the maximum over components, of the score of that component model at the given
location.
The detector was dramatically speeded-up with cascade algorithm proposed by P.F. Felzenszwalb in
@cite Felzenszwalb2010b . The algorithm prunes partial hypotheses using thresholds on their scores.The
basic idea of the algorithm is to use a hierarchy of models defined by an ordering of the original
model's parts. For a model with (n+1) parts, including the root, a sequence of (n+1) models is
obtained. The i-th model in this sequence is defined by the first i parts from the original model.
Using this hierarchy, low scoring hypotheses can be pruned after looking at the best configuration
of a subset of the parts. Hypotheses that score high under a weak model are evaluated further using
a richer model.
In OpenCV there is an C++ implementation of DPM cascade detector.
*/
namespace cv
{
namespace dpm
{
//! @addtogroup dpm
//! @{
/** @brief This is a C++ abstract class, it provides external user API to work with DPM.
*/
class CV_EXPORTS_W DPMDetector
{
public:
struct CV_EXPORTS_W ObjectDetection
{
ObjectDetection();
ObjectDetection( const Rect& rect, float score, int classID=-1 );
Rect rect;
float score;
int classID;
};
virtual bool isEmpty() const = 0;
/** @brief Find rectangular regions in the given image that are likely to contain objects of loaded classes
(models) and corresponding confidence levels.
@param image An image.
@param objects The detections: rectangulars, scores and class IDs.
*/
virtual void detect(cv::Mat &image, CV_OUT std::vector<ObjectDetection> &objects) = 0;
/** @brief Return the class (model) names that were passed in constructor or method load or extracted from
models filenames in those methods.
*/
virtual std::vector<std::string> const& getClassNames() const = 0;
/** @brief Return a count of loaded models (classes).
*/
virtual size_t getClassCount() const = 0;
/** @brief Load the trained models from given .xml files and return cv::Ptr\<DPMDetector\>.
@param filenames A set of filenames storing the trained detectors (models). Each file contains one
model. See examples of such files here `/opencv_extra/testdata/cv/dpm/VOC2007_Cascade/`.
@param classNames A set of trained models names. If it's empty then the name of each model will be
constructed from the name of file containing the model. E.g. the model stored in
"/home/user/cat.xml" will get the name "cat".
*/
static cv::Ptr<DPMDetector> create(std::vector<std::string> const &filenames,
std::vector<std::string> const &classNames = std::vector<std::string>());
virtual ~DPMDetector(){}
};
//! @}
} // namespace dpm
} // namespace cv
#endif
modules/dpm/samples/cascade_detect_camera.cpp
+143
View File
@@ -0,0 +1,143 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2015, Itseez Inc, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Itseez Inc or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
// Author: Jiaolong Xu <jiaolongxu AT gmail.com>
//M*/
#include <opencv2/dpm.hpp>
#include <opencv2/core.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/videoio.hpp>
#include <stdio.h>
#include <iostream>
using namespace cv;
using namespace cv::dpm;
using namespace std;
static void help()
{
cout << "\nThis is a demo of \"Deformable Part-based Model (DPM) cascade detection API\" using web camera.\n"
"Call:\n"
"./example_dpm_cascade_detect_camera <model_path>\n"
<< endl;
}
void drawBoxes(Mat &frame,
vector<DPMDetector::ObjectDetection> ds,
Scalar color,
string text);
int main( int argc, char** argv )
{
const char* keys =
{
"{@model_path | | Path of the DPM cascade model}"
};
CommandLineParser parser(argc, argv, keys);
string model_path(parser.get<string>(0));
if( model_path.empty() )
{
help();
return -1;
}
cv::Ptr<DPMDetector> detector = \
DPMDetector::create(vector<string>(1, model_path));
// use web camera
VideoCapture capture(0);
capture.set(cv::CAP_PROP_FRAME_WIDTH, 320);
capture.set(cv::CAP_PROP_FRAME_HEIGHT, 240);
if ( !capture.isOpened() )
{
cerr << "Fail to open default camera (0)!" << endl;
return -1;
}
Mat frame;
namedWindow("DPM Cascade Detection", 1);
// the color of the rectangle
Scalar color(0, 255, 255); // yellow
while( capture.read(frame) )
{
vector<DPMDetector::ObjectDetection> ds;
Mat image;
frame.copyTo(image);
double t = (double) getTickCount();
// detection
detector->detect(image, ds);
// compute frame per second (fps)
t = ((double) getTickCount() - t)/getTickFrequency();//elapsed time
// draw boxes
string text = format("%0.1f fps", 1.0/t);
drawBoxes(frame, ds, color, text);
imshow("DPM Cascade Detection", frame);
if ( waitKey(30) >= 0)
break;
}
return 0;
}
void drawBoxes(Mat &frame,
vector<DPMDetector::ObjectDetection> ds,
Scalar color,
string text)
{
for (unsigned int i = 0; i < ds.size(); i++)
{
rectangle(frame, ds[i].rect, color, 2);
}
// draw text on image
Scalar textColor(0,0,250);
putText(frame, text, Point(10,50), FONT_HERSHEY_PLAIN, 2, textColor, 2);
}
modules/dpm/samples/cascade_detect_sequence.cpp
+167
View File
@@ -0,0 +1,167 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2015, Itseez Inc, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Itseez Inc or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
// Author: Jiaolong Xu <jiaolongxu AT gmail.com>
//M*/
#include <opencv2/dpm.hpp>
#include <opencv2/core.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui.hpp>
#include <stdio.h>
#include <iostream>
#include <fstream>
using namespace cv;
using namespace cv::dpm;
using namespace std;
int save_results(const string id, const vector<DPMDetector::ObjectDetection> ds, ofstream &out);
static void help()
{
cout << "\nThis example shows object detection on image sequences using \"Deformable Part-based Model (DPM) cascade detection API\n"
"Call:\n"
"./example_dpm_cascade_detect_sequence <model_path> <image_dir>\n"
"The image names has to be provided in \"files.txt\" under <image_dir>.\n"
<< endl;
}
static bool readImageLists( const string &file, vector<string> &imgFileList)
{
ifstream in(file.c_str(), ios::binary);
if (in.is_open())
{
while (in)
{
string line;
getline(in, line);
imgFileList.push_back(line);
}
return true;
}
else
{
cerr << "Invalid image index file: " << file << endl;
return false;
}
}
void drawBoxes(Mat &frame,
vector<DPMDetector::ObjectDetection> ds,
Scalar color,
string text);
int main( int argc, char** argv )
{
const char* keys =
{
"{@model_path | | Path of the DPM cascade model}"
"{@image_dir | | Directory of the images }"
};
CommandLineParser parser(argc, argv, keys);
string model_path(parser.get<string>(0));
string image_dir(parser.get<string>(1));
string image_list = image_dir + "/files.txt";
if( model_path.empty() || image_dir.empty() )
{
help();
return -1;
}
vector<string> imgFileList;
if ( !readImageLists(image_list, imgFileList) )
return -1;
cv::Ptr<DPMDetector> detector = \
DPMDetector::create(vector<string>(1, model_path));
namedWindow("DPM Cascade Detection", 1);
// the color of the rectangle
Scalar color(0, 255, 255); // yellow
Mat frame;
for (size_t i = 0; i < imgFileList.size(); i++)
{
double t = (double) getTickCount();
vector<DPMDetector::ObjectDetection> ds;
Mat image = imread(image_dir + "/" + imgFileList[i]);
frame = image.clone();
if (image.empty()) {
cerr << "\nInvalid image:\n" << imgFileList[i] << endl;
return -1;
}
// detection
detector->detect(image, ds);
// compute frame per second (fps)
t = ((double) getTickCount() - t)/getTickFrequency();//elapsed time
// draw boxes
string text = format("%0.1f fps", 1.0/t);
drawBoxes(frame, ds, color, text);
// show detections
imshow("DPM Cascade Detection", frame);
if ( waitKey(30) >= 0)
break;
}
return 0;
}
void drawBoxes(Mat &frame, \
vector<DPMDetector::ObjectDetection> ds, Scalar color, string text)
{
for (unsigned int i = 0; i < ds.size(); i++)
{
rectangle(frame, ds[i].rect, color, 2);
}
// draw text on image
Scalar textColor(0,0,250);
putText(frame, text, Point(10,50), FONT_HERSHEY_PLAIN, 2, textColor, 2);
}
modules/dpm/samples/data/inriaperson.xml
+691
View File
@@ -0,0 +1,691 @@
<?xml version="1.0"?>
<opencv_storage>
<SBin>8</SBin>
<NumComponents>2</NumComponents>
<NumFeatures>32</NumFeatures>
<Interval>5</Interval>
<MaxSizeX>5</MaxSizeX>
<MaxSizeY>15</MaxSizeY>
<PCAcoeff type_id="opencv-matrix">
<rows>32</rows>
<cols>6</cols>
<dt>d</dt>
<data>
-0.126352 -0.251754 0.000162 -0.307732 0.001753 0.000000
-0.107640 -0.147280 -0.126797 -0.011158 0.083754 0.000000
-0.110775 -0.054764 -0.218856 0.177866 0.156714 0.000000
-0.118092 0.061014 -0.194359 0.147161 0.251803 0.000000
-0.151281 0.247370 -0.083790 -0.176683 0.397600 0.000000
-0.147929 0.241083 0.095421 -0.158980 0.391605 0.000000
-0.116576 0.059412 0.197200 0.149047 0.250757 0.000000
-0.109158 -0.054815 0.219480 0.177534 0.151575 0.000000
-0.106911 -0.146401 0.127344 -0.010968 0.079559 0.000000
-0.126143 -0.249275 -0.001539 -0.307670 -0.000205 0.000000
-0.108651 -0.149549 -0.131209 -0.010469 -0.075286 0.000000
-0.112703 -0.058041 -0.227021 0.182907 -0.147237 0.000000
-0.121120 0.056804 -0.206183 0.157054 -0.248257 0.000000
-0.154138 0.240917 -0.093038 -0.173921 -0.402466 0.000000
-0.150450 0.232438 0.093734 -0.154429 -0.397942 0.000000
-0.119522 0.052840 0.201165 0.156374 -0.250198 0.000000
-0.111659 -0.062961 0.223864 0.179763 -0.151304 0.000000
-0.108686 -0.154411 0.130172 -0.015272 -0.077690 0.000000
-0.223103 -0.364956 -0.001520 -0.370594 0.000681 0.000000
-0.203424 -0.250927 -0.208393 -0.008980 0.006696 0.000000
-0.206852 -0.092446 -0.339663 0.275083 0.006614 0.000000
-0.222081 0.097062 -0.310669 0.239101 0.002267 0.000000
-0.265546 0.340323 -0.121357 -0.200143 -0.005220 0.000000
-0.261715 0.336879 0.131287 -0.183642 -0.004819 0.000000
-0.219935 0.093374 0.311892 0.242094 0.001127 0.000000
-0.204750 -0.096330 0.338401 0.273360 0.000739 0.000000
-0.202781 -0.254320 0.207836 -0.012984 0.001870 0.000000
-0.259609 -0.015209 -0.007047 0.000626 -0.007791 0.000000
-0.260700 -0.017088 0.011097 -0.001094 0.011428 0.000000
-0.259645 -0.015372 0.008475 0.001259 -0.008532 0.000000
-0.260796 -0.017088 -0.009814 -0.000590 0.011747 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 1.000000
</data>
</PCAcoeff>
<PCADim>6</PCADim>
<ScoreThreshold>-0.5000000000000000</ScoreThreshold>
<Bias>
-6.659495 -6.659495
</Bias>
<RootFilters>
<_ type_id="opencv-matrix">
<rows>15</rows>
<cols>160</cols>
<dt>d</dt>
<data>
0.068140 -0.009553 -0.029626 -0.044845 0.015961 0.011180 -0.047270 -0.053032 -0.040501 0.018182 0.001276 -0.006370 -0.025556 0.022397 0.037253 -0.008807 -0.016904 -0.006897 0.054817 0.006889 -0.029269 -0.049491 0.022779 0.031837 -0.042138 -0.050557 -0.026430 -0.061115 0.000283 -0.020680 0.027314 -0.009670 0.007401 0.005270 0.022857 0.021595 0.049167 0.035256 0.002311 -0.023846 -0.037539 0.040376 0.007905 0.046480 0.021463 0.031339 0.014524 -0.050671 -0.030429 -0.022491 0.038177 0.036397 0.074311 0.049325 0.055395 0.022248 -0.048189 -0.038726 -0.047421 -0.016663 0.029055 -0.005605 0.059665 -0.009667 0.013302 -0.016244 -0.007858 -0.006133 0.024184 0.037767 0.025257 0.003032 0.003538 0.048365 -0.032054 -0.013482 0.026308 0.058520 0.052454 0.030932 -0.006515 -0.016205 0.045343 -0.029090 -0.015864 0.011571 0.069803 0.062798 0.060276 0.016956 0.006551 0.018778 0.039975 0.000684 0.046708 -0.003709 0.024794 -0.021387 -0.028795 -0.027813 0.015623 0.001262 -0.006907 -0.007536 0.032384 0.042302 -0.022589 -0.032911 -0.020574 0.016640 0.044733 0.027400 0.014219 -0.015965 0.036502 -0.032726 -0.062807 -0.045817 0.005227 0.026784 0.018727 0.003675 0.027947 0.011070 0.034234 -0.029763 0.000902 -0.003713 0.035544 -0.022931 -0.018055 0.000220 0.032455 0.001804 -0.034702 -0.002373 0.010749 0.015599 0.004384 0.007782 0.004234 0.017988 0.043088 -0.034601 -0.043803 -0.045896 0.019615 -0.002274 -0.012213 0.006196 0.013960 0.016352 -0.058873 -0.034917 -0.011496 0.001176 0.029205 -0.038255 -0.005569 -0.014922
0.057043 0.001617 -0.000480 -0.025184 0.015080 0.013821 -0.012989 -0.016157 -0.033569 0.005633 -0.043526 -0.047811 -0.045843 0.002655 0.001484 0.005111 0.003065 0.021356 0.039239 -0.038718 -0.037235 -0.053042 0.016661 0.008580 -0.002124 -0.009909 0.014568 -0.042022 -0.024888 0.003443 0.016942 0.004342 0.019122 0.013120 -0.003967 -0.002290 0.009155 0.006616 0.027775 0.057341 0.056987 0.038748 -0.016449 -0.004999 0.010282 -0.007851 -0.009807 -0.007090 0.013375 0.016850 0.047072 0.001760 0.008580 0.012458 0.004169 -0.008257 0.003440 0.049428 0.068541 0.015342 0.033014 0.015996 0.037904 0.004345 -0.021244 -0.013004 -0.011427 0.000161 0.013333 0.007543 0.008260 0.042437 0.049123 0.013991 0.007823 0.005170 0.023601 0.017914 -0.028295 -0.008662 0.012419 -0.000015 0.041254 0.012742 0.009396 0.008710 0.014876 0.003786 0.028244 0.044160 0.055982 0.011700 0.027023 0.004429 0.013005 0.010303 0.022234 0.024213 0.010843 -0.012987 0.012817 0.008591 -0.011587 0.015929 -0.001371 0.056766 -0.009289 -0.033632 -0.047433 -0.018183 -0.011580 -0.018981 -0.012982 0.003173 0.061885 0.024670 -0.015458 -0.055850 -0.030199 -0.010894 -0.013926 0.028499 0.024512 0.003145 0.011849 -0.016570 -0.009484 0.010299 0.021825 -0.025420 -0.011728 -0.003262 0.064364 0.035832 0.001544 -0.028108 -0.050468 0.003782 -0.013305 -0.028090 -0.026099 0.016603 0.014230 -0.035601 0.001966 -0.016734 0.012060 -0.020146 -0.035264 -0.015303 0.039655 0.012478 -0.022135 -0.024164 -0.034562 0.007289 0.016895 -0.038800 -0.022470 -0.000910
0.029640 0.001829 0.016931 0.038847 0.030058 0.022421 0.005887 0.017414 -0.005997 0.021909 -0.043247 -0.034392 -0.015132 -0.001477 -0.006589 0.003218 0.000682 0.005744 0.020033 -0.017765 0.008411 0.029477 0.026884 0.021363 -0.000235 0.013463 0.020696 0.010533 -0.020979 0.030481 0.021329 0.006037 -0.021082 0.006932 0.001872 0.050592 0.043405 -0.006976 0.029007 0.033694 0.052028 0.037282 0.009055 0.030068 0.051245 0.000453 -0.039992 0.006284 0.049777 0.016171 0.025080 0.040546 0.053214 0.070923 0.042800 -0.013486 0.034341 0.047261 0.070908 0.060244 0.022409 0.055190 0.027059 0.006040 0.000946 0.001199 0.022867 0.011592 0.032082 0.017506 0.033751 0.037385 0.026509 0.011567 0.007350 -0.003299 0.020538 -0.038279 -0.043271 -0.017231 0.016886 0.029006 0.035041 0.018041 0.015728 0.027384 0.008056 0.004562 0.026198 0.045662 0.046437 0.046807 0.005452 0.029669 -0.003155 0.011998 0.036643 0.048532 0.032543 0.004570 0.019716 0.023553 0.053549 0.063683 0.015756 0.010030 -0.014686 -0.009994 -0.027505 -0.055624 -0.019272 0.029358 0.029755 0.007434 0.041628 0.028158 0.017421 -0.020795 -0.028616 0.025544 0.098255 0.092944 0.031681 0.052304 0.026552 0.041797 -0.003726 0.011993 -0.006270 0.013135 0.003740 -0.018855 0.007595 -0.001976 -0.004907 0.032046 0.003898 0.036235 -0.012379 -0.012530 -0.006658 0.003263 -0.019383 0.007951 0.024669 -0.033363 0.022039 0.002134 -0.004578 -0.026130 -0.004704 -0.004733 -0.000905 0.054071 -0.017977 0.019199 0.009883 0.009650 -0.031091 0.000784
0.000311 0.012595 -0.003724 -0.016393 -0.003968 0.018663 -0.002783 0.013197 -0.031518 -0.024629 0.025460 0.014683 0.007149 -0.005943 -0.037165 0.001592 -0.012018 -0.028182 0.042371 0.043062 0.039090 0.016449 0.006748 -0.016301 0.008460 -0.002430 -0.046631 0.003846 -0.033188 0.000501 -0.005418 -0.005963 -0.053842 0.014600 0.022845 0.004670 -0.001109 -0.032655 0.000214 0.026107 -0.004821 -0.028084 0.000129 -0.000165 0.008456 -0.011027 -0.021400 0.016205 0.005560 -0.000106 0.001589 0.019675 0.024485 0.019211 0.011140 -0.032493 0.019793 0.022479 -0.005300 0.052262 -0.042923 -0.004304 -0.030689 -0.005960 -0.025240 0.003181 0.028170 0.012613 0.025635 -0.016738 -0.000101 0.006714 -0.026027 -0.040430 0.025070 -0.012488 0.001332 -0.018554 -0.035400 0.003984 0.001426 0.004916 -0.030590 0.007141 0.013362 0.004881 0.010103 -0.031920 0.011472 -0.012589 -0.042450 0.044763 -0.042027 0.022184 -0.054118 -0.000002 -0.037712 -0.024121 -0.017608 -0.035700 -0.019149 -0.026707 -0.041595 0.027745 0.022609 -0.015396 0.018685 0.004722 -0.002791 -0.011444 -0.018256 0.019313 0.006991 0.002332 -0.014162 -0.016634 -0.001485 -0.031752 -0.022612 -0.029215 0.018944 0.050985 0.013322 -0.001891 -0.033577 0.029692 -0.064031 -0.000007 -0.027220 -0.004722 0.005438 -0.042078 -0.015131 -0.009136 -0.033884 0.026482 0.045934 0.025151 -0.004228 -0.011495 -0.020495 -0.016545 -0.000698 0.045815 0.007082 0.005009 0.051111 -0.009230 -0.018173 -0.059655 -0.052053 -0.019064 0.018480 0.080820 0.060786 0.002819 -0.013012 0.026316 -0.027776 -0.011216
-0.046375 0.004685 -0.032245 -0.034164 0.014131 0.035548 0.019533 -0.002193 -0.014299 0.012626 0.034105 0.014870 -0.030693 -0.031538 -0.011782 0.009951 0.002253 -0.042071 0.036614 0.029464 0.003190 -0.045947 -0.011291 0.009846 0.022165 -0.009970 -0.045808 -0.002508 -0.018558 -0.010542 -0.014429 -0.005963 -0.012604 0.019137 0.018476 -0.019515 -0.012536 -0.013653 -0.021617 0.010469 0.006393 -0.035276 -0.016879 -0.034260 -0.043987 -0.012579 -0.004460 0.032876 0.034555 0.030514 0.019624 0.002851 -0.020473 -0.046201 -0.015942 -0.013166 0.012840 0.031027 0.029266 0.032909 -0.002471 -0.025388 -0.040379 -0.005960 0.006093 -0.016366 -0.009649 -0.007816 -0.010302 -0.030799 -0.012240 -0.003581 -0.012099 -0.027165 0.017258 -0.012738 -0.008103 -0.012595 -0.016817 0.004793 0.007292 0.025793 0.006819 -0.015841 -0.020438 -0.018998 -0.031207 -0.052897 -0.017731 -0.015394 0.005659 0.010704 -0.019400 -0.009241 -0.038179 -0.000002 -0.013672 -0.037372 -0.041667 -0.031897 -0.008143 0.008794 -0.013284 -0.008196 0.002476 0.013486 0.058469 -0.000506 0.005548 -0.016997 -0.010286 -0.023247 -0.038423 -0.003403 0.032862 0.005932 -0.025982 -0.023179 -0.027094 -0.016704 -0.044242 -0.040605 -0.014547 -0.031706 -0.036196 0.012128 -0.018859 -0.000007 -0.017013 -0.003825 0.003006 -0.011057 -0.007716 0.016402 0.000450 0.012633 0.060208 0.011117 0.005466 -0.013144 0.005520 -0.033609 -0.023586 -0.016380 -0.031006 -0.017571 0.046391 0.006463 -0.013667 -0.001451 -0.030020 0.002838 -0.012918 -0.010998 0.049278 -0.016688 -0.008350 -0.002439 -0.000857 -0.011216
-0.040753 0.005266 -0.015735 -0.028976 0.015863 0.038142 0.007393 -0.016940 -0.004691 0.001828 0.053650 0.033271 0.008104 -0.014934 0.009246 0.002725 0.009441 -0.034744 0.035355 0.055643 0.015926 -0.017295 -0.000197 0.038247 0.012972 -0.009877 -0.018287 0.004559 0.012838 -0.006356 0.002232 -0.005963 0.002774 0.057195 0.020744 0.014011 -0.003664 -0.016739 0.006276 -0.023745 -0.022229 -0.040589 0.004208 -0.014060 -0.007032 -0.007962 -0.009916 -0.005734 0.007255 0.015334 0.020275 0.035137 0.016344 0.002880 -0.004278 -0.021726 -0.005701 -0.003058 -0.002301 0.022480 0.028181 -0.026879 -0.035035 -0.005960 -0.010578 0.006288 -0.018064 -0.024140 -0.016589 -0.027701 -0.020007 -0.023323 -0.015471 -0.039294 0.038037 0.011722 0.007796 -0.041899 -0.034189 -0.017903 -0.014054 -0.005513 -0.013465 0.004024 -0.001518 -0.020610 -0.055130 -0.055278 -0.038432 -0.033171 -0.022163 -0.025914 -0.020575 -0.031475 -0.037474 -0.000002 -0.032887 0.030391 -0.032485 0.003784 -0.002492 -0.024525 -0.023295 -0.004344 0.012172 -0.007400 0.050523 0.003303 -0.011199 -0.021038 -0.006982 -0.001696 -0.004890 -0.009425 0.024103 0.029385 -0.004468 -0.002720 -0.026261 -0.028846 -0.027664 -0.017439 -0.001685 -0.040830 -0.034288 0.012193 0.024040 -0.000007 -0.017564 0.009492 0.011190 0.023265 0.016145 -0.007482 0.002626 0.002001 0.024208 0.023802 0.006328 0.004576 0.007014 0.002558 -0.009276 -0.023857 -0.003696 0.013802 0.069001 0.024481 0.014492 0.031054 0.014206 -0.009901 -0.022106 -0.012606 0.021096 0.001626 0.002771 0.012418 0.023316 -0.011216
0.003725 0.036825 -0.000821 -0.007256 0.023365 0.050676 0.001151 0.012046 0.030297 0.002621 0.041126 0.013602 0.000204 -0.011016 0.002153 -0.028029 -0.026589 -0.021058 0.063558 0.059299 0.018488 -0.010968 0.006115 0.048504 -0.019698 -0.009444 0.018583 0.017701 0.022819 0.011692 0.005780 -0.005963 0.005403 0.052454 -0.003593 0.012488 -0.000172 0.003513 -0.010781 -0.006082 -0.020292 -0.014968 0.012872 -0.006992 -0.009362 -0.005415 0.003588 -0.003479 -0.004325 0.012888 0.062116 0.052967 0.003119 -0.017033 0.004692 0.015836 -0.012558 -0.004076 -0.006995 0.014798 0.037958 -0.020547 -0.023843 -0.005960 -0.025578 0.020306 0.005447 -0.021178 -0.019897 0.000816 -0.004454 -0.022485 -0.015148 -0.057568 0.010680 -0.013176 0.004039 0.024652 -0.012665 -0.024110 -0.026477 -0.007288 -0.044177 0.004123 -0.006816 -0.021788 -0.000717 0.007313 -0.021334 -0.042848 -0.026884 -0.021896 -0.011765 -0.032406 -0.020711 -0.000002 -0.031176 0.022590 -0.000032 0.013707 -0.019036 -0.005708 -0.022960 0.012512 0.014809 -0.029796 0.021787 0.008517 0.003531 -0.020005 -0.051475 -0.019282 -0.010916 0.013216 -0.000265 0.013346 0.013025 -0.004382 -0.027508 -0.029188 -0.033446 -0.004362 0.013277 -0.032680 -0.041651 0.012826 0.014498 -0.000007 -0.020881 -0.001279 -0.008717 -0.013553 -0.019323 -0.018925 -0.017061 0.009155 0.034397 -0.013626 0.006918 -0.010776 -0.005833 0.018593 0.007162 -0.016535 0.000939 0.017611 0.060990 0.010002 -0.012827 -0.014993 0.009177 -0.005912 -0.037379 -0.000950 0.039241 -0.000232 -0.022822 0.001447 -0.002780 -0.011216
0.018274 0.031224 -0.006930 0.007110 0.003084 0.023425 -0.003910 0.011508 -0.003078 0.024702 0.043392 -0.015158 -0.008425 -0.035343 -0.011338 -0.009874 -0.013367 -0.002131 0.066308 0.040628 -0.017587 -0.007944 -0.019798 0.017815 -0.019667 0.004324 0.014249 -0.005769 0.002729 0.031556 -0.003456 -0.000615 0.006260 0.045454 0.017388 0.007047 -0.019124 -0.034737 -0.004709 0.008350 -0.001937 -0.000719 0.007365 -0.030165 -0.005775 -0.049876 -0.030692 -0.012981 -0.020306 -0.018831 0.061251 0.036160 -0.003508 0.008173 -0.016156 -0.021778 -0.016176 -0.013398 0.006737 -0.006740 0.006993 -0.035864 -0.029437 -0.000612 -0.029073 0.028438 0.017341 0.010645 0.009767 -0.013543 -0.006211 -0.015561 -0.021632 -0.026433 0.002211 -0.014534 -0.025540 -0.027290 -0.018238 -0.020337 -0.024284 -0.024375 -0.036039 0.008692 -0.001601 -0.005799 0.025991 0.002872 -0.016999 -0.040327 -0.039116 -0.010381 -0.019336 -0.031181 -0.032746 0.005346 -0.029989 -0.015232 0.009521 -0.004411 -0.004703 0.017273 -0.010975 0.001015 -0.011583 -0.023254 -0.004937 -0.010525 -0.036513 -0.036581 -0.024370 0.004709 0.004431 0.009079 -0.009405 0.001268 -0.001576 -0.017539 0.014323 0.020497 0.000405 0.002903 -0.010662 -0.036628 -0.042321 0.002948 -0.002744 0.005342 -0.002031 -0.014694 -0.010885 -0.002078 0.005904 0.018774 -0.008382 -0.007377 0.034212 0.035038 -0.016614 0.017974 -0.025486 -0.032810 -0.012142 -0.015246 -0.019346 0.034842 0.080173 -0.011300 0.013149 -0.022486 0.002488 0.018024 -0.023748 -0.012892 0.076564 -0.000698 -0.009623 -0.002503 0.003234 -0.005867
0.027086 0.032636 0.002529 -0.005594 -0.016573 0.011340 0.009837 0.016276 0.024095 0.011482 0.022181 0.005300 -0.010327 -0.017096 -0.002980 0.014130 -0.003025 0.021586 0.076625 0.038260 0.005215 -0.020679 0.007709 0.035286 0.009233 0.010740 0.035701 -0.005565 -0.010882 0.056371 0.027431 -0.008714 -0.003716 0.035604 0.033856 -0.005196 -0.039295 -0.011270 0.001425 0.029051 0.002562 -0.001404 -0.001292 -0.008535 0.004298 0.003574 -0.007085 0.000888 -0.007859 -0.002623 0.078395 0.021342 0.006590 -0.002151 -0.000021 -0.005175 -0.005629 0.014586 0.000731 0.013221 0.015246 -0.006191 -0.011442 -0.008711 -0.024022 0.010529 0.002277 -0.005766 -0.029955 -0.032043 -0.006163 0.013193 0.015400 -0.024778 0.014251 -0.016380 -0.023955 -0.013681 -0.020966 -0.011953 -0.027260 -0.016217 -0.007339 0.014964 0.001198 -0.027864 -0.006784 -0.026504 -0.027798 -0.012315 0.005422 -0.015006 -0.011860 -0.032995 -0.033235 -0.002753 -0.020752 -0.005602 0.012489 -0.008847 -0.022160 -0.014654 0.022094 -0.016802 -0.030442 -0.023995 0.014654 -0.027514 -0.027695 -0.006410 -0.026474 -0.011668 -0.011497 0.015279 0.034524 0.025496 -0.003686 -0.022656 0.002795 -0.009375 0.009643 -0.024956 -0.011046 -0.036435 -0.042020 -0.006241 -0.004868 -0.002758 0.026639 0.034657 0.017851 0.000084 0.005211 -0.001414 -0.002091 -0.035176 0.018531 0.043923 0.020126 -0.013244 -0.003220 -0.015843 -0.008682 -0.015808 -0.019031 0.022431 0.125608 0.070002 0.013379 0.000126 0.021518 0.013397 -0.021705 -0.050790 0.042746 0.006065 0.004986 0.009013 0.015265 -0.013967
-0.021032 0.033896 -0.002294 -0.019463 0.015290 0.030725 -0.010907 -0.023059 0.005975 -0.019376 0.001072 0.003116 -0.030763 -0.021565 -0.000768 0.001251 -0.026514 -0.007390 0.024718 0.024932 -0.008095 -0.048284 0.000837 0.026107 -0.009823 -0.043438 0.010571 -0.026847 -0.040957 0.019793 0.004734 -0.002557 -0.055575 0.040138 0.027852 -0.008308 -0.017015 0.000840 -0.000290 -0.022752 0.005326 0.012552 0.005702 -0.004682 -0.018240 -0.019141 -0.006450 -0.027829 -0.029635 0.009688 0.055887 0.026496 0.005392 -0.027029 -0.023552 -0.011453 -0.030673 -0.039426 0.016284 -0.000589 -0.014026 -0.005986 -0.030225 -0.002554 -0.019510 0.043154 0.026394 0.013413 -0.030001 -0.008719 0.003306 0.000899 0.031864 -0.000967 0.011106 0.008727 -0.029461 -0.035354 -0.019323 -0.046779 -0.057785 0.016077 -0.005464 0.036359 0.019480 -0.018648 -0.045519 -0.040893 -0.041239 -0.040804 0.030680 -0.001496 -0.009149 -0.012034 -0.021141 0.003404 -0.001870 0.038288 0.010084 -0.008549 -0.019528 -0.018995 -0.023775 0.006767 0.007929 -0.019925 -0.012707 -0.029610 -0.032536 -0.051934 -0.038394 -0.045584 -0.022093 0.020743 0.048834 0.037842 -0.020390 -0.031642 -0.044036 -0.062813 -0.069315 -0.019074 0.008093 -0.046423 -0.044047 -0.011164 -0.012299 0.003399 -0.033146 0.075241 0.020158 -0.009875 0.001455 0.009292 -0.009972 0.003892 0.020263 0.009192 0.017149 -0.025038 -0.017294 -0.018644 0.001971 -0.004596 -0.011485 -0.017313 0.060137 0.079792 -0.000010 -0.023206 -0.004193 0.002529 -0.013245 -0.010949 -0.003526 0.015142 0.000627 -0.005365 -0.005101 -0.007810
-0.034817 0.023273 -0.008937 -0.021249 0.020593 0.027890 -0.025962 -0.013108 0.008884 -0.020125 0.024719 0.017434 -0.004581 0.001368 -0.030552 -0.044191 -0.039097 0.012636 0.031100 0.010027 -0.005102 -0.019802 0.004633 0.013031 -0.060737 -0.050526 0.013094 -0.033245 -0.034983 0.009745 0.008597 -0.004040 -0.056896 0.033687 0.007919 -0.001980 -0.015227 -0.024272 -0.010761 -0.014196 0.036186 -0.010812 0.003928 0.018828 -0.019123 -0.032635 -0.024885 -0.029925 -0.013168 0.020623 0.040472 0.028435 0.018774 -0.016923 -0.042332 -0.046059 -0.039848 -0.030055 0.059151 -0.019186 -0.006251 -0.017177 -0.019945 -0.004037 0.001273 0.051578 0.017439 0.003812 -0.007210 -0.029904 -0.001166 0.001354 0.027833 0.005426 0.023273 0.010035 -0.015685 -0.048196 -0.021090 -0.001890 -0.026908 0.013311 0.016324 0.061154 0.025596 -0.018343 -0.048658 -0.038648 -0.015444 -0.011616 0.035402 -0.004384 0.011877 -0.008695 0.002751 0.001921 -0.011373 0.019555 -0.029738 -0.010243 -0.005208 -0.025313 -0.028285 0.009110 0.029854 -0.003456 0.002627 -0.020615 -0.014030 -0.038487 -0.025234 -0.011199 0.001411 0.024017 0.044988 0.035909 -0.042832 -0.026766 -0.033316 -0.042039 -0.038082 0.011158 0.012428 -0.025759 -0.031165 -0.009557 0.002085 0.001916 -0.013211 0.023900 -0.028487 -0.027905 0.017302 0.004238 -0.008209 0.004877 0.003152 -0.023702 -0.019111 -0.041299 -0.028258 -0.046578 -0.029054 -0.010127 0.006500 0.038484 0.029062 0.006523 -0.061328 -0.057029 -0.016160 -0.020812 -0.016995 -0.000144 0.027787 0.004692 -0.018268 -0.036413 -0.033679 -0.009293
-0.041351 -0.005922 0.003174 0.000078 0.040562 0.039236 0.002932 0.005404 0.023771 -0.025740 0.021863 0.029210 0.003769 -0.017198 -0.018864 -0.040248 -0.017370 0.011883 0.013301 0.002206 0.018100 0.000819 0.007303 0.024129 -0.030424 -0.012062 0.010734 -0.029851 -0.019389 0.034817 0.021583 -0.002228 0.017519 0.007287 0.002972 -0.020703 0.004984 0.018872 0.013127 0.023273 0.046377 -0.001407 -0.022225 -0.008397 -0.025187 -0.026007 -0.016523 -0.016395 -0.005505 0.020806 0.063877 -0.008873 -0.002022 -0.041940 -0.033906 0.002243 -0.008078 0.014553 0.066542 -0.014126 0.010184 0.004163 0.005845 -0.002226 0.008576 0.027548 0.014805 -0.022294 -0.031193 -0.011236 0.000345 0.031086 0.064590 0.033342 -0.009043 -0.018003 -0.026442 -0.016480 -0.011246 -0.017678 -0.016181 -0.002577 0.007641 0.010226 0.000360 -0.046488 -0.046468 -0.026117 -0.022152 0.019220 0.057613 -0.005895 0.016142 -0.013551 0.002323 0.003733 -0.012304 0.003470 -0.019153 -0.011342 -0.000329 -0.008450 -0.009847 0.022618 0.072397 0.007905 -0.030559 -0.029342 -0.028025 -0.038586 -0.034125 -0.031822 0.012296 0.017466 0.035317 -0.019397 -0.041406 -0.039171 -0.025856 -0.026775 -0.035000 0.035886 0.046941 -0.013157 -0.018353 -0.023798 -0.000191 0.003728 0.016215 0.009701 -0.023749 0.011541 0.030240 -0.007027 -0.025450 0.004005 0.005417 -0.038877 -0.021362 -0.038550 -0.042538 -0.037523 -0.026835 -0.043456 0.002326 0.011537 0.031739 -0.005472 -0.055015 -0.040679 -0.001470 -0.018412 -0.058719 -0.001914 0.001586 -0.002545 -0.007964 -0.048775 -0.041777 -0.007481
-0.017088 0.011582 0.002381 -0.005768 -0.009537 0.001478 -0.020335 -0.016465 0.007514 -0.019420 0.021542 -0.015262 -0.012770 -0.010919 -0.030822 -0.012272 -0.000896 0.011989 0.010589 0.015379 -0.016980 -0.012498 -0.015099 -0.013309 -0.034380 -0.019877 -0.000935 -0.050497 -0.046749 0.026676 0.016328 0.007977 -0.020303 0.006367 -0.005030 -0.018897 -0.024547 -0.010720 -0.026358 -0.016058 0.033619 0.040127 0.038605 -0.013621 -0.030546 -0.042137 -0.041048 -0.013894 0.004397 0.017745 0.066657 0.017688 -0.022494 -0.047222 -0.050534 -0.033139 -0.048864 -0.019094 0.042718 -0.029482 -0.022738 -0.002920 -0.002511 0.007979 0.026116 0.006062 -0.012925 -0.013130 -0.036040 0.009794 -0.018469 -0.017218 0.033369 0.055017 0.010920 -0.000285 0.004495 -0.024393 -0.023878 -0.022718 -0.011272 0.019176 0.021457 -0.019776 -0.014126 -0.023510 -0.052876 -0.008445 -0.045051 -0.009095 0.030037 -0.010234 0.006731 -0.005275 0.001528 0.013938 0.021838 0.013613 -0.022311 -0.010813 -0.011033 -0.006028 -0.027513 0.017322 0.047995 0.019682 -0.032228 -0.037035 -0.013513 -0.031811 -0.027611 -0.011234 0.010813 0.024494 0.062882 -0.012427 -0.048947 -0.038745 -0.035359 -0.018816 -0.042748 0.011725 0.026103 -0.005011 0.001174 -0.022405 -0.009289 0.013933 0.011329 0.028833 -0.006688 -0.005664 0.001289 0.003472 0.004029 0.013869 0.048615 -0.012242 -0.028215 -0.028975 -0.017004 -0.038546 -0.029839 -0.028585 0.006155 0.007074 0.053133 0.009049 -0.030289 -0.037575 -0.018295 -0.019790 -0.035675 -0.005269 0.020598 0.025048 0.017263 -0.043507 -0.032317 0.002724
0.010475 -0.005795 -0.006961 -0.016087 -0.005041 0.009146 -0.007822 -0.010652 -0.007081 -0.040331 -0.006073 -0.012807 -0.004667 -0.046266 -0.031881 -0.001323 -0.009093 -0.005471 0.003118 -0.012511 -0.028822 -0.030731 -0.041625 -0.019276 -0.032232 -0.037129 -0.025186 -0.048122 -0.075320 0.028192 0.002041 0.020351 -0.013106 0.027198 -0.006490 -0.005220 -0.032533 -0.013566 -0.009438 0.025209 0.016714 0.029460 0.052705 0.023592 0.010330 -0.017998 -0.013561 -0.015751 -0.013618 0.007219 0.050158 0.055047 0.011648 -0.006697 -0.020633 -0.015155 -0.033521 0.003853 0.033464 -0.005593 -0.018737 0.040112 0.008330 0.020354 0.030925 0.035173 0.003852 -0.008327 -0.021048 -0.007987 -0.018073 -0.010019 0.030188 0.050730 0.047761 0.000996 0.015162 -0.028516 -0.010843 -0.022079 -0.009215 0.035495 0.059562 0.051748 0.003503 -0.015083 -0.012538 -0.016016 -0.045539 -0.009945 0.051116 0.010092 0.008259 0.026090 0.009381 0.020886 0.033936 0.031939 0.007769 -0.003673 -0.033816 -0.006366 -0.000335 0.032534 0.059490 0.024706 0.010004 -0.035796 -0.026815 -0.025541 0.008274 0.007644 0.017274 0.033936 0.064935 0.034469 -0.020648 -0.027128 -0.035945 -0.009267 -0.000165 0.032918 0.054787 0.027057 0.029468 0.005026 0.002165 0.020879 0.019258 0.016444 0.031552 0.003040 -0.014449 -0.013991 -0.025547 -0.002719 0.010662 0.010995 -0.016608 -0.021177 -0.021351 -0.036096 -0.036935 -0.011347 0.017035 0.014302 0.050284 -0.002846 0.005630 -0.022577 -0.024008 -0.033588 -0.046771 -0.008440 0.006447 0.041014 0.020030 -0.049873 -0.047437 0.009673
-0.006663 -0.015329 -0.010055 -0.039282 0.010696 0.021565 0.023424 0.004018 0.000171 -0.021836 -0.015932 0.008142 0.020986 -0.008337 -0.008475 -0.004884 -0.011034 -0.021290 -0.013883 -0.028005 -0.012433 -0.032229 -0.005894 -0.001478 0.001253 -0.013876 -0.029759 -0.007112 -0.076530 0.050913 -0.002210 0.000846 -0.040971 -0.020152 -0.007984 -0.028648 0.028761 0.066088 0.018539 0.035993 0.004583 -0.006261 0.040816 0.037313 0.015896 -0.017739 -0.016940 -0.004349 -0.001467 -0.043955 -0.018035 0.015302 0.021952 -0.014879 0.012126 0.035675 0.001371 0.019529 -0.031090 0.013255 -0.050600 0.068097 -0.002692 -0.004217 -0.006379 0.039141 0.017744 -0.001831 0.048174 0.027969 -0.037174 -0.016494 -0.017171 0.005798 0.033841 0.025470 -0.005640 -0.017469 -0.022933 0.018680 -0.004736 0.002877 0.001373 0.037821 0.029846 -0.012691 0.019588 0.010886 -0.023464 -0.019051 -0.012527 0.031267 -0.032008 0.056834 -0.013729 -0.004210 0.001118 0.039384 0.012212 0.003794 0.023272 0.019548 -0.022292 -0.002447 -0.015174 -0.000192 0.022093 0.028381 -0.011896 -0.027223 0.000286 0.017698 0.007776 0.046287 0.014855 0.028707 0.019646 -0.016990 0.002287 0.004111 -0.009724 -0.016691 0.014733 0.068195 -0.005447 0.036763 -0.032278 -0.004217 0.004605 0.009424 0.024863 0.024091 0.039030 -0.009147 -0.040629 -0.022836 -0.007392 -0.006257 -0.015338 -0.026979 -0.021604 -0.022981 0.007207 0.004247 -0.004087 -0.008233 0.010530 -0.014894 -0.007378 -0.011403 -0.003863 -0.013877 -0.051449 -0.038957 -0.020155 0.062666 0.010998 -0.019650 -0.087962 -0.014412
</data>
</_>
<_ type_id="opencv-matrix">
<rows>15</rows>
<cols>160</cols>
<dt>d</dt>
<data>
0.015599 0.010749 -0.002373 -0.034702 0.001804 0.032455 0.000220 -0.018055 -0.022931 0.035544 -0.045896 -0.043803 -0.034601 0.043088 0.017988 0.004234 0.007782 0.004384 0.019615 -0.011496 -0.034917 -0.058873 0.016352 0.013960 0.006196 -0.012213 -0.002274 -0.038255 -0.005569 0.001176 0.029205 -0.014922 0.042302 0.032384 -0.007536 -0.006907 0.001262 0.015623 -0.027813 -0.028795 -0.021387 0.024794 -0.015965 0.014219 0.027400 0.044733 0.016640 -0.020574 -0.032911 -0.022589 0.036502 0.027947 0.003675 0.018727 0.026784 0.005227 -0.045817 -0.062807 -0.032726 -0.029763 0.000902 0.011070 0.034234 -0.003713 0.048365 0.003538 0.003032 0.025257 0.037767 0.024184 -0.006133 -0.007858 -0.016244 0.013302 -0.016205 -0.006515 0.030932 0.052454 0.058520 0.026308 -0.013482 -0.032054 0.045343 0.006551 0.016956 0.060276 0.062798 0.069803 0.011571 -0.015864 -0.029090 0.000684 0.046708 0.018778 0.039975 -0.003709 0.040376 -0.037539 -0.023846 0.002311 0.035256 0.049167 0.021595 0.022857 0.005270 0.007401 -0.022491 -0.030429 -0.050671 0.014524 0.031339 0.021463 0.046480 0.007905 0.038177 -0.047421 -0.038726 -0.048189 0.022248 0.055395 0.049325 0.074311 0.036397 -0.005605 0.059665 -0.016663 0.029055 -0.009667 0.018182 -0.040501 -0.053032 -0.047270 0.011180 0.015961 -0.044845 -0.029626 -0.009553 0.068140 -0.006897 -0.016904 -0.008807 0.037253 0.022397 -0.025556 -0.006370 0.001276 0.054817 -0.026430 -0.050557 -0.042138 0.031837 0.022779 -0.049491 -0.029269 0.006889 -0.020680 0.027314 -0.061115 0.000283 -0.009670
0.003782 -0.050468 -0.028108 0.001544 0.035832 0.064364 -0.003262 -0.011728 -0.025420 0.021825 -0.016734 0.001966 -0.035601 0.014230 0.016603 -0.026099 -0.028090 -0.013305 0.012060 -0.034562 -0.024164 -0.022135 0.012478 0.039655 -0.015303 -0.035264 -0.020146 -0.038800 -0.022470 0.007289 0.016895 -0.000910 0.056766 -0.001371 0.015929 -0.011587 0.008591 0.012817 -0.012987 0.010843 0.024213 0.022234 0.003173 -0.012982 -0.018981 -0.011580 -0.018183 -0.047433 -0.033632 -0.009289 0.061885 0.024512 0.028499 -0.013926 -0.010894 -0.030199 -0.055850 -0.015458 0.024670 -0.016570 -0.009484 0.003145 0.011849 0.010299 0.013991 0.049123 0.042437 0.008260 0.007543 0.013333 0.000161 -0.011427 -0.013004 -0.021244 -0.000015 0.012419 -0.008662 -0.028295 0.017914 0.023601 0.005170 0.007823 0.041254 0.055982 0.044160 0.028244 0.003786 0.014876 0.008710 0.009396 0.012742 0.004429 0.013005 0.011700 0.027023 0.010303 0.038748 0.056987 0.057341 0.027775 0.006616 0.009155 -0.002290 -0.003967 0.013120 0.019122 0.016850 0.013375 -0.007090 -0.009807 -0.007851 0.010282 -0.004999 -0.016449 0.047072 0.068541 0.049428 0.003440 -0.008257 0.004169 0.012458 0.008580 0.001760 0.015996 0.037904 0.015342 0.033014 0.004345 0.005633 -0.033569 -0.016157 -0.012989 0.013821 0.015080 -0.025184 -0.000480 0.001617 0.057043 0.021356 0.003065 0.005111 0.001484 0.002655 -0.045843 -0.047811 -0.043526 0.039239 0.014568 -0.009909 -0.002124 0.008580 0.016661 -0.053042 -0.037235 -0.038718 0.003443 0.016942 -0.042022 -0.024888 0.004342
0.036235 0.003898 0.032046 -0.004907 -0.001976 0.007595 -0.018855 0.003740 0.013135 -0.006270 -0.033363 0.024669 0.007951 -0.019383 0.003263 -0.006658 -0.012530 -0.012379 0.022039 -0.017977 0.054071 -0.000905 -0.004733 -0.004704 -0.026130 -0.004578 0.002134 0.009650 -0.031091 0.019199 0.009883 0.000784 0.010030 0.015756 0.063683 0.053549 0.023553 0.019716 0.004570 0.032543 0.048532 0.036643 0.007434 0.029755 0.029358 -0.019272 -0.055624 -0.027505 -0.009994 -0.014686 0.041628 0.031681 0.092944 0.098255 0.025544 -0.028616 -0.020795 0.017421 0.028158 0.041797 -0.003726 0.052304 0.026552 0.011993 0.011567 0.026509 0.037385 0.033751 0.017506 0.032082 0.011592 0.022867 0.001199 0.000946 0.029006 0.016886 -0.017231 -0.043271 -0.038279 0.020538 -0.003299 0.007350 0.035041 0.046437 0.045662 0.026198 0.004562 0.008056 0.027384 0.015728 0.018041 0.029669 -0.003155 0.046807 0.005452 0.011998 0.037282 0.052028 0.033694 0.029007 -0.006976 0.043405 0.050592 0.001872 0.006932 -0.021082 0.016171 0.049777 0.006284 -0.039992 0.000453 0.051245 0.030068 0.009055 0.025080 0.070908 0.047261 0.034341 -0.013486 0.042800 0.070923 0.053214 0.040546 0.055190 0.027059 0.060244 0.022409 0.006040 0.021909 -0.005997 0.017414 0.005887 0.022421 0.030058 0.038847 0.016931 0.001829 0.029640 0.005744 0.000682 0.003218 -0.006589 -0.001477 -0.015132 -0.034392 -0.043247 0.020033 0.020696 0.013463 -0.000235 0.021363 0.026884 0.029477 0.008411 -0.017765 0.030481 0.021329 0.010533 -0.020979 0.006037
0.025151 0.045934 0.026482 -0.033884 -0.009136 -0.015131 -0.042078 0.005438 -0.004722 -0.027220 0.005009 0.007082 0.045815 -0.000698 -0.016545 -0.020495 -0.011495 -0.004228 0.051111 0.060786 0.080820 0.018480 -0.019064 -0.052053 -0.059655 -0.018173 -0.009230 0.026316 -0.027776 0.002819 -0.013012 -0.011216 -0.015396 0.022609 0.027745 -0.041595 -0.026707 -0.019149 -0.035700 -0.017608 -0.024121 -0.037712 0.002332 0.006991 0.019313 -0.018256 -0.011444 -0.002791 0.004722 0.018685 -0.014162 0.013322 0.050985 0.018944 -0.029215 -0.022612 -0.031752 -0.001485 -0.016634 0.029692 -0.064031 -0.001891 -0.033577 -0.000007 -0.040430 -0.026027 0.006714 -0.000101 -0.016738 0.025635 0.012613 0.028170 0.003181 -0.025240 0.004916 0.001426 0.003984 -0.035400 -0.018554 0.001332 -0.012488 0.025070 -0.030590 -0.042450 -0.012589 0.011472 -0.031920 0.010103 0.004881 0.013362 0.007141 0.022184 -0.054118 0.044763 -0.042027 -0.000002 -0.028084 -0.004821 0.026107 0.000214 -0.032655 -0.001109 0.004670 0.022845 0.014600 -0.053842 -0.000106 0.005560 0.016205 -0.021400 -0.011027 0.008456 -0.000165 0.000129 0.001589 -0.005300 0.022479 0.019793 -0.032493 0.011140 0.019211 0.024485 0.019675 -0.004304 -0.030689 0.052262 -0.042923 -0.005960 -0.024629 -0.031518 0.013197 -0.002783 0.018663 -0.003968 -0.016393 -0.003724 0.012595 0.000311 -0.028182 -0.012018 0.001592 -0.037165 -0.005943 0.007149 0.014683 0.025460 0.042371 -0.046631 -0.002430 0.008460 -0.016301 0.006748 0.016449 0.039090 0.043062 0.000501 -0.005418 0.003846 -0.033188 -0.005963
0.011117 0.060208 0.012633 0.000450 0.016402 -0.007716 -0.011057 0.003006 -0.003825 -0.017013 -0.017571 -0.031006 -0.016380 -0.023586 -0.033609 0.005520 -0.013144 0.005466 0.046391 0.049278 -0.010998 -0.012918 0.002838 -0.030020 -0.001451 -0.013667 0.006463 -0.002439 -0.000857 -0.016688 -0.008350 -0.011216 0.013486 0.002476 -0.008196 -0.013284 0.008794 -0.008143 -0.031897 -0.041667 -0.037372 -0.013672 -0.003403 -0.038423 -0.023247 -0.010286 -0.016997 0.005548 -0.000506 0.058469 0.032862 -0.014547 -0.040605 -0.044242 -0.016704 -0.027094 -0.023179 -0.025982 0.005932 0.012128 -0.018859 -0.031706 -0.036196 -0.000007 -0.027165 -0.012099 -0.003581 -0.012240 -0.030799 -0.010302 -0.007816 -0.009649 -0.016366 0.006093 0.025793 0.007292 0.004793 -0.016817 -0.012595 -0.008103 -0.012738 0.017258 0.006819 0.005659 -0.015394 -0.017731 -0.052897 -0.031207 -0.018998 -0.020438 -0.015841 -0.009241 -0.038179 0.010704 -0.019400 -0.000002 -0.035276 0.006393 0.010469 -0.021617 -0.013653 -0.012536 -0.019515 0.018476 0.019137 -0.012604 0.030514 0.034555 0.032876 -0.004460 -0.012579 -0.043987 -0.034260 -0.016879 0.019624 0.029266 0.031027 0.012840 -0.013166 -0.015942 -0.046201 -0.020473 0.002851 -0.025388 -0.040379 0.032909 -0.002471 -0.005960 0.012626 -0.014299 -0.002193 0.019533 0.035548 0.014131 -0.034164 -0.032245 0.004685 -0.046375 -0.042071 0.002253 0.009951 -0.011782 -0.031538 -0.030693 0.014870 0.034105 0.036614 -0.045808 -0.009970 0.022165 0.009846 -0.011291 -0.045947 0.003190 0.029464 -0.010542 -0.014429 -0.002508 -0.018558 -0.005963
0.023802 0.024208 0.002001 0.002626 -0.007482 0.016145 0.023265 0.011190 0.009492 -0.017564 0.013802 -0.003696 -0.023857 -0.009276 0.002558 0.007014 0.004576 0.006328 0.069001 0.021096 -0.012606 -0.022106 -0.009901 0.014206 0.031054 0.014492 0.024481 0.012418 0.023316 0.001626 0.002771 -0.011216 -0.007400 0.012172 -0.004344 -0.023295 -0.024525 -0.002492 0.003784 -0.032485 0.030391 -0.032887 -0.009425 -0.004890 -0.001696 -0.006982 -0.021038 -0.011199 0.003303 0.050523 0.024103 -0.001685 -0.017439 -0.027664 -0.028846 -0.026261 -0.002720 -0.004468 0.029385 0.012193 0.024040 -0.040830 -0.034288 -0.000007 -0.039294 -0.015471 -0.023323 -0.020007 -0.027701 -0.016589 -0.024140 -0.018064 0.006288 -0.010578 -0.005513 -0.014054 -0.017903 -0.034189 -0.041899 0.007796 0.011722 0.038037 -0.013465 -0.022163 -0.033171 -0.038432 -0.055278 -0.055130 -0.020610 -0.001518 0.004024 -0.031475 -0.037474 -0.025914 -0.020575 -0.000002 -0.040589 -0.022229 -0.023745 0.006276 -0.016739 -0.003664 0.014011 0.020744 0.057195 0.002774 0.015334 0.007255 -0.005734 -0.009916 -0.007962 -0.007032 -0.014060 0.004208 0.020275 -0.002301 -0.003058 -0.005701 -0.021726 -0.004278 0.002880 0.016344 0.035137 -0.026879 -0.035035 0.022480 0.028181 -0.005960 0.001828 -0.004691 -0.016940 0.007393 0.038142 0.015863 -0.028976 -0.015735 0.005266 -0.040753 -0.034744 0.009441 0.002725 0.009246 -0.014934 0.008104 0.033271 0.053650 0.035355 -0.018287 -0.009877 0.012972 0.038247 -0.000197 -0.017295 0.015926 0.055643 -0.006356 0.002232 0.004559 0.012838 -0.005963
-0.013626 0.034397 0.009155 -0.017061 -0.018925 -0.019323 -0.013553 -0.008717 -0.001279 -0.020881 0.017611 0.000939 -0.016535 0.007162 0.018593 -0.005833 -0.010776 0.006918 0.060990 0.039241 -0.000950 -0.037379 -0.005912 0.009177 -0.014993 -0.012827 0.010002 0.001447 -0.002780 -0.000232 -0.022822 -0.011216 -0.029796 0.014809 0.012512 -0.022960 -0.005708 -0.019036 0.013707 -0.000032 0.022590 -0.031176 0.013216 -0.010916 -0.019282 -0.051475 -0.020005 0.003531 0.008517 0.021787 -0.000265 0.013277 -0.004362 -0.033446 -0.029188 -0.027508 -0.004382 0.013025 0.013346 0.012826 0.014498 -0.032680 -0.041651 -0.000007 -0.057568 -0.015148 -0.022485 -0.004454 0.000816 -0.019897 -0.021178 0.005447 0.020306 -0.025578 -0.007288 -0.026477 -0.024110 -0.012665 0.024652 0.004039 -0.013176 0.010680 -0.044177 -0.026884 -0.042848 -0.021334 0.007313 -0.000717 -0.021788 -0.006816 0.004123 -0.032406 -0.020711 -0.021896 -0.011765 -0.000002 -0.014968 -0.020292 -0.006082 -0.010781 0.003513 -0.000172 0.012488 -0.003593 0.052454 0.005403 0.012888 -0.004325 -0.003479 0.003588 -0.005415 -0.009362 -0.006992 0.012872 0.062116 -0.006995 -0.004076 -0.012558 0.015836 0.004692 -0.017033 0.003119 0.052967 -0.020547 -0.023843 0.014798 0.037958 -0.005960 0.002621 0.030297 0.012046 0.001151 0.050676 0.023365 -0.007256 -0.000821 0.036825 0.003725 -0.021058 -0.026589 -0.028029 0.002153 -0.011016 0.000204 0.013602 0.041126 0.063558 0.018583 -0.009444 -0.019698 0.048504 0.006115 -0.010968 0.018488 0.059299 0.011692 0.005780 0.017701 0.022819 -0.005963
0.035038 0.034212 -0.007377 -0.008382 0.018774 0.005904 -0.002078 -0.010885 -0.014694 -0.002031 0.034842 -0.019346 -0.015246 -0.012142 -0.032810 -0.025486 0.017974 -0.016614 0.080173 0.076564 -0.012892 -0.023748 0.018024 0.002488 -0.022486 0.013149 -0.011300 -0.002503 0.003234 -0.000698 -0.009623 -0.005867 -0.023254 -0.011583 0.001015 -0.010975 0.017273 -0.004703 -0.004411 0.009521 -0.015232 -0.029989 0.009079 0.004431 0.004709 -0.024370 -0.036581 -0.036513 -0.010525 -0.004937 -0.009405 -0.010662 0.002903 0.000405 0.020497 0.014323 -0.017539 -0.001576 0.001268 0.002948 -0.002744 -0.036628 -0.042321 0.005342 -0.026433 -0.021632 -0.015561 -0.006211 -0.013543 0.009767 0.010645 0.017341 0.028438 -0.029073 -0.024375 -0.024284 -0.020337 -0.018238 -0.027290 -0.025540 -0.014534 0.002211 -0.036039 -0.039116 -0.040327 -0.016999 0.002872 0.025991 -0.005799 -0.001601 0.008692 -0.031181 -0.032746 -0.010381 -0.019336 0.005346 -0.000719 -0.001937 0.008350 -0.004709 -0.034737 -0.019124 0.007047 0.017388 0.045454 0.006260 -0.018831 -0.020306 -0.012981 -0.030692 -0.049876 -0.005775 -0.030165 0.007365 0.061251 0.006737 -0.013398 -0.016176 -0.021778 -0.016156 0.008173 -0.003508 0.036160 -0.035864 -0.029437 -0.006740 0.006993 -0.000612 0.024702 -0.003078 0.011508 -0.003910 0.023425 0.003084 0.007110 -0.006930 0.031224 0.018274 -0.002131 -0.013367 -0.009874 -0.011338 -0.035343 -0.008425 -0.015158 0.043392 0.066308 0.014249 0.004324 -0.019667 0.017815 -0.019798 -0.007944 -0.017587 0.040628 0.031556 -0.003456 -0.005769 0.002729 -0.000615
0.043923 0.018531 -0.035176 -0.002091 -0.001414 0.005211 0.000084 0.017851 0.034657 0.026639 0.022431 -0.019031 -0.015808 -0.008682 -0.015843 -0.003220 -0.013244 0.020126 0.125608 0.042746 -0.050790 -0.021705 0.013397 0.021518 0.000126 0.013379 0.070002 0.009013 0.015265 0.006065 0.004986 -0.013967 -0.023995 -0.030442 -0.016802 0.022094 -0.014654 -0.022160 -0.008847 0.012489 -0.005602 -0.020752 0.015279 -0.011497 -0.011668 -0.026474 -0.006410 -0.027695 -0.027514 0.014654 0.034524 -0.011046 -0.024956 0.009643 -0.009375 0.002795 -0.022656 -0.003686 0.025496 -0.006241 -0.004868 -0.036435 -0.042020 -0.002758 -0.024778 0.015400 0.013193 -0.006163 -0.032043 -0.029955 -0.005766 0.002277 0.010529 -0.024022 -0.016217 -0.027260 -0.011953 -0.020966 -0.013681 -0.023955 -0.016380 0.014251 -0.007339 0.005422 -0.012315 -0.027798 -0.026504 -0.006784 -0.027864 0.001198 0.014964 -0.032995 -0.033235 -0.015006 -0.011860 -0.002753 -0.001404 0.002562 0.029051 0.001425 -0.011270 -0.039295 -0.005196 0.033856 0.035604 -0.003716 -0.002623 -0.007859 0.000888 -0.007085 0.003574 0.004298 -0.008535 -0.001292 0.078395 0.000731 0.014586 -0.005629 -0.005175 -0.000021 -0.002151 0.006590 0.021342 -0.006191 -0.011442 0.013221 0.015246 -0.008711 0.011482 0.024095 0.016276 0.009837 0.011340 -0.016573 -0.005594 0.002529 0.032636 0.027086 0.021586 -0.003025 0.014130 -0.002980 -0.017096 -0.010327 0.005300 0.022181 0.076625 0.035701 0.010740 0.009233 0.035286 0.007709 -0.020679 0.005215 0.038260 0.056371 0.027431 -0.005565 -0.010882 -0.008714
0.009192 0.020263 0.003892 -0.009972 0.009292 0.001455 -0.009875 0.020158 0.075241 -0.033146 -0.017313 -0.011485 -0.004596 0.001971 -0.018644 -0.017294 -0.025038 0.017149 0.060137 -0.003526 -0.010949 -0.013245 0.002529 -0.004193 -0.023206 -0.000010 0.079792 -0.005365 -0.005101 0.015142 0.000627 -0.007810 -0.019925 0.007929 0.006767 -0.023775 -0.018995 -0.019528 -0.008549 0.010084 0.038288 -0.001870 0.020743 -0.022093 -0.045584 -0.038394 -0.051934 -0.032536 -0.029610 -0.012707 0.048834 0.008093 -0.019074 -0.069315 -0.062813 -0.044036 -0.031642 -0.020390 0.037842 -0.011164 -0.012299 -0.046423 -0.044047 0.003399 -0.000967 0.031864 0.000899 0.003306 -0.008719 -0.030001 0.013413 0.026394 0.043154 -0.019510 0.016077 -0.057785 -0.046779 -0.019323 -0.035354 -0.029461 0.008727 0.011106 -0.005464 0.030680 -0.040804 -0.041239 -0.040893 -0.045519 -0.018648 0.019480 0.036359 -0.012034 -0.021141 -0.001496 -0.009149 0.003404 0.012552 0.005326 -0.022752 -0.000290 0.000840 -0.017015 -0.008308 0.027852 0.040138 -0.055575 0.009688 -0.029635 -0.027829 -0.006450 -0.019141 -0.018240 -0.004682 0.005702 0.055887 0.016284 -0.039426 -0.030673 -0.011453 -0.023552 -0.027029 0.005392 0.026496 -0.005986 -0.030225 -0.000589 -0.014026 -0.002554 -0.019376 0.005975 -0.023059 -0.010907 0.030725 0.015290 -0.019463 -0.002294 0.033896 -0.021032 -0.007390 -0.026514 0.001251 -0.000768 -0.021565 -0.030763 0.003116 0.001072 0.024718 0.010571 -0.043438 -0.009823 0.026107 0.000837 -0.048284 -0.008095 0.024932 0.019793 0.004734 -0.026847 -0.040957 -0.002557
-0.023702 0.003152 0.004877 -0.008209 0.004238 0.017302 -0.027905 -0.028487 0.023900 -0.013211 0.038484 0.006500 -0.010127 -0.029054 -0.046578 -0.028258 -0.041299 -0.019111 0.029062 0.027787 -0.000144 -0.016995 -0.020812 -0.016160 -0.057029 -0.061328 0.006523 -0.036413 -0.033679 0.004692 -0.018268 -0.009293 -0.003456 0.029854 0.009110 -0.028285 -0.025313 -0.005208 -0.010243 -0.029738 0.019555 -0.011373 0.024017 0.001411 -0.011199 -0.025234 -0.038487 -0.014030 -0.020615 0.002627 0.044988 0.012428 0.011158 -0.038082 -0.042039 -0.033316 -0.026766 -0.042832 0.035909 -0.009557 0.002085 -0.025759 -0.031165 0.001916 0.005426 0.027833 0.001354 -0.001166 -0.029904 -0.007210 0.003812 0.017439 0.051578 0.001273 0.013311 -0.026908 -0.001890 -0.021090 -0.048196 -0.015685 0.010035 0.023273 0.016324 0.035402 -0.011616 -0.015444 -0.038648 -0.048658 -0.018343 0.025596 0.061154 -0.008695 0.002751 -0.004384 0.011877 0.001921 -0.010812 0.036186 -0.014196 -0.010761 -0.024272 -0.015227 -0.001980 0.007919 0.033687 -0.056896 0.020623 -0.013168 -0.029925 -0.024885 -0.032635 -0.019123 0.018828 0.003928 0.040472 0.059151 -0.030055 -0.039848 -0.046059 -0.042332 -0.016923 0.018774 0.028435 -0.017177 -0.019945 -0.019186 -0.006251 -0.004037 -0.020125 0.008884 -0.013108 -0.025962 0.027890 0.020593 -0.021249 -0.008937 0.023273 -0.034817 0.012636 -0.039097 -0.044191 -0.030552 0.001368 -0.004581 0.017434 0.024719 0.031100 0.013094 -0.050526 -0.060737 0.013031 0.004633 -0.019802 -0.005102 0.010027 0.009745 0.008597 -0.033245 -0.034983 -0.004040
-0.038877 0.005417 0.004005 -0.025450 -0.007027 0.030240 0.011541 -0.023749 0.009701 0.016215 0.011537 0.002326 -0.043456 -0.026835 -0.037523 -0.042538 -0.038550 -0.021362 0.031739 0.001586 -0.001914 -0.058719 -0.018412 -0.001470 -0.040679 -0.055015 -0.005472 -0.048775 -0.041777 -0.002545 -0.007964 -0.007481 0.007905 0.072397 0.022618 -0.009847 -0.008450 -0.000329 -0.011342 -0.019153 0.003470 -0.012304 0.017466 0.012296 -0.031822 -0.034125 -0.038586 -0.028025 -0.029342 -0.030559 0.035317 0.046941 0.035886 -0.035000 -0.026775 -0.025856 -0.039171 -0.041406 -0.019397 -0.023798 -0.000191 -0.013157 -0.018353 0.003728 0.033342 0.064590 0.031086 0.000345 -0.011236 -0.031193 -0.022294 0.014805 0.027548 0.008576 -0.002577 -0.016181 -0.017678 -0.011246 -0.016480 -0.026442 -0.018003 -0.009043 0.007641 0.057613 0.019220 -0.022152 -0.026117 -0.046468 -0.046488 0.000360 0.010226 -0.013551 0.002323 -0.005895 0.016142 0.003733 -0.001407 0.046377 0.023273 0.013127 0.018872 0.004984 -0.020703 0.002972 0.007287 0.017519 0.020806 -0.005505 -0.016395 -0.016523 -0.026007 -0.025187 -0.008397 -0.022225 0.063877 0.066542 0.014553 -0.008078 0.002243 -0.033906 -0.041940 -0.002022 -0.008873 0.004163 0.005845 -0.014126 0.010184 -0.002226 -0.025740 0.023771 0.005404 0.002932 0.039236 0.040562 0.000078 0.003174 -0.005922 -0.041351 0.011883 -0.017370 -0.040248 -0.018864 -0.017198 0.003769 0.029210 0.021863 0.013301 0.010734 -0.012062 -0.030424 0.024129 0.007303 0.000819 0.018100 0.002206 0.034817 0.021583 -0.029851 -0.019389 -0.002228
-0.012242 0.048615 0.013869 0.004029 0.003472 0.001289 -0.005664 -0.006688 0.028833 0.011329 0.007074 0.006155 -0.028585 -0.029839 -0.038546 -0.017004 -0.028975 -0.028215 0.053133 0.020598 -0.005269 -0.035675 -0.019790 -0.018295 -0.037575 -0.030289 0.009049 -0.043507 -0.032317 0.025048 0.017263 0.002724 0.019682 0.047995 0.017322 -0.027513 -0.006028 -0.011033 -0.010813 -0.022311 0.013613 0.021838 0.024494 0.010813 -0.011234 -0.027611 -0.031811 -0.013513 -0.037035 -0.032228 0.062882 0.026103 0.011725 -0.042748 -0.018816 -0.035359 -0.038745 -0.048947 -0.012427 -0.022405 -0.009289 -0.005011 0.001174 0.013933 0.055017 0.033369 -0.017218 -0.018469 0.009794 -0.036040 -0.013130 -0.012925 0.006062 0.026116 0.019176 -0.011272 -0.022718 -0.023878 -0.024393 0.004495 -0.000285 0.010920 0.021457 0.030037 -0.009095 -0.045051 -0.008445 -0.052876 -0.023510 -0.014126 -0.019776 -0.005275 0.001528 -0.010234 0.006731 0.013938 0.040127 0.033619 -0.016058 -0.026358 -0.010720 -0.024547 -0.018897 -0.005030 0.006367 -0.020303 0.017745 0.004397 -0.013894 -0.041048 -0.042137 -0.030546 -0.013621 0.038605 0.066657 0.042718 -0.019094 -0.048864 -0.033139 -0.050534 -0.047222 -0.022494 0.017688 -0.002920 -0.002511 -0.029482 -0.022738 0.007979 -0.019420 0.007514 -0.016465 -0.020335 0.001478 -0.009537 -0.005768 0.002381 0.011582 -0.017088 0.011989 -0.000896 -0.012272 -0.030822 -0.010919 -0.012770 -0.015262 0.021542 0.010589 -0.000935 -0.019877 -0.034380 -0.013309 -0.015099 -0.012498 -0.016980 0.015379 0.026676 0.016328 -0.050497 -0.046749 0.007977
0.010995 0.010662 -0.002719 -0.025547 -0.013991 -0.014449 0.003040 0.031552 0.016444 0.019258 0.014302 0.017035 -0.011347 -0.036935 -0.036096 -0.021351 -0.021177 -0.016608 0.050284 0.006447 -0.008440 -0.046771 -0.033588 -0.024008 -0.022577 0.005630 -0.002846 -0.049873 -0.047437 0.041014 0.020030 0.009673 0.024706 0.059490 0.032534 -0.000335 -0.006366 -0.033816 -0.003673 0.007769 0.031939 0.033936 0.033936 0.017274 0.007644 0.008274 -0.025541 -0.026815 -0.035796 0.010004 0.064935 0.054787 0.032918 -0.000165 -0.009267 -0.035945 -0.027128 -0.020648 0.034469 0.005026 0.002165 0.027057 0.029468 0.020879 0.050730 0.030188 -0.010019 -0.018073 -0.007987 -0.021048 -0.008327 0.003852 0.035173 0.030925 0.035495 -0.009215 -0.022079 -0.010843 -0.028516 0.015162 0.000996 0.047761 0.059562 0.051116 -0.009945 -0.045539 -0.016016 -0.012538 -0.015083 0.003503 0.051748 0.026090 0.009381 0.010092 0.008259 0.020886 0.029460 0.016714 0.025209 -0.009438 -0.013566 -0.032533 -0.005220 -0.006490 0.027198 -0.013106 0.007219 -0.013618 -0.015751 -0.013561 -0.017998 0.010330 0.023592 0.052705 0.050158 0.033464 0.003853 -0.033521 -0.015155 -0.020633 -0.006697 0.011648 0.055047 0.040112 0.008330 -0.005593 -0.018737 0.020354 -0.040331 -0.007081 -0.010652 -0.007822 0.009146 -0.005041 -0.016087 -0.006961 -0.005795 0.010475 -0.005471 -0.009093 -0.001323 -0.031881 -0.046266 -0.004667 -0.012807 -0.006073 0.003118 -0.025186 -0.037129 -0.032232 -0.019276 -0.041625 -0.030731 -0.028822 -0.012511 0.028192 0.002041 -0.048122 -0.075320 0.020351
-0.006257 -0.007392 -0.022836 -0.040629 -0.009147 0.039030 0.024091 0.024863 0.009424 0.004605 -0.008233 -0.004087 0.004247 0.007207 -0.022981 -0.021604 -0.026979 -0.015338 0.010530 -0.020155 -0.038957 -0.051449 -0.013877 -0.003863 -0.011403 -0.007378 -0.014894 -0.019650 -0.087962 0.062666 0.010998 -0.014412 -0.000192 -0.015174 -0.002447 -0.022292 0.019548 0.023272 0.003794 0.012212 0.039384 0.001118 0.046287 0.007776 0.017698 0.000286 -0.027223 -0.011896 0.028381 0.022093 0.014855 0.014733 -0.016691 -0.009724 0.004111 0.002287 -0.016990 0.019646 0.028707 0.036763 -0.032278 0.068195 -0.005447 -0.004217 0.005798 -0.017171 -0.016494 -0.037174 0.027969 0.048174 -0.001831 0.017744 0.039141 -0.006379 0.002877 -0.004736 0.018680 -0.022933 -0.017469 -0.005640 0.025470 0.033841 0.001373 -0.012527 -0.019051 -0.023464 0.010886 0.019588 -0.012691 0.029846 0.037821 0.056834 -0.013729 0.031267 -0.032008 -0.004210 -0.006261 0.004583 0.035993 0.018539 0.066088 0.028761 -0.028648 -0.007984 -0.020152 -0.040971 -0.043955 -0.001467 -0.004349 -0.016940 -0.017739 0.015896 0.037313 0.040816 -0.018035 -0.031090 0.019529 0.001371 0.035675 0.012126 -0.014879 0.021952 0.015302 0.068097 -0.002692 0.013255 -0.050600 -0.004217 -0.021836 0.000171 0.004018 0.023424 0.021565 0.010696 -0.039282 -0.010055 -0.015329 -0.006663 -0.021290 -0.011034 -0.004884 -0.008475 -0.008337 0.020986 0.008142 -0.015932 -0.013883 -0.029759 -0.013876 0.001253 -0.001478 -0.005894 -0.032229 -0.012433 -0.028005 0.050913 -0.002210 -0.007112 -0.076530 0.000846
</data>
</_>
</RootFilters>
<RootPCAFilters>
<_ type_id="opencv-matrix">
<rows>15</rows>
<cols>30</cols>
<dt>d</dt>
<data>
0.036621 0.008802 -0.019033 -0.152517 -0.040016 -0.009670 -0.073788 0.037254 -0.147937 -0.053372 0.026185 -0.009667 -0.117812 0.079659 0.049861 -0.064028 -0.024660 -0.003709 -0.009406 0.008244 0.096364 -0.089360 -0.027699 -0.003713 0.014001 0.024357 -0.054736 -0.089365 -0.007043 -0.014922
0.032800 -0.000956 0.060006 -0.092997 0.012988 0.004342 -0.090398 -0.069090 0.052776 -0.001193 0.032154 0.004345 -0.075403 -0.031849 0.036137 0.015493 0.015518 0.010303 0.005541 -0.084748 0.040766 -0.069620 0.044545 0.010299 0.028125 0.071115 -0.007950 -0.090019 0.035600 -0.000910
-0.051953 0.014680 0.009718 -0.022193 0.050435 0.006037 -0.162737 -0.044711 -0.017695 0.071354 0.032639 0.006040 -0.086521 -0.047888 0.024183 0.034178 0.069218 0.011998 -0.117254 -0.067258 0.110172 0.053944 0.078856 0.011993 -0.006979 -0.024147 0.037146 -0.001239 0.010311 0.000784
-0.000860 -0.016483 -0.052826 0.015380 0.015912 -0.005963 0.000404 -0.009569 -0.015708 0.075358 0.001514 -0.005960 0.033081 0.019645 -0.037609 0.053768 0.028459 -0.000002 0.049144 -0.029244 0.055066 0.049363 -0.033174 -0.000007 0.001438 -0.086387 0.109681 0.006449 -0.019948 -0.011216
0.025813 0.001203 0.017711 -0.018689 0.030113 -0.005963 0.022707 -0.038385 0.075505 0.011507 -0.006350 -0.005960 0.069277 -0.042025 0.010200 0.005734 -0.016081 -0.000002 0.073160 -0.031306 -0.018970 -0.058837 -0.005304 -0.000007 0.010461 -0.054640 0.014413 -0.021450 0.040967 -0.011216
-0.033492 0.006654 -0.017721 -0.014927 0.003179 -0.005963 0.001245 -0.032548 -0.035333 0.016374 0.010014 -0.005960 0.119078 -0.048782 -0.042641 0.021885 -0.004442 -0.000002 0.037220 -0.049742 -0.029535 -0.003099 -0.005632 -0.000007 -0.048261 -0.043951 -0.044174 -0.024014 0.020518 -0.011216
-0.070120 -0.029102 -0.030115 -0.058302 0.046262 -0.005963 -0.025660 -0.035473 -0.023048 -0.038116 0.007176 -0.005960 0.077285 0.044761 -0.037463 0.000960 -0.010442 -0.000002 0.044618 -0.049616 -0.033163 0.035512 0.023290 -0.000007 0.003548 -0.042516 0.009331 -0.038117 -0.025664 -0.011216
-0.028205 -0.065672 -0.000787 -0.051814 0.038691 -0.000615 0.030725 -0.081541 -0.030707 -0.009367 0.032978 -0.000612 0.069800 0.038830 -0.051886 0.003171 0.037368 0.005346 0.040662 0.019242 0.019588 0.011541 0.032790 0.005342 -0.020589 -0.063598 0.020188 -0.063989 0.032711 -0.005867
-0.076668 -0.067448 0.026057 -0.039006 0.009824 -0.008714 -0.026237 -0.058178 -0.006755 -0.005508 -0.005005 -0.008711 0.072086 -0.031815 -0.011311 0.010577 0.006527 -0.002753 0.047947 -0.019133 -0.004396 -0.009435 0.011581 -0.002758 -0.065050 -0.096430 -0.052904 -0.101573 0.019649 -0.013967
0.025549 0.001582 -0.003871 -0.051906 0.029752 -0.002557 0.036075 -0.053857 -0.035301 -0.031529 0.021629 -0.002554 0.054742 -0.081041 -0.051924 0.005204 0.046064 0.003404 0.101506 -0.107019 -0.023458 -0.029343 0.046182 0.003399 -0.019359 -0.055033 -0.023980 -0.035472 0.028852 -0.007810
0.038623 -0.007002 -0.054593 -0.059613 0.030486 -0.004040 0.048012 -0.093696 -0.031914 0.010310 0.019311 -0.004037 0.008284 -0.109536 -0.030267 0.017737 0.028833 0.001921 0.057584 -0.087937 0.021953 -0.024824 0.011876 0.001916 0.070580 -0.043438 0.067802 -0.041208 0.040781 -0.009293
-0.012318 0.016359 -0.031535 -0.005406 0.054148 -0.002228 -0.010647 -0.074475 0.062808 -0.034576 0.045725 -0.002226 0.018554 -0.096572 0.043938 -0.010815 0.021041 0.003733 0.049984 -0.074865 0.073388 -0.023974 0.045085 0.003728 0.085750 -0.026878 0.021185 -0.060108 0.056626 -0.007481
0.050101 -0.028921 -0.017505 -0.014491 0.012265 0.007977 0.058841 -0.123426 0.012828 -0.050370 0.016333 0.007979 0.035284 -0.084667 0.009153 -0.046982 0.003724 0.013938 0.044115 -0.087216 0.058200 -0.058979 0.022016 0.013933 0.035733 -0.067704 0.031257 -0.040325 0.052476 0.002724
0.100474 -0.016493 0.001261 -0.011686 0.027933 0.020351 -0.022684 -0.099301 -0.028120 -0.008879 -0.007213 0.020354 -0.036475 -0.123526 -0.029296 -0.056939 -0.000743 0.020886 -0.046350 -0.118139 0.071061 -0.028824 0.008207 0.020879 0.041278 -0.084509 -0.011324 -0.022296 0.027989 0.009673
0.046195 0.036676 0.017946 -0.001693 0.010842 0.000846 -0.026232 0.047339 -0.000317 0.023235 0.042284 -0.004217 -0.029835 -0.003763 -0.060872 -0.018769 0.028531 -0.004210 -0.042071 -0.031723 -0.021026 -0.010191 0.013643 -0.004217 0.049369 0.005233 -0.040402 -0.040319 0.024094 -0.014412
</data>
</_>
<_ type_id="opencv-matrix">
<rows>15</rows>
<cols>30</cols>
<dt>d</dt>
<data>
0.014312 0.023332 0.055520 -0.089554 -0.007871 -0.014922 -0.010101 0.009560 -0.095998 -0.089633 -0.026492 -0.003713 -0.118106 0.080170 -0.047860 -0.063934 -0.023828 -0.003709 -0.072725 0.034939 0.149745 -0.052922 0.024108 -0.009667 0.036660 0.008888 0.019476 -0.153158 -0.040752 -0.009670
0.028354 0.070950 0.009942 -0.088926 0.035293 -0.000910 0.005206 -0.084116 -0.040942 -0.069874 0.044937 0.010299 -0.075424 -0.032220 -0.035893 0.016817 0.016694 0.010303 -0.090614 -0.068665 -0.052724 -0.000383 0.033394 0.004345 0.032555 0.000425 -0.059449 -0.092272 0.013631 0.004342
-0.007164 -0.024083 -0.037399 -0.000648 0.010972 0.000784 -0.118255 -0.065293 -0.109661 0.052279 0.079638 0.011993 -0.086559 -0.047786 -0.023513 0.034875 0.069742 0.011998 -0.162144 -0.045884 0.018166 0.074289 0.033061 0.006040 -0.051862 0.015071 -0.008350 -0.021227 0.050814 0.006037
0.000593 -0.084948 -0.111290 0.005826 -0.018308 -0.011216 0.048838 -0.028959 -0.056536 0.049752 -0.032163 -0.000007 0.033576 0.018865 0.037674 0.055269 0.027638 -0.000002 0.000725 -0.010101 0.015052 0.076796 0.001231 -0.005960 -0.000544 -0.017471 0.052611 0.015194 0.015120 -0.005963
0.010177 -0.054568 -0.014594 -0.022631 0.041485 -0.011216 0.073098 -0.031976 0.018308 -0.059989 -0.005366 -0.000007 0.069374 -0.041907 -0.011683 0.006774 -0.015944 -0.000002 0.022250 -0.036878 -0.076265 0.011898 -0.005526 -0.005960 0.025334 0.001208 -0.017325 -0.020796 0.029864 -0.005963
-0.047786 -0.044870 0.044293 -0.022866 0.020203 -0.011216 0.037355 -0.050392 0.028529 -0.003321 -0.006130 -0.000007 0.119298 -0.049409 0.040780 0.021529 -0.005304 -0.000002 0.001565 -0.032623 0.034902 0.016976 0.009092 -0.005960 -0.033793 0.006283 0.018362 -0.017419 0.002462 -0.005963
0.003607 -0.042586 -0.009919 -0.037372 -0.025119 -0.011216 0.044899 -0.050255 0.032264 0.035874 0.023245 -0.000007 0.077526 0.044229 0.037609 0.000833 -0.011008 -0.000002 -0.025627 -0.035442 0.023153 -0.038683 0.006460 -0.005960 -0.070264 -0.029541 0.031483 -0.060369 0.045657 -0.005963
-0.020781 -0.063134 -0.019965 -0.064432 0.033233 -0.005867 0.040423 0.019829 -0.019037 0.010824 0.033022 0.005342 0.070183 0.038176 0.052592 0.003460 0.036229 0.005346 0.030884 -0.081797 0.029664 -0.009468 0.032254 -0.000612 -0.028500 -0.065473 0.000937 -0.053497 0.038554 -0.000615
-0.064699 -0.096963 0.052970 -0.101650 0.018694 -0.013967 0.048023 -0.019157 0.004032 -0.009293 0.011337 -0.002758 0.072198 -0.032202 0.010443 0.010873 0.006403 -0.002753 -0.026245 -0.058148 0.005928 -0.005758 -0.005008 -0.008711 -0.077054 -0.066800 -0.025989 -0.040413 0.010037 -0.008714
-0.019411 -0.055186 0.024098 -0.036601 0.028100 -0.007810 0.101696 -0.107000 0.022005 -0.029139 0.045859 0.003399 0.054930 -0.081519 0.051095 0.004207 0.045261 0.003404 0.036151 -0.054088 0.034846 -0.032483 0.020983 -0.002554 0.025351 0.001879 0.004705 -0.053417 0.029237 -0.002557
0.070202 -0.042272 -0.067973 -0.040719 0.041560 -0.009293 0.057494 -0.087722 -0.023306 -0.024358 0.012278 0.001916 0.008376 -0.109810 0.028915 0.017131 0.027903 0.001921 0.048247 -0.094120 0.030519 0.010472 0.018931 -0.004037 0.039014 -0.008033 0.055329 -0.059504 0.029996 -0.004040
0.085804 -0.026484 -0.020895 -0.058788 0.056884 -0.007481 0.049626 -0.074025 -0.073989 -0.023163 0.046604 0.003728 0.018157 -0.095991 -0.045045 -0.011448 0.021846 0.003733 -0.011147 -0.073409 -0.062915 -0.035225 0.046665 -0.002226 -0.012155 0.015689 0.032896 -0.005849 0.053875 -0.002228
0.035553 -0.067134 -0.031530 -0.040099 0.052978 0.002724 0.043759 -0.086272 -0.059199 -0.058673 0.023211 0.013933 0.035006 -0.084337 -0.010339 -0.048276 0.004295 0.013938 0.058658 -0.123306 -0.014461 -0.050870 0.016780 0.007979 0.050243 -0.029138 0.017096 -0.014391 0.012239 0.007977
0.041432 -0.084318 0.010193 -0.021633 0.027891 0.009673 -0.047029 -0.116695 -0.072107 -0.029986 0.009212 0.020879 -0.036369 -0.123788 0.028236 -0.057505 -0.001056 0.020886 -0.022660 -0.099929 0.026877 -0.009789 -0.007391 0.020354 0.100322 -0.016099 -0.001911 -0.012731 0.027772 0.020351
0.049726 0.005035 0.040661 -0.039509 0.023142 -0.014412 -0.042023 -0.031532 0.021316 -0.010672 0.012906 -0.004217 -0.029414 -0.004604 0.061757 -0.018602 0.027334 -0.004210 -0.026542 0.046851 0.001791 0.021248 0.042347 -0.004217 0.046019 0.036782 -0.017675 -0.002359 0.010979 0.000846
</data>
</_>
</RootPCAFilters>
<PartFilters>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>192</cols>
<dt>d</dt>
<data>
0.035732 -0.008720 -0.021893 -0.002435 -0.018121 -0.014058 -0.017443 -0.019029 -0.037319 0.045045 -0.028079 0.010731 -0.023287 -0.006230 -0.006273 -0.022910 -0.009932 0.000403 0.041147 0.002023 0.005307 0.001126 -0.025409 -0.017918 -0.035078 -0.018667 -0.018426 -0.061732 -0.013232 -0.016772 0.023940 0.002777 0.042866 0.003012 -0.003068 0.044648 0.042881 -0.008764 -0.050729 -0.014496 -0.035415 -0.018639 -0.027390 0.024162 0.075241 0.035814 -0.011089 -0.059830 -0.047692 -0.019576 0.002997 -0.013111 0.052297 0.111851 0.078376 -0.016975 -0.088971 -0.053906 -0.049135 -0.023509 -0.005975 -0.013616 0.029870 0.003541 0.035341 -0.010754 -0.027894 0.026044 0.072276 0.078459 0.009432 -0.024157 -0.028106 0.008127 -0.000939 -0.014769 0.045120 0.032119 0.038865 -0.005460 -0.060579 -0.046328 0.020851 -0.001620 -0.023084 0.075309 0.109066 0.111098 0.038138 -0.070615 -0.060107 0.015485 0.017046 0.008437 0.018804 0.003543 0.002923 -0.020865 -0.029588 -0.028359 -0.008187 0.065268 0.074602 -0.000959 -0.006302 0.027952 -0.012330 -0.038172 -0.017134 0.005800 0.069746 0.030158 -0.016107 -0.028886 0.020654 -0.024595 -0.063367 -0.043685 0.000824 0.105464 0.135706 0.027904 -0.005599 0.006635 0.026878 -0.003981 0.003258 0.003543 0.030546 -0.012927 -0.023998 -0.035725 -0.027261 -0.022420 0.007910 0.017834 0.002821 0.049329 -0.013334 -0.000879 -0.012139 0.003464 0.005373 -0.012701 -0.005595 -0.032417 0.043672 -0.019039 -0.023737 -0.041917 -0.025131 -0.017558 -0.005563 0.028824 -0.003603 -0.007982 0.025788 -0.038356 -0.018160 0.003543 0.024649 -0.024813 -0.018387 0.015312 0.047195 0.013122 -0.018588 -0.024495 -0.023546 0.031060 -0.005615 -0.013591 0.004597 0.026868 0.052674 0.009040 -0.021173 -0.031754 0.016204 -0.022244 -0.030248 0.019022 0.042631 0.048285 -0.003090 -0.022022 -0.040981 0.008324 0.031043 -0.033054 0.013746 0.003543
0.016853 0.019630 0.015043 -0.013962 -0.003398 0.014003 -0.021126 -0.011935 -0.009556 0.042053 0.051121 0.039643 -0.024648 -0.044948 -0.010477 -0.020907 -0.027315 -0.013180 0.042963 0.085913 0.076447 -0.008214 -0.033021 -0.002667 -0.034160 -0.031756 -0.005189 -0.022643 -0.017626 0.004763 0.034041 0.011092 -0.003093 0.065567 0.064871 0.025970 -0.002805 -0.018109 -0.026044 -0.040584 -0.036376 -0.022762 0.001361 0.082241 0.060692 0.016102 -0.018640 -0.029386 -0.031624 -0.029814 0.005507 0.072941 0.149767 0.103032 0.033473 -0.025549 -0.053893 -0.061115 -0.048473 0.025208 -0.007561 0.000563 0.008927 0.011856 -0.052455 -0.044116 -0.028575 -0.003398 -0.024133 -0.006154 0.019850 -0.030200 -0.020136 -0.040892 -0.023870 -0.003424 0.020000 0.047310 0.038316 0.014588 -0.002443 -0.052330 -0.077387 -0.060103 -0.020133 0.013543 0.042947 0.032031 0.045447 -0.008223 -0.056004 0.000934 -0.037757 -0.013986 -0.039729 0.011858 -0.060654 -0.054360 -0.057706 -0.032825 -0.033922 -0.050979 0.017371 0.016913 0.022724 -0.026810 -0.018071 -0.019960 -0.014327 0.005595 0.049864 0.075043 0.088595 0.018260 -0.047181 -0.065002 -0.066939 -0.041843 -0.014606 0.016769 0.111763 0.114874 0.064840 -0.010700 -0.013448 0.013914 -0.025240 0.011858 -0.004592 -0.031743 -0.016496 -0.022719 -0.000751 -0.017560 0.010254 0.021128 0.046876 0.031745 -0.022297 0.001845 -0.005443 -0.009948 -0.025938 -0.003200 0.049076 0.055462 0.044708 -0.035341 -0.006986 -0.024532 -0.014359 -0.038167 0.024284 0.092338 0.122492 0.005649 0.023139 0.003976 -0.006508 0.011858 0.005363 -0.007932 0.016027 -0.000784 0.028293 0.047364 -0.008565 0.003059 0.008590 0.002408 -0.016760 -0.013115 0.015448 0.047701 0.057618 -0.026051 -0.024526 -0.026344 -0.004147 -0.009634 0.008138 0.018197 0.031784 0.056514 -0.016671 -0.006301 -0.001726 0.021773 0.035835 -0.010911 0.004119 0.011858
0.059055 0.012531 0.002643 -0.049883 0.013849 0.008124 -0.018202 0.020389 0.011660 0.046324 0.062672 -0.027427 -0.001371 -0.007575 0.016132 -0.006422 -0.013430 0.023952 0.066535 0.091481 0.009089 -0.032898 0.006263 0.012576 -0.019856 0.010650 0.042950 0.004308 0.003025 0.029345 0.035455 0.011099 -0.012970 0.003483 0.022532 -0.011744 0.013902 0.003645 0.039032 0.051800 0.076500 0.021355 -0.008281 0.019839 -0.008461 -0.014420 0.007507 -0.011912 -0.027484 -0.013138 0.032681 0.021547 0.046968 -0.003570 0.012967 0.021856 0.026612 0.030095 0.075830 0.035208 0.027280 0.002357 0.006423 0.011863 -0.055669 -0.041109 -0.028627 -0.011030 -0.015294 -0.011613 0.011463 -0.002652 0.018229 -0.014135 -0.020716 0.016855 -0.014405 0.033710 0.011684 0.001574 -0.028165 -0.063587 -0.049224 -0.054905 -0.001036 -0.012471 0.016941 0.003447 0.013642 -0.010664 -0.034596 -0.009583 -0.022250 -0.032746 -0.036059 0.011865 -0.025438 -0.033296 -0.041163 -0.023311 -0.034561 -0.044062 -0.027913 0.015136 0.044318 -0.026078 0.008407 0.018736 -0.007385 -0.003607 0.009661 0.030026 0.010940 -0.011986 -0.002927 -0.013996 -0.011721 -0.024391 -0.020423 -0.019173 0.020740 0.049988 0.038508 -0.031423 -0.030836 0.005360 -0.009840 0.011865 0.059092 0.035124 0.002103 -0.025852 0.009493 -0.014157 -0.035380 -0.053546 -0.016994 0.019886 0.021807 -0.001034 -0.030713 -0.039916 -0.016283 -0.010317 0.043152 0.098325 0.098687 0.069725 0.015523 -0.050640 -0.034335 -0.040891 -0.033364 0.030321 0.097572 -0.001821 0.006475 0.013250 0.003210 0.011865 -0.004546 -0.026415 -0.013330 -0.008345 0.024526 0.049893 -0.018236 -0.050942 0.023715 0.045317 -0.011793 -0.043179 0.003017 0.038155 0.007494 -0.019855 -0.038271 -0.001394 0.018174 -0.013241 -0.040190 0.001974 0.029682 0.023826 -0.021977 -0.060035 0.026146 0.010732 0.014524 -0.026863 -0.019222 0.011865
0.045713 0.015593 -0.000125 -0.037312 0.000918 -0.012318 -0.040078 -0.003631 0.025510 0.001490 0.017264 -0.007113 0.027016 0.033409 0.030102 -0.010506 0.025813 0.011031 0.038319 0.027933 -0.007705 -0.001655 0.022499 0.012867 -0.029293 0.021507 0.056992 -0.000124 0.008454 0.016128 0.033417 0.011233 0.015523 -0.022849 0.001521 -0.014710 -0.001017 -0.009445 0.018217 0.055317 0.090927 -0.034665 -0.007574 -0.011589 0.010760 -0.015775 -0.028912 -0.012993 0.038568 0.021745 0.002204 -0.011029 0.005441 0.002317 -0.013696 -0.024358 0.011795 0.100854 0.102257 0.023605 0.031621 -0.009781 -0.001582 0.011998 -0.030372 -0.046518 -0.022065 0.000818 0.019213 -0.004459 0.020159 0.025620 0.036691 -0.028171 -0.011837 0.004993 0.021754 0.020342 -0.001045 -0.028942 -0.034940 -0.041304 -0.036366 -0.046871 -0.009575 0.031798 0.027455 0.007815 0.012571 0.022383 0.009332 -0.010126 0.003561 -0.022993 -0.017611 0.012000 0.006109 0.026648 0.013027 0.000575 0.036819 0.004578 -0.016938 0.026196 0.049220 0.011158 0.028201 0.007963 -0.001577 -0.025383 -0.039348 -0.007060 -0.019948 -0.023975 0.051483 0.044736 0.020688 0.007020 0.025619 -0.011445 0.003174 0.025027 0.028774 -0.020580 -0.010739 0.024789 0.042479 0.012000 0.052453 0.076575 0.046405 0.016742 0.007613 0.003958 -0.008954 0.002852 -0.019566 -0.004503 0.011025 -0.004227 -0.030730 -0.030603 -0.016745 0.000330 0.023632 0.023260 0.082786 0.086020 0.047318 -0.002261 -0.017213 0.001048 0.009035 0.052004 0.033819 0.011668 0.016334 0.013398 0.029084 0.012000 -0.000242 -0.020826 -0.014196 -0.016109 0.006688 -0.007310 0.002061 -0.036521 -0.014416 0.003929 -0.003328 -0.020583 0.002012 -0.017546 0.013401 -0.006494 -0.023990 -0.021703 0.005332 -0.009855 -0.025835 0.002574 -0.020421 -0.001498 0.015419 -0.034025 -0.003864 0.002198 -0.000316 -0.043556 -0.040904 0.012000
0.005528 -0.018080 0.008959 -0.007237 0.075938 0.043813 -0.009828 -0.012468 -0.017555 0.007293 -0.043978 -0.014166 0.001722 -0.003690 0.030106 -0.009851 0.039684 0.013837 0.002162 -0.042232 0.000326 0.008453 0.062758 0.051677 -0.025751 0.044339 0.015937 -0.006249 0.009847 0.013201 0.025639 -0.000767 -0.010848 -0.017668 -0.036805 0.012990 -0.004961 0.001107 -0.000772 0.042687 0.056497 0.023354 0.021565 0.037596 0.031120 -0.001990 -0.009944 0.013211 0.054593 0.031620 0.036157 0.019284 0.012560 0.053648 0.015132 0.007989 0.036564 0.089243 0.087591 0.032054 0.056241 0.003127 0.023293 -0.000002 -0.022927 -0.018319 -0.030043 0.000433 -0.018827 -0.017492 -0.013233 -0.003480 -0.018839 -0.036108 -0.027039 -0.024113 0.043412 -0.009404 -0.029585 0.001786 -0.014419 -0.030016 -0.043510 -0.033122 -0.039218 0.049786 0.003643 -0.005440 -0.003595 0.005056 -0.032417 -0.036412 -0.012881 -0.049010 -0.028132 0.000000 -0.017766 0.002752 0.017414 0.006250 0.048097 0.021515 -0.003702 -0.013264 -0.028751 -0.002775 -0.008830 0.016752 0.010240 -0.052793 -0.045794 -0.019855 -0.050689 -0.001300 0.008010 0.006039 0.029642 0.038000 0.020474 -0.000175 -0.007112 -0.043782 -0.024547 -0.023599 -0.028270 -0.015391 0.009514 0.000000 0.037476 0.018098 0.006236 0.054551 0.045153 0.062820 0.031604 0.006064 -0.021018 -0.038170 -0.005081 -0.012495 -0.010858 -0.010865 0.002865 0.034193 0.023969 0.009064 0.028924 0.023538 0.010280 0.039522 0.028154 0.071117 0.086028 0.048354 0.000708 0.025191 0.024419 0.034116 0.026395 0.000000 -0.024480 0.012273 0.006883 -0.010198 -0.007835 0.017240 0.049300 0.007858 -0.011561 0.007912 -0.013007 -0.023159 0.009213 0.009822 0.010611 0.022014 -0.009836 -0.021100 0.006305 0.003270 -0.013795 0.001509 -0.001960 0.019304 0.055287 0.035874 -0.006759 0.006789 0.029330 -0.008888 -0.012169 -0.000000
-0.014790 -0.018474 0.035857 0.024997 0.004685 -0.018902 -0.004844 -0.028047 -0.035394 -0.022602 -0.018436 0.001782 0.045392 0.037168 0.007145 -0.016749 -0.009904 -0.046138 -0.018591 -0.019931 0.034634 0.065598 0.044473 0.010398 -0.033282 -0.024491 -0.070428 0.002381 -0.032586 0.003656 -0.009869 -0.000767 -0.017930 -0.001771 0.011756 -0.001121 0.001007 -0.012915 -0.007045 0.042679 0.055764 0.009251 0.014568 0.025255 0.014796 -0.001842 -0.015260 0.012591 0.043155 0.029404 0.004585 0.013724 0.019021 0.007255 0.013467 -0.005890 0.009647 0.074500 0.060065 0.034544 0.019243 0.038491 0.003105 -0.000002 -0.027245 -0.002804 0.010345 0.034682 -0.004211 0.006354 0.009710 0.027739 -0.004802 -0.018770 -0.029106 -0.006529 0.025900 0.004222 -0.021277 0.005281 -0.005173 0.013533 -0.025566 -0.025539 0.011972 0.036080 0.006636 0.001049 0.009472 0.019954 0.011878 0.013177 0.001632 0.001466 -0.007861 0.000000 -0.026528 0.019513 0.089015 0.061445 0.031311 -0.011799 -0.034869 -0.040947 -0.043652 -0.045359 -0.012807 0.001470 0.029816 -0.014273 -0.045569 -0.030604 -0.024470 -0.025038 -0.055849 0.001450 0.074791 0.062796 0.010435 -0.035047 -0.052828 -0.058722 -0.060733 0.007722 -0.029768 -0.013205 -0.022894 0.000000 -0.015825 -0.024911 0.007548 -0.024571 -0.023578 -0.034272 -0.015628 -0.002471 -0.042693 -0.037432 -0.004381 -0.023226 -0.009038 0.010012 0.008351 0.043333 0.026447 -0.000901 -0.049460 -0.037027 -0.021588 -0.034750 -0.015101 -0.005964 0.054719 0.030494 -0.030172 -0.001148 -0.041387 0.005390 -0.039804 0.000000 -0.008312 -0.033815 -0.013884 -0.023438 -0.045755 -0.013872 0.016814 0.035080 -0.023030 -0.054206 -0.058271 -0.036446 -0.011501 0.013605 0.042736 0.084352 0.049932 0.020165 -0.041615 -0.074235 -0.045173 -0.030505 -0.024436 0.046846 0.118457 0.116368 0.004981 -0.000156 -0.009903 0.013495 -0.031647 -0.000000
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>192</cols>
<dt>d</dt>
<data>
-0.009536 0.028299 0.026214 0.021322 0.049201 0.054863 0.024401 -0.002666 -0.012060 -0.030796 0.008439 -0.003394 0.006521 0.014264 0.001840 0.025604 0.003743 -0.002570 -0.022791 0.019178 0.010179 0.020318 0.035820 0.051757 0.045685 -0.011362 -0.006014 0.027694 -0.012522 0.051223 0.029623 0.006155 -0.024910 0.003046 0.016269 0.030011 0.032758 0.014561 -0.010393 -0.015577 -0.014370 -0.052633 -0.011398 0.003933 0.013183 0.017080 -0.010376 -0.020346 -0.014922 0.001412 -0.048640 -0.004931 0.011074 0.023895 0.022302 0.020417 -0.011393 -0.028357 -0.013343 -0.016807 -0.034543 0.035095 -0.003860 0.001899 -0.013696 0.008776 0.000802 -0.006601 0.026671 -0.001407 -0.022360 -0.002970 0.016615 0.002108 -0.022041 -0.002038 0.000849 -0.010796 0.002058 -0.001187 0.001008 0.025555 0.018009 0.002468 0.009805 -0.018730 0.012154 0.020783 -0.020423 0.004875 0.017998 -0.006698 -0.009573 0.021800 -0.004893 0.004850 -0.013449 -0.016282 -0.030457 -0.025218 -0.027962 -0.014257 -0.012360 -0.011294 0.029094 -0.029801 -0.005091 0.009524 -0.008201 -0.023077 -0.018817 0.029095 0.017750 0.028443 0.005377 -0.030384 -0.021240 -0.036936 -0.030552 -0.011004 0.004729 -0.003227 0.041000 0.002336 0.017535 -0.036389 -0.041162 0.010170 -0.044965 0.003043 0.010275 -0.014553 -0.027812 -0.001386 0.004195 -0.018660 -0.013634 -0.004166 0.007358 -0.007105 0.005841 -0.020995 0.004575 0.003384 0.000003 0.002281 0.008619 0.000962 -0.000890 -0.006753 -0.035521 0.001907 0.003634 -0.017948 -0.016194 -0.029343 -0.023583 -0.007195 0.007173 0.010797 -0.012893 0.019658 0.012862 0.015172 0.011579 0.017096 -0.013982 -0.010629 0.028181 0.017717 -0.009804 -0.025162 -0.028066 -0.021799 0.001072 -0.015480 -0.007029 -0.020622 0.019320 0.001812 -0.000738 -0.009781 -0.008904 0.007205 -0.025035 -0.002702 -0.015443 -0.018822 -0.010312 0.004712 0.004563 0.015598
0.011812 0.001537 0.017732 0.001464 0.015882 0.015692 0.023220 -0.002358 -0.016153 -0.017230 -0.009144 0.002062 0.020005 0.007348 0.021512 -0.010329 -0.019093 -0.004583 0.008587 -0.008580 0.009641 0.018770 0.022313 0.047349 0.012994 -0.010698 -0.010821 0.008839 -0.009693 0.017200 0.011643 0.005911 -0.004484 -0.005397 0.000510 -0.007683 0.022224 0.034478 -0.019266 -0.007386 -0.025859 -0.032732 -0.034179 -0.015324 0.019338 0.004564 -0.000764 0.012001 0.018954 0.004472 -0.022045 -0.029956 -0.019064 0.020104 0.019730 0.043838 -0.009840 0.001475 -0.021145 -0.024494 -0.039914 0.034739 0.012447 0.001654 0.001888 0.001933 0.000823 -0.008433 0.020192 0.010014 -0.004428 0.022207 0.055110 -0.031638 0.000895 0.001763 -0.002072 -0.018476 -0.010694 -0.012006 0.006158 -0.002970 0.015037 -0.000416 0.006765 -0.005715 0.009361 0.002512 -0.008968 0.025746 0.061821 -0.015439 -0.020626 0.039864 0.010468 0.004606 -0.025445 -0.028408 -0.009511 -0.014017 -0.022986 -0.015996 -0.020576 0.013934 0.039959 -0.014593 0.003634 -0.000484 -0.004886 -0.027326 -0.023416 -0.007242 -0.015678 0.039404 0.013743 -0.016770 -0.007758 -0.024543 -0.030105 -0.017278 -0.027394 -0.003522 0.056318 -0.011536 0.012395 -0.029265 -0.034590 0.009925 -0.003291 0.022749 -0.009335 -0.010697 -0.010303 -0.018531 0.000477 -0.023061 -0.027560 -0.061994 -0.000117 -0.024237 -0.013299 -0.039376 -0.044586 -0.014719 -0.013946 -0.008215 -0.010499 0.011881 -0.020762 -0.034193 -0.030328 -0.043157 -0.010378 -0.033037 -0.020956 -0.055413 -0.033584 -0.040093 -0.012349 0.010552 0.023061 0.023421 0.001402 -0.002748 0.019042 0.017837 -0.003918 0.019241 0.023288 0.002319 0.012201 -0.003735 -0.006093 0.001603 0.009923 -0.021682 -0.009223 -0.024486 0.052899 0.016099 0.001390 -0.011761 0.033214 0.028712 -0.029926 0.001774 0.000124 -0.009249 0.006787 0.007876 0.032983 0.015353
0.006293 -0.033385 -0.004694 0.013539 0.041627 0.012684 0.011828 0.002930 0.004350 -0.022085 0.004529 0.001516 0.028302 -0.002637 0.014079 0.010800 -0.015789 -0.006468 -0.011849 -0.028869 -0.011300 0.032617 0.031896 0.016694 0.013078 -0.011053 0.005625 0.006043 0.004840 0.013987 0.006911 0.005910 0.015266 0.000689 -0.003363 -0.000982 -0.004129 -0.006309 -0.017416 -0.035090 -0.044030 -0.042173 -0.024183 -0.017323 0.012441 0.023305 0.012467 0.006674 -0.013674 -0.018090 -0.012128 -0.028758 -0.023962 0.006186 0.016405 0.004659 -0.002211 -0.046077 -0.058385 -0.052793 -0.050931 0.014804 0.015419 0.001653 -0.018240 0.005958 -0.003367 0.008272 -0.011528 0.006028 -0.019104 0.004405 0.019812 0.006996 0.011493 -0.020399 -0.001574 0.006810 0.005000 0.006131 -0.006665 -0.005759 0.010155 0.011980 -0.015669 -0.000044 0.007257 -0.002972 -0.010080 -0.014346 0.014908 -0.041539 -0.027982 0.034766 0.032054 0.004604 -0.043597 -0.025039 0.009319 0.021350 0.006206 0.006179 0.033924 0.023246 0.039226 -0.008692 0.036706 -0.025827 -0.012499 0.004956 0.008241 0.001829 0.001509 0.013782 0.018197 0.022352 -0.005330 -0.006727 0.020708 0.009556 0.030375 0.020553 0.052469 -0.008155 0.035906 0.001307 0.013755 0.009924 -0.004923 0.027723 0.023414 0.014943 -0.014584 -0.009365 0.001611 -0.026908 -0.025527 -0.045605 0.017925 -0.006992 0.013099 -0.015390 -0.014760 -0.013775 -0.002280 0.003763 -0.002178 0.018587 0.028058 0.011375 -0.018248 -0.011009 -0.022454 -0.024259 -0.024649 -0.022915 -0.003680 -0.027982 0.017982 0.010551 0.035437 0.017953 0.002008 -0.008434 -0.007940 0.007270 0.018913 0.003560 -0.000313 -0.009006 0.008510 0.024845 0.025785 0.001125 -0.010342 -0.024901 -0.010199 0.011431 0.040171 0.011957 0.024127 0.011810 0.007073 0.013279 -0.010591 0.002063 0.015237 0.007270 0.010429 -0.001775 0.024475 0.015352
0.003075 -0.014803 -0.001133 0.005396 0.006431 -0.014221 0.017992 0.015211 0.006425 -0.011644 0.019422 0.010479 0.021925 0.005429 -0.028922 -0.020957 -0.024318 -0.023658 0.005436 0.003701 0.000301 0.006833 0.003263 -0.030715 0.002298 -0.013703 -0.017009 -0.011323 -0.016403 0.016532 -0.001945 0.005636 0.006469 -0.001421 -0.006553 0.004349 0.008372 -0.025453 -0.009222 -0.013116 -0.027250 -0.020147 -0.017368 -0.010588 0.007608 0.014796 -0.028152 -0.010978 -0.037573 -0.036093 -0.006670 -0.013164 -0.010595 0.004503 -0.002692 -0.039773 -0.025408 -0.047798 -0.059486 -0.067268 -0.056665 0.016002 0.012558 0.001379 -0.017109 0.003451 0.001624 -0.001895 -0.009062 -0.031901 0.009953 0.017401 -0.001772 -0.022770 0.002506 0.018364 0.019834 -0.017530 0.008927 0.006314 -0.009246 -0.027848 -0.009088 0.013094 0.023845 0.014512 -0.026249 -0.023820 0.011716 -0.005797 -0.029731 -0.050418 -0.034289 0.022239 0.038540 0.004331 -0.043195 -0.007466 0.018361 -0.008860 0.007291 0.000742 0.063586 0.047652 0.014252 0.022512 0.035126 0.032407 0.028918 -0.011621 0.009201 0.018907 0.010948 -0.036343 0.021923 0.028185 0.036906 0.022589 -0.006367 0.022175 0.050973 0.038172 -0.016536 0.001037 0.028832 0.026228 0.039322 0.009650 0.038027 0.041453 0.026821 0.023561 -0.014751 0.001255 0.029432 -0.007032 -0.026188 -0.013274 -0.017316 -0.006170 0.008212 0.008682 -0.012732 0.004612 0.023458 -0.008369 0.027599 0.006299 0.011164 0.025565 -0.006899 0.013188 0.019504 0.018478 -0.023057 0.010320 0.029462 -0.006788 0.013996 0.010277 0.050120 -0.005734 0.038172 0.034920 0.027230 -0.014876 0.001609 0.005079 -0.001165 0.015428 0.001571 -0.018199 -0.013821 -0.037549 -0.012670 0.006477 0.010001 0.032269 0.057737 0.000975 0.021788 0.024527 0.000534 -0.008403 0.017233 0.019763 0.027626 0.026979 0.027344 -0.010578 0.012287 0.015078
0.003947 -0.004624 -0.021068 -0.028488 0.004409 0.029255 0.036115 0.029581 0.031031 0.015611 0.003325 0.016381 0.012026 0.006368 0.013447 0.008119 -0.001221 -0.009510 0.028074 0.009220 0.001593 -0.005022 -0.006242 0.040492 0.043883 0.026676 0.026402 -0.004018 -0.002214 0.043678 0.030768 0.005636 0.004345 -0.002083 -0.019595 -0.009375 0.025984 0.054226 0.018291 -0.000492 -0.017783 -0.000202 0.005794 0.034026 0.056938 0.061795 0.031588 -0.012617 -0.033528 -0.018226 0.017478 0.011010 0.021536 0.047833 0.031413 0.027495 0.005975 -0.028099 -0.030843 -0.019383 -0.026530 0.062775 0.067559 0.001379 -0.013878 -0.020418 -0.015673 -0.026595 -0.002802 0.038372 0.034814 0.004643 0.000845 -0.000561 -0.000054 0.033952 0.073110 0.048605 0.034700 -0.004893 -0.005567 -0.033601 0.003010 -0.016746 0.008813 0.039776 0.015437 0.009336 0.018976 -0.010033 -0.024887 -0.011528 -0.026293 0.055370 0.050804 0.004331 -0.026703 -0.015445 -0.031994 -0.036694 0.044457 0.064100 0.034418 0.016897 -0.010152 0.007531 0.011562 0.024280 0.033824 0.008237 0.011991 0.034067 -0.005633 -0.035840 -0.007563 0.001715 -0.004285 -0.007476 0.021595 0.037743 0.049252 0.005711 -0.039229 0.009008 0.001968 0.035199 0.014590 0.009650 0.014482 0.021535 0.011857 0.024410 0.064600 0.044089 -0.013016 -0.012394 -0.025397 0.008821 -0.010466 0.006654 -0.003569 -0.001867 -0.011223 0.039495 0.000257 -0.010084 0.023796 0.005436 0.010148 0.016529 0.046154 0.035682 -0.001132 -0.007551 -0.027462 0.029369 0.018056 0.021683 0.000747 0.010277 0.039943 0.008480 0.014850 0.043143 0.027759 0.006804 -0.031184 -0.038497 0.004440 0.028071 0.000144 -0.001658 -0.007539 0.013617 0.036533 0.045915 0.011126 0.022074 0.067595 0.017510 0.007155 0.041254 0.044247 0.028782 0.006274 -0.020131 0.029575 0.052955 0.036701 0.011720 0.004228 0.015078
0.003021 -0.002354 -0.017527 0.008060 0.019642 0.028730 0.025057 0.004527 0.011711 0.023338 -0.008375 0.005607 -0.004002 0.008724 -0.004992 0.004851 0.001617 -0.029120 0.033099 -0.001971 -0.001882 0.001870 0.010076 -0.000797 0.013022 0.004504 -0.006703 0.018462 -0.027822 0.028676 0.017696 0.022133 -0.008979 0.003566 -0.014394 -0.022447 0.036574 0.083210 0.015159 0.022124 0.003901 -0.001452 -0.006549 -0.002344 -0.017963 0.010424 0.022775 0.000388 -0.007488 -0.014072 -0.008812 -0.002034 -0.017630 -0.033333 0.030187 0.046207 0.003201 0.011146 -0.003001 0.025419 -0.050705 0.061425 0.012148 0.017876 -0.020813 -0.023706 -0.016604 -0.039786 0.065863 0.074971 0.019693 0.003727 0.014240 -0.021638 -0.014638 -0.014075 -0.006016 0.008512 0.010976 -0.006631 -0.008711 -0.034240 -0.038767 -0.035758 -0.019719 -0.041903 0.026540 0.034783 0.016979 -0.006265 -0.014361 0.016971 -0.059079 0.053674 -0.015750 0.020828 -0.013389 -0.012856 -0.027461 -0.039557 0.067280 0.059436 0.006269 -0.013164 -0.028602 -0.022494 -0.001847 0.012693 0.007497 -0.014905 -0.004044 -0.025979 -0.005785 -0.041377 -0.030635 -0.017162 -0.008952 -0.034185 0.023693 0.037790 -0.003555 -0.020741 -0.059902 0.017530 -0.057202 0.035696 -0.042356 0.020829 -0.013317 0.002939 -0.003326 0.017365 0.064793 0.043236 -0.033283 -0.035863 -0.033219 -0.030855 -0.008009 -0.003394 0.010039 -0.010802 -0.002935 -0.009402 -0.011579 -0.031588 -0.033109 -0.001860 -0.008602 0.015592 0.034773 0.027507 -0.033998 -0.041964 -0.061053 0.029077 -0.043330 0.025097 -0.052892 0.020829 -0.003184 -0.007350 0.004839 0.044135 0.047930 0.022428 -0.010279 -0.028272 -0.027264 -0.015936 -0.005849 -0.003860 0.005052 0.008897 -0.012307 -0.001850 -0.016592 -0.016721 -0.005548 -0.007986 -0.003704 0.023389 0.023673 0.015348 -0.008951 -0.040026 -0.036753 0.048194 -0.029781 0.027956 -0.053999 0.020829
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>192</cols>
<dt>d</dt>
<data>
-0.012935 0.007775 -0.000675 -0.002979 -0.001396 -0.024028 -0.003375 -0.002623 -0.027330 -0.015037 -0.001305 0.017008 0.040644 -0.003948 -0.015861 0.002207 0.016023 0.009320 -0.015717 0.006465 0.020340 0.032293 0.023050 -0.010239 0.008684 0.029486 -0.015845 0.001549 -0.005134 -0.003561 -0.001582 0.000000 -0.024724 0.012177 0.048091 0.014543 -0.009661 -0.036839 -0.028223 -0.033498 -0.007329 -0.018350 -0.024377 0.023819 0.026728 -0.023504 -0.034061 -0.011738 0.012970 0.001117 -0.025322 -0.004158 0.039271 0.022300 0.005605 -0.033544 -0.016883 -0.013575 -0.014024 0.012841 -0.017307 -0.022441 -0.026296 0.000000 0.007368 0.004159 0.029154 0.039961 0.034395 0.042219 0.035143 -0.035163 -0.019300 -0.018226 -0.029987 -0.020532 -0.014575 -0.001230 0.001108 0.051591 0.027645 0.016668 0.004351 -0.018429 0.010736 0.011109 0.038434 0.060332 0.095164 0.010333 -0.005050 0.033507 0.001355 0.036747 -0.000711 0.000000 0.022161 0.003545 -0.007878 -0.016954 -0.001040 0.057559 0.063167 0.006893 -0.029683 -0.018761 -0.038184 -0.015715 -0.012747 -0.022995 0.022841 0.059706 0.025381 0.001551 0.001230 -0.026908 -0.021163 -0.027929 -0.009357 0.070732 0.132418 0.077541 -0.007001 0.010974 0.013492 0.032108 -0.009978 -0.000000 0.016383 0.016560 0.016853 -0.005826 -0.002499 0.005697 -0.018038 0.012595 -0.016309 -0.015379 -0.010769 0.014386 -0.001837 -0.012429 -0.008965 0.001955 -0.023825 -0.033434 -0.002784 0.006899 0.022706 -0.004142 -0.007306 0.001239 0.005050 0.039538 -0.023437 -0.006464 0.012018 -0.017093 -0.019046 -0.001385 0.017122 0.013110 -0.002643 0.006554 -0.001107 -0.020382 -0.041769 -0.049178 -0.020569 -0.005165 -0.006249 -0.002122 0.003806 0.018910 0.003838 -0.009349 -0.038902 -0.017870 -0.003182 0.012603 0.005584 0.020275 0.012493 -0.013390 -0.040918 -0.067519 -0.021369 -0.003877 -0.016679 -0.036706 -0.014375 -0.001392
-0.023688 -0.005455 -0.008837 -0.009943 0.014653 0.031579 0.025828 -0.021603 -0.037246 -0.003120 0.001513 0.003057 0.021687 0.019958 -0.016694 0.012987 0.003162 0.033855 0.001554 -0.011945 -0.009695 0.005206 0.010219 0.012190 0.028539 -0.021240 -0.015150 0.024324 -0.019630 0.028371 -0.013411 0.000000 -0.000434 0.039590 0.031418 -0.018588 -0.033309 -0.041168 -0.012593 -0.025668 -0.027099 -0.012622 -0.007989 -0.001908 0.016007 0.002730 0.000588 -0.033944 -0.012180 -0.001121 0.009237 0.020015 0.007418 -0.001693 -0.034674 -0.029088 -0.040936 -0.038137 -0.036649 0.034785 -0.023354 -0.022025 -0.054596 0.000000 -0.018976 0.003764 0.042561 -0.021602 -0.047472 -0.065776 -0.068335 -0.080860 -0.023627 -0.021428 -0.007621 -0.017996 0.003286 0.009511 0.002357 0.013386 0.011165 0.015540 -0.044926 -0.008454 0.010710 -0.015919 -0.037742 -0.042693 -0.035009 -0.063520 -0.013255 0.014623 -0.065163 -0.012272 -0.065466 0.000000 -0.032637 -0.042754 -0.025197 -0.034038 -0.043250 -0.038169 -0.027368 0.007688 -0.017944 -0.056340 -0.041745 -0.019011 -0.008105 -0.008565 0.034401 0.064081 0.006243 0.000595 -0.067040 -0.077232 -0.038261 -0.043393 -0.047206 0.006855 0.054434 0.051357 -0.020957 -0.035684 -0.067809 0.028700 -0.058196 -0.000000 -0.030387 -0.014647 -0.008169 -0.016373 -0.003073 -0.016450 -0.019917 0.067587 0.054629 -0.012014 -0.018229 -0.016695 -0.014272 -0.017665 0.037278 0.070447 0.026091 0.000268 -0.006267 -0.028239 -0.021397 -0.029704 -0.022437 0.012516 0.078685 0.149221 0.084717 0.005166 -0.000263 0.036091 -0.008746 -0.001385 -0.006341 -0.019024 -0.004934 0.004806 0.033838 0.012555 -0.033543 -0.007870 0.013668 0.011450 0.004605 -0.021404 -0.019812 0.016610 0.032832 -0.023302 -0.019661 -0.024664 -0.000143 -0.006776 -0.029992 -0.013550 0.032155 0.022159 -0.042106 0.003328 0.001294 0.001699 0.014940 -0.021435 -0.018864 -0.001392
-0.009268 0.006242 0.006018 -0.021799 0.020700 0.035215 0.000030 -0.019033 -0.027382 0.021169 0.017370 0.011308 0.005743 -0.000500 -0.008290 -0.002479 0.001246 0.008202 0.023297 0.002354 0.009545 -0.016232 0.014864 0.014339 -0.004256 -0.016783 -0.029917 0.018797 -0.016938 0.035773 -0.016657 0.000000 0.003261 0.017447 -0.000409 -0.012676 -0.012016 -0.016750 -0.023476 -0.022166 -0.021995 0.003488 0.016298 0.005628 0.020543 -0.005135 0.029691 0.026891 0.000181 0.019729 0.011693 0.017076 0.007322 0.010650 -0.012864 0.004998 0.006330 -0.023047 -0.012020 0.043873 0.016958 -0.006807 -0.040575 0.000000 -0.006619 -0.005542 0.002137 -0.042734 -0.062256 -0.053937 -0.062260 -0.047013 -0.020362 -0.010616 0.028441 0.010184 0.030060 0.031989 0.000010 0.041755 0.025026 0.021144 -0.004366 0.008434 0.004845 -0.004034 -0.016048 -0.041655 -0.016840 -0.018577 -0.011163 0.008926 -0.008193 -0.021594 -0.035987 0.000000 -0.021106 -0.036576 -0.004643 -0.027640 -0.043664 -0.048337 -0.079683 -0.091440 -0.025845 -0.021576 0.009691 0.012609 0.024993 0.012402 0.005835 0.031348 -0.009636 0.005371 -0.015690 -0.024623 0.002114 -0.015074 -0.030182 -0.025959 -0.033406 -0.078068 -0.040720 -0.047665 -0.079828 -0.000416 -0.017234 -0.000000 -0.017803 -0.021671 -0.005888 -0.023879 -0.028432 -0.020140 -0.050646 0.022737 0.070587 -0.003662 -0.017988 -0.010765 0.011496 -0.015549 -0.006467 0.027913 0.023589 0.032909 0.013883 -0.020153 -0.014153 -0.021288 -0.040950 -0.016413 -0.005610 0.078137 0.090039 -0.023289 -0.024323 0.039340 -0.007596 -0.001385 0.001219 -0.006669 -0.007961 0.009370 0.016922 0.021827 -0.034228 -0.004752 0.051337 0.030396 0.011834 -0.001489 0.009882 0.005857 0.012344 -0.019278 0.014987 0.026492 0.032806 0.014492 -0.006289 0.015616 0.011706 0.025314 -0.034233 0.037712 0.072021 0.010799 0.029753 0.018256 0.006287 -0.001392
-0.006232 0.022379 0.018955 0.005107 -0.007971 -0.013237 -0.029988 -0.003758 -0.023055 0.010679 0.012794 0.002753 0.008360 0.005819 0.013392 0.012512 0.010507 0.013488 -0.001116 0.002526 0.015703 0.000657 0.000437 -0.010051 -0.011376 -0.002601 -0.019602 0.016587 -0.016544 0.019782 0.004926 0.000000 -0.022692 -0.018846 -0.006271 -0.021973 0.003475 -0.013079 -0.011045 -0.005002 0.005889 0.002101 0.053476 -0.002574 0.034528 0.011262 0.013532 0.011496 0.007916 0.010809 -0.022007 0.017229 -0.001646 0.017357 -0.013710 0.003011 -0.002723 -0.000323 0.007965 0.025976 0.023373 0.003570 -0.027934 0.000000 -0.004041 -0.011713 -0.029100 -0.037588 -0.034937 -0.013486 -0.013591 -0.013784 -0.017760 0.003109 0.040153 0.031505 0.043797 0.032571 0.005916 0.014735 0.015095 0.010893 0.007886 -0.000592 0.000518 0.005199 -0.004702 -0.016071 -0.009083 -0.002620 -0.014693 0.007890 0.017509 -0.006495 -0.008640 0.000000 0.009471 0.003319 -0.009803 -0.025588 -0.039513 -0.019048 -0.026767 -0.041668 -0.006767 0.007807 0.037116 0.027710 0.028320 0.024648 0.026748 0.015470 0.012208 0.001002 0.011289 0.020337 0.004487 0.000554 -0.011601 0.009560 -0.017561 -0.032791 -0.023245 -0.004706 -0.013472 0.007220 0.022586 -0.000000 -0.018596 -0.024920 -0.026660 -0.025946 -0.029793 -0.019234 -0.025408 -0.018457 0.039368 -0.011575 0.004127 0.010083 0.011297 0.009553 -0.008589 0.011402 -0.023738 0.015398 0.002237 -0.019886 -0.010692 -0.010024 -0.014961 -0.017716 -0.011476 -0.025002 0.048127 -0.051008 -0.043589 0.025224 0.007295 -0.001385 0.015903 -0.028807 -0.002538 0.007139 -0.005464 0.007895 -0.033978 0.020966 0.029521 0.017201 0.006858 0.016167 0.017007 -0.011280 -0.000240 0.008179 0.006668 0.029282 0.046653 -0.010804 0.007191 0.010806 -0.016638 0.008580 -0.018972 0.035774 0.079137 -0.002508 0.013291 0.019735 0.016848 -0.001392
-0.005278 0.010101 0.010821 -0.024074 -0.030596 -0.000076 0.000770 -0.002716 0.007414 -0.009982 -0.001912 0.001349 -0.014215 0.013088 0.020222 -0.001460 0.007384 0.008453 0.002652 -0.008099 -0.000870 -0.020789 -0.012505 0.008667 -0.003622 0.001112 -0.002895 0.015420 -0.006707 -0.000852 -0.012908 0.000000 -0.018278 -0.026732 -0.007099 0.000587 -0.008117 0.009998 -0.007787 -0.015345 0.012958 -0.015015 0.006584 0.000438 0.011803 0.024921 0.016270 -0.009621 -0.006393 0.004775 -0.029420 -0.023974 -0.012953 0.006958 -0.005679 0.014604 -0.031447 -0.024556 0.007361 0.010700 -0.007869 0.002520 -0.017633 0.000000 -0.003496 0.009267 -0.032538 -0.014780 -0.007248 -0.015228 -0.011471 -0.008963 0.015909 0.027857 0.044821 0.019757 0.029216 0.012690 0.016270 0.011592 0.004450 0.023712 0.033146 0.029547 -0.002499 0.016268 0.001574 -0.016805 0.008490 -0.013112 0.022077 0.020963 0.017352 0.017180 0.001929 0.000000 -0.000985 0.028807 -0.010026 -0.033950 -0.038280 -0.036001 0.003926 0.008909 0.002550 0.036928 0.035800 0.011008 -0.012550 0.002093 0.017122 0.038170 0.013158 0.002336 0.036113 0.043381 0.001867 -0.028553 -0.018590 -0.014176 0.023931 0.013341 -0.003573 -0.004341 -0.000667 0.019890 0.017651 -0.000000 -0.031081 -0.025594 0.003034 -0.007414 -0.016808 -0.027073 -0.010850 -0.016432 0.025161 0.017569 -0.001287 -0.027150 0.003971 -0.006998 -0.008655 0.001305 -0.000485 0.022787 -0.002464 -0.012673 -0.026278 0.000461 -0.015716 -0.028295 -0.008746 -0.012426 0.026853 -0.057443 -0.046667 0.022913 0.031228 -0.001385 0.001526 -0.038005 0.028847 0.014221 0.022061 0.018849 -0.014938 -0.038735 0.020337 -0.005710 0.003143 -0.005403 0.015844 0.020199 0.011733 0.005427 0.005600 0.009215 0.022861 -0.010163 0.021386 0.025059 0.040288 0.028039 -0.009730 -0.018914 0.045592 -0.002385 0.007766 0.008768 0.020833 -0.001392
0.008828 -0.015090 -0.001382 -0.006695 0.019576 -0.005510 0.013623 -0.005300 0.026098 -0.012598 0.033584 0.015327 0.013229 0.019702 -0.007849 -0.001128 -0.000663 0.006516 -0.002868 0.012582 0.011924 0.005585 0.020136 -0.011418 0.006507 -0.004348 0.004268 0.038332 0.013670 0.003940 -0.008675 0.000000 -0.038196 -0.033274 -0.015711 0.022265 0.001905 -0.013222 -0.015221 0.008452 -0.000476 -0.000764 0.001597 0.013133 0.009962 0.020777 0.002658 0.015153 0.004596 0.000498 -0.019482 -0.033663 0.005384 0.006418 -0.004929 -0.021765 -0.008938 0.003824 -0.005154 0.004365 -0.010449 0.010367 -0.011763 0.000000 -0.042244 0.023558 -0.015060 0.017016 0.003806 -0.004113 -0.008398 0.001058 0.008195 0.022142 0.027279 0.019446 0.019617 0.011729 0.015634 -0.002046 -0.009545 -0.009654 0.010803 0.025666 0.017917 0.022821 0.008536 0.001323 -0.019129 -0.006353 0.001816 0.003965 0.009643 0.018876 0.004483 0.000000 0.007339 0.013792 -0.041958 -0.013491 0.005382 0.006712 -0.007281 0.001406 0.024647 0.027103 0.038337 0.004945 0.014873 0.002857 0.007959 0.008400 0.007069 0.008140 0.019485 0.030226 -0.033243 -0.008599 -0.007209 0.015204 -0.000775 0.004291 0.018875 -0.005120 0.005193 0.028276 0.026442 -0.000000 -0.000446 0.003580 -0.020047 -0.008281 0.000370 -0.020473 -0.006593 -0.003780 0.023407 0.006228 0.023791 -0.005169 -0.006251 0.008362 -0.013979 0.009727 0.018898 -0.002221 0.009109 0.022267 -0.009774 -0.012021 0.000890 -0.031018 -0.009477 0.002487 0.008604 -0.035920 -0.036357 0.029605 0.046030 -0.001385 -0.019515 -0.028396 -0.004052 -0.008151 -0.017124 0.001007 -0.016286 -0.045638 0.007120 0.008020 0.017611 0.016026 0.012029 -0.004198 -0.021140 0.004025 0.035892 0.011886 0.033923 0.001087 0.004247 0.006376 -0.007682 -0.012655 -0.006756 -0.015644 0.020113 -0.010658 -0.013768 -0.000316 0.000755 -0.001392
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>192</cols>
<dt>d</dt>
<data>
0.004133 -0.002565 0.005506 0.006013 0.001956 0.020539 0.023360 0.008834 0.018513 0.005987 0.036708 -0.013714 -0.009542 -0.015816 0.015416 -0.006318 -0.022601 0.024432 0.018173 0.043110 0.001125 0.002081 0.001343 0.021027 0.003146 -0.003566 0.039894 0.004470 0.010983 0.005432 0.026652 0.005336 -0.019373 -0.008974 -0.007482 0.002422 -0.018906 0.020114 0.011930 -0.011979 -0.002184 -0.022567 -0.019258 -0.007941 -0.008639 0.007598 0.025718 0.026144 0.005175 0.032764 -0.021368 -0.019526 -0.009718 0.001798 0.018476 0.021996 0.023125 0.002239 0.013969 0.006017 0.004693 -0.002995 -0.005565 0.005336 -0.028209 -0.014373 -0.014748 0.025756 0.009465 0.017742 -0.004588 -0.017865 -0.027515 -0.053554 -0.032660 0.009483 0.008782 0.007266 0.017075 -0.005844 -0.006300 -0.012068 -0.029485 -0.028215 -0.009740 0.024380 0.009845 0.014491 -0.006121 -0.025438 -0.030638 -0.034167 -0.031874 0.003545 0.004912 0.005330 -0.003401 0.026671 -0.009923 0.020502 0.021662 0.010080 -0.016038 0.002536 0.000781 0.015757 0.043138 -0.021883 -0.015315 -0.034254 -0.012038 -0.034402 -0.033451 -0.005776 0.047267 0.067636 -0.014745 0.009735 0.011386 -0.006751 -0.044261 -0.021314 -0.001668 -0.021114 -0.031829 0.009736 0.021827 0.005330 0.000285 0.012654 -0.002867 0.001321 0.001671 0.019290 0.007643 -0.013641 0.013384 0.002626 0.007988 -0.007952 0.004650 -0.008602 0.009498 -0.002613 -0.001287 -0.018952 0.018239 0.016939 -0.009549 0.014595 0.011444 0.028683 0.005239 -0.016496 -0.008245 0.025089 0.007787 -0.009260 -0.011786 -0.005955 -0.011980 0.013213 -0.014519 0.013880 0.031407 0.033363 0.013715 -0.026971 -0.007757 -0.033801 -0.011413 0.001485 -0.010170 0.010396 0.009530 0.025599 -0.000449 -0.007676 -0.029742 0.005624 -0.006617 0.008687 0.042468 0.030923 0.030953 -0.026963 -0.018122 0.039732 0.016559 -0.016977 -0.026186 -0.011858
-0.004949 0.018567 0.008271 0.012340 0.003631 -0.020407 -0.017504 0.014372 0.002524 0.018156 0.035342 -0.009512 0.000531 -0.005532 0.013289 -0.022896 -0.025943 0.019865 0.034084 0.049710 -0.005320 0.010524 0.004571 -0.010492 -0.033732 -0.000409 0.022674 -0.003532 0.011594 -0.002486 0.013348 0.008054 -0.020196 -0.027520 -0.010169 0.018725 0.014049 0.000142 0.014349 0.000855 0.002780 -0.004143 -0.010687 -0.001005 -0.010935 -0.016406 0.009167 -0.020327 -0.005853 0.011368 -0.013439 -0.021113 -0.007163 0.003690 0.000771 -0.003799 -0.007363 0.002303 0.004812 0.007305 -0.004343 -0.020427 -0.008842 0.008054 -0.005060 0.011402 0.007555 0.017760 0.004340 0.001389 0.002844 -0.025586 -0.043446 -0.056324 -0.017285 0.019613 -0.002029 -0.046281 -0.005284 -0.012176 0.022672 0.016856 -0.009654 0.007802 0.019126 0.008228 -0.027565 -0.009743 -0.010205 -0.003251 -0.008682 -0.031457 -0.036810 0.015181 0.001684 0.008048 0.007279 0.036983 -0.018122 0.018148 0.026683 0.013430 -0.003972 -0.008673 0.003871 0.012482 0.015276 0.007886 -0.001234 -0.012315 -0.017078 -0.015689 -0.009595 0.010136 0.061087 0.058640 -0.005967 0.014692 0.008134 -0.012699 -0.020746 -0.013698 0.006521 -0.003612 -0.012012 0.024129 0.022369 0.008048 -0.005654 0.012418 -0.017612 0.009615 0.027321 0.023186 -0.007384 -0.011158 -0.002013 -0.001130 -0.010200 -0.003124 -0.012181 -0.003631 0.002197 0.007551 -0.016981 -0.025470 0.006824 -0.004822 -0.013196 0.000343 0.025035 0.008390 -0.001347 -0.034494 -0.024730 0.029595 -0.000570 -0.015856 -0.029315 -0.003237 -0.009913 0.009370 -0.001095 -0.009381 0.014772 0.035741 -0.005326 -0.009632 -0.016282 -0.027342 -0.012520 0.002814 0.010233 0.035348 0.025708 0.022518 -0.011613 -0.019685 -0.025112 -0.002603 0.001858 -0.001072 0.023133 0.030047 0.017968 -0.012472 -0.028739 0.045902 0.013571 -0.005536 -0.038043 -0.009140
0.001407 0.009375 0.000435 -0.005851 0.017747 0.000470 0.008699 0.013731 0.008409 0.021821 0.042854 0.002222 -0.007218 -0.020296 -0.014515 -0.002036 0.008430 0.045256 0.028543 0.037165 -0.009832 -0.011783 0.002258 -0.017588 0.002571 0.020375 0.051027 0.017513 0.011238 0.018633 0.014342 0.008036 -0.042542 -0.030594 -0.016054 -0.000236 0.022740 0.024351 0.012097 -0.004171 -0.012812 -0.008714 -0.017961 -0.015874 -0.018418 -0.022122 -0.022988 -0.004481 0.018536 0.024018 -0.047271 -0.033703 -0.030089 -0.011704 0.002177 -0.011869 0.005620 0.027273 0.018030 0.015567 -0.007469 -0.023643 -0.038771 0.008036 -0.010151 -0.008379 0.009802 0.003081 0.020054 0.016511 -0.007363 -0.019064 -0.040124 -0.060281 -0.030628 0.004195 0.003011 -0.037246 -0.049885 -0.015855 0.025594 0.019549 -0.040098 -0.028010 0.013413 0.002241 -0.015110 -0.032621 -0.014677 0.003042 -0.015788 -0.047618 -0.052564 0.016819 -0.000159 0.008029 -0.012548 0.019526 -0.007815 0.003283 0.011869 -0.011980 -0.022325 -0.010454 0.022537 -0.015126 0.013461 0.013362 0.012918 -0.001504 -0.009966 0.003779 0.009997 0.024290 0.046128 0.045499 0.006852 0.007690 -0.007987 -0.017078 -0.009655 0.001728 0.033598 -0.005155 -0.019172 0.028308 0.016433 0.008029 -0.016767 0.014353 -0.021925 0.003014 0.037792 -0.001118 -0.033020 -0.010626 -0.006114 -0.039831 -0.042377 -0.004737 -0.002457 0.016134 0.037294 0.010362 0.000432 -0.007637 -0.020318 -0.005851 -0.016089 0.000157 0.013594 0.025345 -0.023042 -0.014653 -0.018298 0.040280 0.001705 -0.029529 -0.044148 -0.003255 -0.004802 0.005637 0.005455 -0.000720 0.042218 0.029678 0.026488 0.024213 -0.010972 -0.019217 -0.005813 -0.010084 0.023689 0.020045 0.011112 -0.009212 -0.020135 -0.010190 -0.017899 -0.001718 -0.007632 0.024065 0.022265 0.018604 0.012282 0.005708 -0.014539 0.045000 0.022637 0.005004 -0.026730 -0.009159
0.006370 0.004095 -0.004285 -0.009341 -0.017334 0.005699 0.000114 0.033869 0.054415 0.020402 0.028174 0.017460 0.001493 -0.005691 -0.023387 -0.008159 -0.008707 0.015033 0.037722 0.039893 0.007732 -0.009703 -0.006217 -0.013800 -0.014381 0.037380 0.066113 0.003121 0.022498 0.002345 0.023993 0.003802 -0.040740 -0.018111 -0.021839 -0.021165 -0.014245 0.003658 0.025890 0.006817 0.018056 0.005984 -0.018063 -0.029201 -0.011386 -0.013736 -0.022095 0.015439 0.042993 0.041405 -0.020201 -0.026213 -0.039778 -0.032843 -0.018539 -0.006668 0.022428 0.036746 0.051621 0.010293 0.021446 -0.034549 -0.020920 0.003802 -0.018778 -0.011408 -0.000164 0.012271 0.020030 0.014038 0.021923 -0.018380 -0.044115 -0.077851 -0.031559 -0.004601 -0.006443 -0.030219 -0.020486 0.011163 0.047678 0.030358 -0.057055 -0.041795 -0.003103 0.005095 -0.000630 -0.002266 0.033905 0.021967 -0.005466 -0.033978 -0.045307 0.008559 0.020502 0.003796 0.015746 -0.010410 -0.021081 0.003736 0.034124 0.013572 0.006440 0.023603 0.023650 -0.004139 0.004269 0.031371 -0.003407 -0.011754 -0.026863 -0.022584 0.024630 0.066367 0.077043 0.000313 0.000732 -0.006497 0.003425 -0.006569 -0.002549 0.028583 0.057408 0.008293 -0.005763 0.042128 0.024765 0.003796 -0.008140 -0.009434 -0.012150 0.004494 0.022442 -0.000317 0.018022 0.028659 0.009163 -0.046769 -0.030146 -0.017853 -0.006250 -0.014678 0.004973 -0.010358 -0.005799 0.016952 -0.017359 -0.032602 -0.026311 -0.001535 -0.004112 0.008586 0.011336 0.025631 0.007448 0.017792 0.029766 -0.032784 -0.041732 -0.007489 -0.006734 -0.009853 -0.002759 0.007787 0.048676 0.032054 0.002289 -0.002528 -0.000495 -0.011511 -0.004290 -0.008484 0.012807 0.008621 0.003769 -0.006523 0.006885 -0.028172 -0.009260 -0.015841 -0.000640 0.015727 0.030521 0.025520 0.003624 0.002935 -0.024362 0.027165 0.028996 -0.024078 -0.012503 -0.013392
0.006856 0.001112 -0.001899 -0.009330 0.017747 0.020706 -0.015964 0.018506 0.050413 0.000952 -0.005921 0.011137 0.008267 -0.004394 -0.008388 0.002279 0.012094 -0.019100 0.035182 0.001012 0.008256 -0.000233 0.008305 -0.002253 -0.023307 0.029629 0.041211 -0.009842 0.023856 0.002148 0.023940 0.003802 -0.025011 -0.022541 -0.006780 -0.012521 -0.026546 0.005586 -0.003411 0.051308 0.068660 0.035544 -0.026143 -0.024171 -0.007140 -0.018648 -0.025713 0.020084 0.037208 -0.002234 0.027215 -0.031483 -0.024375 -0.017667 -0.040626 -0.020615 0.007418 0.080945 0.043376 0.009014 0.052059 -0.042788 -0.010020 0.003802 -0.029355 -0.033086 -0.013488 0.005501 -0.003521 0.004490 0.022901 -0.035146 -0.026659 -0.074604 -0.035600 -0.015228 -0.010124 -0.037348 -0.035019 0.026911 0.062023 -0.001278 -0.066667 -0.056280 -0.024527 -0.003414 -0.028361 -0.024011 0.026421 0.032487 -0.030257 -0.029973 -0.037551 -0.035662 -0.004591 0.003795 0.012287 -0.003642 -0.015476 0.003009 0.001400 0.014228 0.018310 -0.018803 0.031421 -0.026943 -0.017454 0.022403 0.002693 -0.013910 -0.041244 -0.007152 0.068269 0.064705 0.048675 -0.005745 0.006190 0.006349 -0.007058 -0.018986 0.013423 0.031095 0.081971 -0.004592 -0.011935 0.036660 0.024226 0.003795 -0.007043 -0.012192 0.003558 0.003364 0.013369 0.022645 0.012974 0.016662 0.018196 -0.034770 -0.025658 0.002459 0.003318 -0.011533 -0.027463 -0.015645 0.001031 0.035600 -0.017031 -0.033454 0.000690 0.003954 -0.003695 0.003383 0.004548 0.010521 0.032257 0.012321 0.027844 -0.015047 -0.025649 -0.007489 -0.024752 -0.015641 0.003566 -0.000383 0.046754 0.038837 -0.002489 0.023454 0.015223 0.002499 0.008010 -0.013907 0.016106 -0.000547 0.008266 0.005124 -0.012738 -0.026305 -0.022822 -0.007205 -0.007864 0.009576 0.021059 0.045494 0.004964 0.023521 -0.016999 0.019769 0.042838 -0.021349 -0.007752 -0.013393
-0.033117 0.025023 0.007664 -0.000400 0.004314 0.016702 -0.006688 -0.023969 0.009715 -0.008293 -0.033323 -0.021427 -0.005958 0.021603 0.005652 0.012881 -0.008620 0.003488 -0.006052 -0.015789 -0.021601 -0.002527 0.026674 0.019477 -0.000882 -0.021455 0.008884 -0.013313 -0.011918 0.010841 -0.001994 0.002233 -0.004091 0.019415 -0.010261 -0.010211 -0.006775 0.006525 0.020319 0.047649 0.050456 0.043740 -0.016532 0.003947 0.004886 0.010245 0.006269 0.027997 0.019579 0.023307 0.037755 -0.000119 -0.002280 -0.005303 0.008448 0.014423 0.029584 0.046014 0.056521 0.034771 0.065570 0.006667 0.004463 0.002233 -0.041068 -0.016321 0.003739 -0.016013 -0.011029 0.005097 0.006352 -0.025368 -0.022694 -0.058911 -0.026126 -0.015643 0.005313 -0.017580 -0.007330 0.036568 0.018761 -0.029908 -0.055028 -0.038548 -0.012736 -0.009148 -0.010599 -0.004179 0.028667 0.010285 -0.041532 -0.026353 -0.009469 -0.048301 -0.015890 0.002226 0.013995 0.008914 0.008856 0.013636 0.012021 0.013383 -0.004008 -0.032543 -0.025421 -0.050913 -0.004539 0.008927 0.026709 -0.012233 -0.002807 -0.002881 0.031404 0.022808 0.039589 0.021802 0.014186 0.025746 0.009154 0.014421 -0.013710 0.009620 0.006704 -0.017638 -0.013027 0.012584 0.030011 0.002226 0.005084 0.000291 -0.003315 0.031119 0.022731 0.024925 -0.000935 -0.014958 -0.015045 -0.047901 -0.008109 -0.005103 0.010369 -0.002571 -0.001009 -0.006555 0.010826 0.041387 -0.001096 -0.004902 -0.002519 0.022844 0.016833 0.017314 -0.002335 0.000402 0.010325 0.023052 0.021689 -0.014529 -0.010776 -0.009058 -0.010912 -0.009323 0.011590 0.004077 0.042182 0.012307 0.002187 0.017338 0.013633 -0.017150 -0.010993 -0.010930 0.007079 -0.008974 -0.000390 0.003247 -0.001666 -0.016245 -0.016444 -0.013311 0.001496 0.002879 0.027626 0.026525 -0.005465 0.023962 -0.006866 0.028571 0.020200 -0.013640 -0.022377 -0.014962
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>192</cols>
<dt>d</dt>
<data>
-0.016071 0.019811 0.004252 0.008883 0.000034 0.010121 0.011788 0.000401 0.040190 0.019387 -0.001963 -0.015967 -0.007732 0.002950 0.009007 -0.022636 -0.002795 -0.012518 0.006393 0.012021 0.002084 -0.000994 0.010725 0.002507 -0.017107 0.003608 0.034721 -0.002467 0.009405 0.006566 0.008720 -0.006270 -0.022846 0.001188 0.017646 0.018437 -0.001433 0.012741 0.018763 -0.001238 0.023331 -0.003438 0.020339 0.001008 -0.017941 -0.006628 -0.013041 -0.014388 -0.019885 -0.024749 0.014397 0.025265 0.012522 -0.000804 0.004063 0.011515 0.012043 -0.010856 -0.003186 0.005722 0.027312 -0.027135 -0.011618 -0.006192 0.026478 0.006801 0.030078 0.000280 -0.007865 0.005815 0.010283 0.000414 -0.019697 -0.036584 0.017799 0.000765 -0.020005 -0.038691 -0.001432 0.013697 0.002200 -0.012941 0.013021 0.011369 0.026401 -0.010102 -0.022426 0.013305 0.024668 -0.001842 -0.033576 0.024309 0.019255 -0.034784 -0.019436 -0.006192 0.019262 0.009217 -0.001113 0.025846 -0.004288 0.006825 0.014290 0.015952 0.012959 -0.000441 0.025427 -0.009884 -0.017473 -0.018127 0.010193 0.011445 0.008847 0.013829 0.026397 0.021111 -0.000468 0.016269 0.012577 0.018664 0.033417 0.027921 0.024391 0.021172 0.005300 0.020920 0.010480 -0.001155 -0.021893 -0.000071 0.013172 -0.001304 0.004262 0.003362 0.011309 -0.021354 -0.023551 -0.016434 0.011057 -0.020011 -0.014540 0.000508 0.025093 0.030185 0.016286 -0.013860 -0.024194 0.010954 0.004135 -0.010144 0.024879 0.026685 0.023536 -0.004492 -0.024811 0.003416 -0.007527 0.011070 -0.015343 0.000000 -0.014718 -0.017596 -0.004693 -0.002024 -0.012640 0.002027 -0.004100 -0.017685 -0.010102 -0.002835 0.012475 -0.015613 0.021164 0.030174 0.013250 0.015133 0.005636 -0.005833 0.005615 -0.002702 -0.019220 0.014189 0.005842 0.016970 0.010143 -0.004675 -0.016297 0.001709 -0.002439 0.004396 -0.007427 0.000000
0.006853 0.014272 -0.009826 0.001780 0.009250 0.017662 0.011112 -0.019276 0.031174 0.025703 0.018777 -0.000084 0.015285 0.002737 0.017268 -0.007134 0.004976 -0.019090 0.022191 0.022567 -0.005336 0.012978 0.009772 0.028339 0.002525 -0.005547 0.017564 0.013818 -0.000253 0.034384 0.009298 -0.006270 -0.007626 0.027271 -0.002056 -0.017461 -0.012780 -0.021751 0.006351 -0.001910 0.016832 0.001355 0.032813 0.013373 0.002743 -0.003688 -0.015359 -0.022516 -0.003248 -0.013649 0.007037 0.027413 0.014851 -0.014072 -0.011476 -0.034456 -0.010195 -0.003899 0.014123 0.007691 0.013789 -0.007973 -0.023551 -0.006192 0.011597 0.043072 0.018223 -0.008625 -0.014676 -0.018070 -0.007077 0.006114 -0.041547 -0.013406 0.020944 -0.002663 -0.006372 -0.015555 -0.020328 -0.008948 0.000254 -0.004999 0.032606 0.030076 0.028397 -0.003336 -0.016843 -0.030818 -0.013158 -0.000397 -0.035900 0.027176 0.018823 -0.040394 -0.034861 -0.006192 0.026481 0.012131 0.034092 0.007478 -0.010213 -0.006106 0.011686 0.010437 -0.021617 -0.046787 0.010645 -0.006759 0.001114 -0.018736 -0.009425 0.020080 0.011008 0.033096 -0.001502 0.014688 0.022967 0.011721 -0.001201 -0.006298 0.025882 0.009352 0.017188 0.019679 -0.004305 0.008766 0.003487 -0.001155 -0.023462 0.019280 0.009007 -0.001352 0.017145 0.006349 0.016317 0.010947 -0.030859 -0.022218 -0.017819 0.002220 0.003674 -0.012120 0.010756 -0.012309 -0.017812 -0.002968 -0.022760 -0.004208 0.016866 0.015079 0.011758 0.009345 -0.000522 0.001762 -0.015821 0.014870 -0.030552 0.013146 -0.018783 0.000000 -0.033834 -0.018954 -0.005076 -0.005446 0.018286 0.021902 -0.005511 -0.014544 -0.041277 -0.027940 0.003709 -0.009511 0.030087 0.004712 -0.024220 -0.008215 0.001350 0.030579 -0.033429 -0.004396 -0.000076 0.012058 0.029684 0.005995 0.001237 -0.011906 -0.018324 0.004041 -0.028638 0.015676 -0.030630 0.000000
0.012321 -0.010220 0.015295 0.017378 0.014551 0.009380 0.002913 -0.020428 0.015998 0.025289 0.015714 -0.029519 0.002506 0.016182 0.015233 -0.009160 -0.036568 -0.016232 0.014572 0.025503 -0.011115 0.010634 0.030824 0.023281 -0.003634 -0.052844 0.012277 -0.012221 -0.012272 0.037892 0.005756 -0.006270 0.003683 0.005808 -0.008284 -0.008138 -0.007330 0.005722 -0.014193 -0.007732 0.002621 0.034390 0.021096 -0.015560 0.009440 -0.013267 -0.000899 -0.017165 -0.023055 -0.004588 0.049820 0.015257 -0.017831 0.000983 -0.000826 0.013868 -0.019685 -0.019976 0.014025 -0.014889 0.011374 -0.004454 -0.009685 -0.006192 0.015177 0.036858 0.019092 -0.006622 -0.002726 -0.017043 -0.034266 0.013315 -0.021664 0.002135 -0.002017 -0.005926 -0.008201 -0.018673 -0.012600 0.002033 -0.023759 0.017525 0.035397 0.022610 0.003319 -0.016636 -0.003628 -0.023339 -0.024589 -0.006816 0.002633 0.006299 0.047257 -0.049465 -0.026417 -0.006192 -0.004805 0.003326 0.018288 -0.004112 -0.008479 0.001794 -0.008213 0.005514 0.004170 -0.040995 -0.001606 -0.008940 0.009993 -0.006168 -0.019689 0.033436 0.024344 0.005593 -0.011607 0.005851 0.011046 0.001763 -0.010178 -0.020049 0.012481 0.008408 0.016981 0.016565 0.010475 -0.029884 0.004471 -0.001155 -0.019333 -0.014069 -0.023074 -0.007043 -0.006117 -0.005969 0.015760 0.014920 0.008024 -0.015202 -0.010921 -0.004866 0.032865 -0.001699 0.006965 0.044774 0.051845 -0.000613 -0.012372 -0.010051 -0.007991 0.025623 -0.003266 -0.011128 0.040675 0.052064 0.012681 0.017597 0.002842 0.011283 -0.000494 0.000000 -0.050475 -0.020775 -0.017652 -0.009973 0.020142 -0.008459 -0.006815 -0.006675 -0.023000 -0.028994 -0.013402 0.021803 0.043884 0.014391 -0.005516 0.009853 0.020574 0.005479 -0.052616 -0.019400 0.010680 0.020877 0.023622 -0.007824 0.006652 0.012099 -0.018409 -0.010473 -0.015292 0.007257 -0.007706 0.000000
0.026688 -0.005696 -0.012270 -0.004610 0.010500 0.021774 0.013500 -0.011347 0.013307 0.004669 0.017873 -0.021710 -0.007000 0.001272 -0.002789 -0.009381 0.006120 -0.008321 0.006953 0.003861 -0.023795 -0.000271 0.023915 0.033982 0.001027 -0.000070 -0.005047 -0.028417 -0.022645 0.035141 0.031280 -0.006270 0.017623 0.028082 0.012434 0.015757 0.005607 0.016552 -0.011118 -0.001460 -0.021429 0.008555 0.007346 -0.035139 -0.019485 -0.026364 0.003592 0.015370 -0.003871 0.018103 0.045164 0.012322 -0.015176 0.003954 0.007006 0.035013 0.007800 0.007054 0.007520 -0.015026 0.008309 0.004245 0.016688 -0.006192 -0.030227 0.015220 0.015512 0.000678 -0.020222 -0.011086 -0.006456 -0.001611 -0.005687 -0.011872 -0.026648 -0.000960 -0.000137 -0.014627 0.037400 0.035280 0.001020 0.013337 0.017624 -0.013250 0.001791 -0.007295 -0.008212 0.031800 0.028917 0.005906 0.020150 0.006731 0.041378 -0.035626 -0.017709 -0.006192 -0.036226 -0.027677 -0.026785 -0.012239 -0.022146 0.015320 0.024045 0.026652 -0.001323 -0.043827 -0.017149 -0.006773 0.020714 0.012662 0.014605 0.022997 -0.001770 -0.000330 -0.042636 -0.037497 -0.030324 0.017577 0.027887 0.041570 0.030138 0.012825 0.005600 0.016471 0.017419 -0.040923 -0.020896 -0.001155 -0.026060 -0.009918 -0.010498 -0.013322 0.001751 0.007300 0.035766 0.011269 0.001278 -0.010588 -0.005952 -0.009131 0.018847 0.019845 0.026618 0.002237 0.000228 -0.033521 -0.007416 -0.014802 -0.012170 0.019225 0.032607 0.045839 0.025218 0.018029 -0.028100 -0.012359 0.010852 -0.000608 0.005015 0.000000 -0.043363 -0.004598 0.018502 0.046173 0.001827 0.005247 -0.001391 -0.013754 -0.018699 -0.010888 0.026113 0.034655 0.005142 0.008279 -0.021684 -0.004617 -0.013136 -0.034194 -0.027315 0.021358 0.043178 0.047366 0.029488 0.007109 -0.003508 -0.013785 -0.042635 -0.013876 -0.003442 -0.010278 0.017985 0.000000
0.018151 0.002051 -0.006662 -0.004369 0.021446 0.026825 0.013834 0.003099 0.014014 -0.016013 -0.027401 -0.018080 0.001231 0.009780 0.011044 0.030430 0.044730 0.010176 0.004017 -0.014546 -0.033531 -0.006325 0.025309 0.035121 0.039555 0.030050 0.033817 -0.027430 -0.016028 0.055329 0.051431 -0.000275 0.010419 0.027908 0.012071 0.001609 0.023741 0.020322 0.027335 0.000847 0.012500 0.001784 0.015666 -0.003413 -0.006886 -0.006645 0.019937 -0.006469 0.012852 0.009510 0.050185 0.027716 0.006041 -0.011095 0.009390 0.022956 0.023285 0.014929 0.021597 0.014881 0.014667 0.018487 0.033558 -0.000197 -0.041038 -0.001575 -0.032491 -0.032797 -0.019391 0.008295 0.010283 -0.012828 -0.000171 0.011173 0.021950 -0.003239 -0.020112 -0.022362 0.015968 -0.019219 -0.022512 -0.013172 0.047770 0.022517 -0.036569 -0.047808 -0.020176 0.021694 -0.011988 -0.032229 0.012818 0.007076 -0.002780 -0.040310 -0.045651 -0.000197 -0.055540 -0.029903 -0.032750 -0.031692 -0.016380 0.017161 0.040529 0.009529 0.007693 -0.011294 0.013868 -0.017159 -0.001490 -0.001107 -0.012951 -0.029507 -0.043230 -0.041360 -0.021724 0.003741 -0.036201 -0.022677 -0.006279 0.002543 0.001137 -0.042547 -0.027394 -0.005431 -0.006783 -0.040916 -0.057925 0.004840 -0.034826 -0.007722 0.010736 0.028407 0.012706 0.038053 0.034545 0.013186 0.009840 -0.003168 0.007832 -0.013001 -0.019287 -0.004634 -0.006571 -0.001954 -0.006716 -0.031044 -0.012593 0.005564 -0.004129 0.012298 0.010512 0.025668 0.024481 0.009005 -0.026658 -0.010579 -0.003923 0.012032 0.014907 0.005995 0.013878 0.028979 0.016907 0.042567 0.025861 0.031998 0.005041 0.000623 0.008727 -0.007929 0.007907 -0.012386 -0.019007 -0.013271 -0.017448 -0.015176 -0.010913 0.006069 0.006900 0.036907 0.014135 0.020110 0.019488 0.021565 -0.009199 0.000952 0.008263 0.005268 0.015572 0.006277 0.016454 0.005995
0.007540 -0.013258 0.004663 0.023916 0.045957 0.014574 -0.023268 -0.034503 -0.037814 -0.060006 -0.031091 0.008058 0.006771 0.033370 0.034944 0.014642 -0.003820 0.009103 -0.034114 -0.038653 0.007613 0.028233 0.046902 0.039689 -0.003921 -0.037090 -0.027049 -0.027336 -0.043843 0.038747 0.032328 -0.002314 0.010573 0.015975 0.035927 -0.004824 0.008653 -0.005537 -0.007486 -0.019929 0.006343 -0.022521 0.006685 0.016257 0.010827 0.013229 0.029572 0.011428 -0.021185 -0.002851 0.031518 0.026513 0.029623 0.005588 0.008597 0.015210 -0.003406 -0.035045 0.012467 0.016581 0.002017 0.015146 0.004504 -0.002236 -0.038679 -0.022331 -0.030098 -0.034595 -0.037501 -0.005131 0.012322 -0.002190 0.048677 0.026835 0.040387 -0.003697 0.008237 -0.032744 -0.026729 -0.035479 -0.025793 -0.013200 0.047008 0.004114 -0.035469 -0.029542 -0.049282 -0.031992 -0.035597 -0.030354 0.042368 0.013311 -0.006953 -0.038145 -0.049157 -0.002236 -0.070161 -0.035801 -0.017998 -0.023378 -0.028620 -0.005945 0.016832 0.005847 0.008044 -0.033896 0.018637 0.007753 -0.005328 -0.031095 -0.037653 -0.046564 -0.035822 -0.022822 -0.039887 -0.001195 -0.012177 -0.032426 -0.051373 -0.042976 -0.031367 -0.036091 -0.025036 -0.034064 -0.020997 -0.042213 -0.062045 0.002801 -0.003935 0.032725 -0.001266 0.016577 0.011605 0.032577 0.032117 0.011831 0.027062 -0.003268 0.036973 -0.007810 -0.018494 -0.038172 -0.034453 -0.031016 -0.009359 0.010651 0.005168 0.052894 -0.004539 -0.007632 -0.028098 -0.010838 -0.004778 0.008234 0.032130 -0.018861 0.003232 0.011212 0.034750 0.003956 0.036270 0.068995 -0.004314 0.004213 -0.004827 0.011296 0.013462 0.002399 0.022803 0.015551 0.003493 -0.015656 -0.026586 -0.023125 -0.009565 -0.012766 -0.016508 0.037902 0.027985 0.057767 -0.012652 -0.018710 -0.030620 -0.023868 -0.000885 -0.002808 0.042949 0.018962 0.015927 -0.001911 0.015595 0.003956
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>192</cols>
<dt>d</dt>
<data>
-0.003016 0.003379 -0.005443 -0.026041 -0.017671 0.018740 0.021270 0.016592 0.000009 0.002341 -0.049243 -0.027341 0.001100 0.012767 0.005414 0.004447 -0.007026 -0.001668 0.009821 -0.023277 -0.012555 -0.008513 0.004609 0.027024 0.021808 0.008034 -0.012158 -0.027938 -0.014757 0.004482 0.013987 -0.001176 0.005827 0.059540 0.059139 0.022956 -0.002675 -0.013568 0.010418 0.006595 -0.015040 -0.014824 -0.007062 0.013571 0.039450 0.036740 0.001173 -0.024901 -0.015309 -0.006301 0.038383 0.071478 0.105286 0.068857 0.036501 -0.002190 -0.017263 -0.008175 -0.018852 0.028350 0.010120 0.006982 0.027959 -0.001176 -0.042917 -0.008696 0.004262 0.044345 0.003681 -0.028393 -0.008421 0.017377 0.022374 0.012754 0.040836 0.030234 0.036813 0.008975 0.006720 -0.006419 -0.019128 -0.042673 0.002410 0.028797 0.039351 0.074531 0.017123 0.000820 -0.006739 0.005113 -0.015550 0.060659 -0.022202 0.007029 -0.011674 -0.001161 -0.040201 -0.025764 -0.017142 -0.033930 -0.019671 -0.028669 0.004723 0.015163 0.007502 -0.012297 0.005895 -0.002348 0.013522 0.015415 -0.000439 0.042039 -0.007005 -0.005914 -0.031441 -0.015902 -0.010039 0.005104 0.002754 -0.001928 0.036794 0.026544 -0.002046 0.036970 -0.037726 0.014709 -0.055966 -0.000636 -0.038859 -0.041079 0.007458 -0.000143 -0.003488 -0.033380 -0.011187 0.011645 -0.017319 -0.027176 0.027492 0.009893 0.009403 0.011418 0.006838 -0.005650 -0.003357 -0.011253 -0.046410 -0.011391 0.009383 0.024006 0.007694 -0.000179 -0.004486 0.006424 -0.037067 0.003579 -0.033632 0.020301 -0.041510 -0.000000 -0.007082 0.006977 0.015545 0.034144 0.014523 -0.009128 -0.042167 -0.007588 -0.006572 -0.032399 0.026168 0.013832 0.006254 -0.009630 -0.008541 0.006338 0.026201 0.004368 -0.017670 0.017770 0.035114 0.028021 0.001188 -0.004971 0.005226 0.015944 -0.015435 0.020120 -0.013098 0.025936 -0.018230 -0.000000
0.032858 0.045288 0.024028 -0.017766 -0.016952 0.029459 0.005789 0.014322 0.018740 0.003361 0.011556 -0.001320 -0.011034 0.013795 0.005634 -0.021592 -0.030273 -0.027180 0.039428 0.065033 0.049362 -0.009194 -0.005220 0.026526 -0.011996 -0.018325 -0.014419 -0.000790 -0.007171 0.009553 0.035514 -0.001176 0.007152 0.064823 0.055455 -0.009868 -0.043991 -0.030569 -0.020769 0.003471 -0.022364 -0.014422 0.049675 -0.001187 0.035248 0.006986 -0.027293 -0.012356 -0.037462 0.002051 0.037660 0.083755 0.065648 0.032741 -0.023485 -0.049127 -0.023165 -0.030471 -0.021842 0.046803 -0.009207 -0.017148 -0.018290 -0.001176 -0.047110 -0.048225 -0.043909 -0.061399 -0.046590 -0.030273 -0.027648 -0.000371 -0.033241 -0.029153 0.012186 -0.010331 0.007905 0.010649 -0.002159 0.022021 -0.009916 0.003998 -0.039617 -0.031910 -0.047129 -0.045175 -0.030336 -0.025054 -0.009077 -0.019711 -0.031633 0.007776 -0.049252 -0.037521 -0.078246 -0.001161 -0.028215 -0.038901 -0.039351 -0.033794 -0.014904 -0.029200 0.002008 0.013789 -0.015817 -0.005965 -0.005812 0.009592 -0.006533 -0.014515 0.050078 0.034054 0.026314 0.012267 -0.015406 -0.046238 -0.022281 -0.035540 -0.018562 0.015991 0.019142 0.032805 -0.008528 -0.003503 -0.025331 0.026430 -0.037619 -0.000636 0.003515 -0.007074 -0.006806 -0.038753 -0.035488 -0.007838 -0.002781 0.014308 -0.024169 -0.035407 0.011177 0.009729 0.025890 0.010085 0.018582 0.024269 0.004549 0.008661 -0.023707 0.005806 0.024066 -0.014027 -0.019747 0.011916 0.020549 0.017164 -0.027034 0.006252 -0.025124 0.014283 -0.008398 -0.000000 -0.016939 -0.010632 0.011957 -0.007318 -0.010285 -0.012531 -0.038409 0.001582 0.008240 -0.028325 0.029898 -0.014474 -0.004890 0.008777 -0.009086 -0.000181 -0.005177 0.002899 -0.017280 -0.011753 0.012419 -0.008396 -0.008508 -0.015612 -0.025235 -0.000139 -0.006808 0.013838 -0.027591 0.002099 -0.033079 -0.000000
0.021379 0.066238 0.013583 -0.025431 -0.010387 0.008782 0.002073 0.004785 -0.006490 -0.012568 0.010615 0.019739 -0.007018 -0.011581 -0.009337 -0.012570 0.005815 -0.003794 0.052760 0.077709 0.042404 -0.015426 -0.015089 0.002290 -0.005327 0.005528 -0.006265 0.011743 -0.002036 0.007101 0.008569 -0.001176 -0.014898 0.032232 -0.023884 -0.041760 -0.047148 -0.030476 -0.027193 -0.004825 -0.002220 -0.016695 0.026342 0.001553 0.004188 -0.020498 -0.037608 0.000982 -0.005220 -0.008983 0.019253 0.032649 0.002145 -0.031681 -0.061441 -0.068217 -0.022347 -0.017862 -0.018643 0.021038 -0.005924 -0.055784 -0.061205 -0.001176 -0.015526 -0.026640 -0.008647 -0.040978 -0.048304 -0.026470 -0.019613 0.006168 -0.008934 -0.028280 0.001997 -0.014036 0.011361 0.003889 -0.010361 0.029389 0.043066 0.053113 -0.017952 -0.027450 -0.028197 -0.020386 -0.031375 -0.036196 0.011425 0.022199 0.026894 0.002945 0.002551 -0.012475 -0.039597 -0.001161 0.008418 -0.008071 0.002417 -0.007346 -0.005558 0.000461 -0.011177 0.013348 0.002766 -0.018777 -0.001823 -0.024987 0.008732 0.022729 0.020981 0.034832 0.033395 0.025830 0.000437 -0.018781 -0.014344 -0.000776 0.011083 0.020928 0.016126 0.018136 0.012578 -0.004443 -0.002792 0.027632 0.024940 -0.000636 -0.010635 -0.003977 -0.017885 0.018173 0.036462 0.018621 -0.021599 -0.012627 -0.007861 -0.020812 0.012407 -0.000099 0.015629 0.034433 0.013507 0.018762 0.019871 0.000887 -0.021386 0.011614 0.012316 0.015904 0.043410 0.018886 0.001501 0.004477 -0.021475 0.025206 -0.003148 0.013830 0.008073 -0.000000 -0.010352 0.001608 0.002723 0.008790 0.032737 0.013905 -0.029245 -0.015241 0.023735 0.013290 0.038911 0.001784 -0.012855 0.012797 -0.009530 0.002527 -0.019882 -0.011075 -0.001186 0.017612 0.001567 -0.010923 0.037163 0.004088 -0.020537 -0.022778 -0.003828 0.042012 -0.011250 0.007168 -0.016893 -0.000000
-0.005870 0.050434 0.021238 -0.022847 0.004867 0.005255 -0.011143 -0.012207 -0.014206 0.000939 0.028410 0.004433 0.002818 -0.014116 -0.003703 0.000971 -0.009159 0.003816 0.048348 0.071989 0.035025 -0.007356 -0.003980 -0.000812 -0.002910 -0.002932 0.006428 0.022560 -0.000452 -0.001164 -0.006835 -0.001176 -0.030593 -0.019007 -0.039582 -0.018296 -0.008645 0.007875 -0.009044 -0.001552 0.016515 0.006164 0.019785 -0.001429 -0.005330 -0.023531 -0.017398 -0.006188 0.009454 -0.028634 0.003914 0.005367 -0.022930 -0.016716 -0.029175 -0.022451 -0.017903 -0.002961 -0.011479 0.007715 0.017964 -0.039956 -0.056167 -0.001176 0.035934 0.002859 -0.014782 -0.021627 -0.023024 -0.008048 -0.019089 -0.020123 -0.017844 -0.020360 0.027471 0.001234 -0.013234 0.001801 -0.003172 0.017693 0.038902 0.047340 0.013189 0.004445 -0.006482 -0.031234 -0.016673 -0.015258 0.008702 -0.001099 0.030895 -0.007780 0.020708 -0.008710 0.001407 -0.001161 0.018520 0.036418 0.029021 -0.007850 -0.039712 -0.013009 -0.020687 -0.016626 -0.005400 -0.033802 -0.010397 -0.029446 -0.009710 0.006182 0.004210 0.023556 0.008384 0.027681 -0.005942 0.008516 0.008471 -0.013667 -0.030873 -0.021181 0.007867 -0.008215 -0.016136 0.002706 -0.016750 -0.012530 0.011174 -0.000636 0.002643 0.012294 0.005901 -0.015034 -0.000062 -0.013256 -0.017922 -0.027355 -0.020927 -0.011908 0.031255 0.008215 -0.011380 0.004831 0.007816 0.037765 -0.002606 0.021357 0.015496 0.007211 0.034117 -0.011343 0.000438 -0.023754 0.003670 -0.009548 -0.010658 0.019466 -0.001844 0.002847 -0.014988 -0.000000 0.003074 -0.004118 -0.022400 -0.024240 0.002594 0.002800 0.000167 -0.004701 -0.011728 -0.009685 0.021282 -0.010900 -0.016808 0.011215 0.001290 0.004890 0.007269 0.026726 0.009101 0.010446 -0.015400 -0.032981 0.005610 -0.020204 -0.011875 0.006590 0.010401 0.013817 0.008163 -0.006423 -0.026530 -0.000000
-0.010329 0.039702 -0.035670 -0.012398 0.013331 0.007688 -0.001139 -0.006204 -0.012654 0.005468 0.008666 -0.013242 -0.019752 -0.024580 0.008032 0.020577 0.030418 -0.005622 0.030737 0.047154 -0.031645 -0.012894 -0.005317 0.013395 0.018224 0.014201 0.010730 0.018106 -0.001708 -0.000509 -0.019523 -0.001176 -0.019503 -0.015323 -0.017531 -0.000868 -0.015257 0.009633 0.027246 -0.016085 0.009718 -0.021110 0.003333 0.024500 0.002011 0.005610 -0.021645 -0.011241 0.011625 0.000494 -0.019672 -0.006304 0.009677 -0.010059 -0.011076 -0.009417 0.006458 -0.010294 -0.005702 -0.002358 0.015820 -0.008891 -0.025498 -0.001176 0.049144 0.024396 -0.004680 -0.000300 -0.015152 -0.001176 0.018268 -0.018400 -0.010357 -0.011134 -0.003154 0.003352 -0.014365 0.025573 -0.027869 -0.025112 0.005154 0.056615 0.040878 0.014975 0.009969 -0.024054 0.003089 -0.027470 -0.003245 -0.006716 0.044025 0.009328 0.015688 -0.010131 0.009064 -0.001161 0.003779 0.042687 0.009198 -0.004392 -0.009079 -0.004202 0.006933 0.014283 0.014849 -0.003893 -0.009548 -0.018234 -0.021563 0.014215 -0.012570 0.015002 -0.001289 0.036053 0.013064 0.018316 -0.006478 -0.010688 -0.000171 -0.022251 0.024468 -0.006593 0.020499 0.034453 0.015746 -0.009713 -0.006437 -0.000636 -0.000595 0.004934 -0.013968 -0.005874 -0.002779 -0.019216 -0.015643 -0.002388 0.003971 -0.013842 0.010791 0.000322 0.001501 0.016850 0.020846 0.031794 0.015276 0.023106 0.000121 0.007231 -0.017033 -0.000459 -0.004875 0.000842 0.005201 0.008102 0.019426 0.026954 0.008918 0.002129 -0.012033 -0.000000 -0.010673 -0.007571 -0.012940 0.004713 0.013945 0.026978 0.021820 -0.005988 -0.006190 -0.040369 0.007536 -0.006393 0.013751 0.030311 0.023199 0.009440 0.014559 0.017339 -0.018962 -0.012190 -0.009439 0.014813 0.019987 0.015512 0.018767 -0.001119 -0.012724 0.008706 0.017073 0.023921 -0.005640 -0.000000
-0.015428 -0.037517 -0.014551 -0.033986 -0.003301 -0.011660 0.005634 0.012123 0.009852 -0.002305 0.021972 0.001002 0.027315 0.034421 0.046255 0.024740 0.005188 0.002568 0.017023 0.016202 -0.009062 -0.000840 0.023358 0.021157 0.030302 0.016664 0.012822 0.017007 0.007829 0.013665 -0.004408 -0.001176 -0.010152 -0.010968 0.006874 -0.016915 0.000188 0.007497 0.016363 -0.007049 -0.013155 -0.017389 0.009187 0.013723 0.027175 0.037069 0.005921 0.002642 -0.009083 -0.009086 -0.015566 -0.004105 0.026989 0.003990 0.026511 0.019389 0.015274 -0.016238 -0.024936 -0.004363 0.010005 0.006104 0.003735 -0.001176 0.038153 0.054654 0.038576 -0.020429 -0.008651 -0.001393 -0.009569 0.004125 0.005572 -0.002497 -0.005170 0.003044 -0.004441 0.009923 -0.001035 -0.017703 0.000734 -0.022445 0.037325 0.039303 0.039386 -0.021481 0.004558 0.001824 -0.025271 0.006254 0.000374 0.017432 0.022668 -0.008896 -0.002238 -0.001161 -0.018071 0.031695 0.017335 0.022173 0.019052 -0.012638 -0.023249 0.001222 -0.003301 0.009790 -0.025169 -0.000635 -0.012547 -0.025219 -0.006959 0.016422 0.027598 -0.002639 0.011526 0.013903 0.000547 0.008220 -0.015890 -0.028525 -0.008429 0.026378 0.015690 0.033922 0.020914 -0.026841 -0.020989 -0.000636 -0.045404 -0.003147 0.011731 0.028184 0.013832 -0.000161 -0.002889 -0.011116 -0.006502 -0.017401 -0.000858 -0.001620 -0.015796 -0.013136 -0.000806 0.022545 0.020744 -0.006141 -0.034938 0.002866 0.002900 0.007700 0.007126 0.002279 0.009870 0.001183 -0.010168 0.012533 0.002217 -0.007144 -0.020776 -0.000000 -0.004238 0.021725 -0.010535 0.017866 0.016140 0.007256 -0.013378 -0.015491 -0.014081 -0.007967 0.018551 0.014793 -0.009340 -0.023216 -0.022408 -0.004845 0.018218 0.021324 0.018310 0.013883 0.007771 0.009886 -0.020202 -0.005189 -0.017674 -0.007330 0.002112 -0.003826 0.000187 0.013113 -0.004582 -0.000000
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>192</cols>
<dt>d</dt>
<data>
-0.010258 0.006290 0.006416 0.008348 -0.013230 -0.014803 -0.019403 -0.011726 0.002204 -0.020005 0.016211 -0.009860 -0.002057 0.006054 -0.005807 0.010811 0.009392 -0.013930 -0.011252 -0.000494 -0.000941 0.003068 -0.010355 -0.043854 -0.006855 -0.005395 -0.009466 -0.005520 -0.008714 -0.004201 -0.007658 0.000000 0.012685 0.002988 -0.032154 -0.000506 0.017911 -0.005595 -0.008030 -0.005218 -0.006097 -0.030531 0.022805 0.015767 0.000255 0.013415 -0.003541 -0.033407 -0.008406 0.004717 0.008432 0.008964 -0.022839 -0.007169 -0.002290 -0.011230 -0.039264 -0.014305 0.006724 -0.007042 -0.010116 -0.003154 0.000070 -0.000003 -0.025730 -0.003813 -0.012478 -0.004984 0.018593 0.009254 0.016380 -0.006588 -0.011365 -0.045289 0.002202 0.006567 -0.005597 -0.012538 -0.005930 0.015824 0.018920 0.009790 -0.034794 0.000344 0.000292 -0.011517 -0.012971 -0.002542 0.019723 0.015255 -0.000775 0.001009 -0.008135 -0.000268 -0.009945 -0.000007 -0.022384 0.002922 0.013343 0.021262 -0.000799 -0.003681 -0.007931 0.023154 0.054733 0.011283 0.000196 0.011478 -0.002697 -0.017324 -0.013819 -0.009453 -0.000467 -0.001824 0.003433 0.008121 0.025069 0.014912 -0.024341 -0.014225 -0.013649 0.031279 0.040594 0.006293 -0.002887 0.017451 0.006481 -0.000007 -0.013573 0.006968 -0.013811 0.014249 -0.007451 -0.021809 -0.019465 0.014757 0.058052 -0.005525 -0.006084 -0.004448 -0.015220 -0.012751 -0.000777 0.012330 0.032908 0.000399 0.019834 0.005471 -0.005888 0.011933 -0.000446 -0.015146 -0.008820 0.029373 0.053228 -0.017273 -0.027958 0.033612 0.020458 -0.000007 -0.021969 0.005500 -0.004936 -0.014373 -0.020601 -0.006485 -0.008913 -0.014452 -0.008701 -0.013129 -0.005133 0.000592 -0.008737 0.035017 0.027659 -0.010178 -0.005439 -0.003063 0.003311 -0.004657 0.007875 -0.015413 0.020842 0.008370 -0.015161 -0.017995 -0.011842 -0.000237 -0.027467 0.000860 -0.009615 -0.000016
0.004032 -0.002087 0.013914 0.010517 -0.011819 -0.014059 0.003207 -0.002332 -0.003055 -0.016928 0.001743 -0.023557 0.027606 0.019576 0.028662 0.035465 0.016409 -0.000060 0.004934 -0.007077 -0.000639 0.019074 0.011722 0.029964 0.029816 0.004585 -0.001476 0.015396 0.009137 0.010065 0.006524 0.000000 -0.012229 -0.001966 -0.001364 0.024723 0.034518 0.001178 0.021417 0.004880 -0.009338 0.004127 0.010945 -0.010852 -0.014115 0.004887 0.012739 -0.016785 0.000479 -0.010094 0.021404 0.011173 -0.020053 -0.003661 0.024842 0.010485 -0.002409 0.002465 -0.020220 0.005394 0.000450 0.012336 0.002160 -0.000003 -0.029628 0.010500 0.027520 0.032178 0.042078 0.033343 -0.007202 -0.006494 -0.014433 -0.013477 -0.012382 0.006209 0.015634 -0.004270 -0.012355 -0.012632 0.007708 -0.014249 -0.025495 0.017908 0.018479 0.031280 0.021367 0.013866 -0.021238 -0.013343 -0.021725 0.001928 0.005291 0.011301 0.004129 -0.000007 -0.037224 0.010444 0.004693 0.026277 -0.002606 -0.002142 -0.012299 -0.010654 0.014663 0.000754 0.000746 0.033983 0.006177 -0.005785 -0.046699 -0.011359 -0.012846 0.010590 -0.017930 0.013045 0.041435 0.018338 0.000092 -0.032428 -0.025176 -0.013699 0.019030 -0.017417 -0.003170 -0.003054 0.007950 -0.000007 -0.020539 0.003880 -0.027075 -0.015877 -0.019667 -0.018524 -0.019173 0.022241 0.066405 -0.006359 -0.032892 -0.019307 -0.023716 -0.019321 -0.017785 -0.007012 0.009139 0.018777 0.021916 -0.020887 -0.034673 -0.030982 -0.022981 -0.021833 -0.016034 0.036370 0.070701 -0.043537 -0.030388 -0.002606 0.016754 -0.000007 -0.009529 0.001387 -0.016372 -0.023483 0.000078 0.011047 -0.003525 0.000463 0.016938 0.011073 -0.008020 -0.000656 -0.009992 -0.008212 -0.008813 -0.004307 0.004327 -0.012761 0.039689 -0.004644 -0.012636 -0.030011 0.004092 0.016018 -0.010363 -0.001998 0.001961 0.003642 -0.008476 -0.018512 -0.005106 -0.000016
-0.012876 -0.002299 0.009487 0.026525 -0.013599 0.008405 -0.019287 -0.010244 -0.001176 -0.005616 -0.006172 -0.012284 -0.011821 -0.010252 -0.002397 0.029968 0.006105 -0.011774 0.001560 -0.008494 -0.011008 0.006213 -0.017852 0.011510 0.016722 0.004224 0.001976 -0.022484 0.014702 -0.017284 0.006536 0.000000 -0.002458 -0.000230 0.011585 0.004533 0.003757 0.008084 -0.012968 0.001187 -0.022550 -0.031379 0.001834 0.003034 0.007836 0.009881 0.004744 0.011194 0.003899 -0.001334 0.004881 0.003142 0.024852 0.019313 -0.002893 0.014864 -0.005196 0.009629 -0.023780 -0.007703 0.007519 -0.011118 0.011609 -0.000003 -0.023597 -0.011138 0.012057 -0.013439 0.024393 0.021194 -0.000433 0.009590 -0.023679 -0.013726 -0.005560 0.001402 0.029931 -0.015160 -0.020987 -0.005358 0.005720 0.003341 -0.016125 -0.005331 0.019274 0.020035 0.003812 -0.009909 -0.007236 0.012900 -0.009767 -0.011752 0.004011 -0.010348 0.006093 -0.000007 -0.030939 -0.018851 -0.009050 -0.003017 0.002383 0.009238 0.015973 0.012197 -0.014770 -0.034980 -0.018697 0.009549 0.014903 -0.008672 -0.027492 -0.007342 -0.000561 0.006822 -0.044531 -0.026880 -0.001281 -0.006752 0.007290 -0.017797 0.002101 0.001834 -0.009702 -0.030333 -0.005830 -0.015615 0.003079 -0.000007 0.014897 0.006753 0.005169 0.020512 0.013380 -0.001433 -0.007564 0.002976 0.049500 -0.004744 -0.007298 0.012776 -0.017115 -0.016653 -0.021768 -0.018958 -0.020635 0.017913 0.043907 -0.004404 0.008826 0.013217 0.012295 -0.008704 -0.021652 -0.021660 0.037499 -0.020020 -0.010026 0.005757 0.037350 -0.000007 0.013095 0.014822 -0.023086 0.001846 0.031493 0.038394 -0.004258 -0.014128 0.038791 0.040854 0.002152 0.011388 -0.021249 -0.021547 -0.025211 -0.016262 -0.009549 -0.006406 0.044553 0.031828 -0.016217 -0.020537 0.009631 0.020563 -0.013404 -0.009907 0.025047 0.017134 0.017851 -0.012888 0.002012 -0.000016
-0.005414 -0.003744 -0.016800 0.009662 0.000453 0.011723 0.011149 0.010492 0.012128 -0.022829 0.001147 -0.006485 -0.002086 0.007346 0.026649 0.032963 0.014769 -0.019086 -0.010267 0.005549 -0.023148 0.021184 0.046311 0.041467 0.031167 0.009263 -0.004863 0.024639 -0.010363 0.015268 -0.000301 0.000000 -0.034584 -0.028890 -0.020842 0.009925 0.011353 -0.005213 0.011552 -0.006495 -0.006359 -0.032561 0.002586 -0.006422 0.009094 0.016352 0.009034 0.004703 0.005913 -0.012244 -0.040546 -0.006291 -0.013251 0.024131 0.033520 0.010805 0.031000 -0.006324 -0.010989 0.005467 -0.021746 0.005743 -0.023923 -0.000003 -0.042204 -0.041526 -0.024638 0.033728 0.026485 0.017860 0.015812 -0.009527 -0.015304 -0.021040 -0.003282 -0.006351 0.024571 0.009305 -0.003545 -0.001524 0.026122 -0.005799 -0.041244 -0.031222 -0.014147 0.036667 0.055553 0.031783 0.030172 0.019204 -0.010385 -0.002587 -0.010739 0.014439 -0.010946 -0.000007 -0.024639 -0.026850 -0.023016 0.031984 0.012756 0.001831 0.009809 -0.019751 -0.010142 -0.013474 -0.014683 -0.019180 0.003280 -0.014039 0.000977 -0.008284 -0.016965 -0.005015 -0.042051 -0.027868 -0.045933 0.021116 0.031117 0.032395 0.002164 -0.035161 -0.014960 -0.040853 -0.026513 0.005087 -0.001549 -0.000007 -0.004683 0.017669 0.010590 0.014167 0.014126 -0.020139 -0.015409 0.002767 0.033602 -0.004677 -0.012840 0.000374 0.010704 -0.012409 0.003061 -0.008376 -0.014406 0.007150 0.044456 0.024400 0.023833 0.020058 0.030232 0.005181 -0.019009 -0.004978 0.026967 -0.017970 -0.004970 0.002493 0.030473 -0.000007 0.031451 0.020385 -0.008035 -0.017904 -0.001345 0.020401 0.009491 0.001324 0.025866 0.038692 0.013162 0.041538 0.003363 -0.034061 -0.014058 -0.001988 -0.007934 0.008985 0.075795 0.042920 0.033983 -0.016357 -0.013791 0.011201 0.000876 -0.005047 0.058481 0.027392 0.035923 -0.009936 0.007588 -0.000016
-0.015216 -0.004970 -0.030791 -0.019428 -0.026994 -0.003458 0.023951 0.025593 -0.006090 0.001881 -0.011899 0.008926 0.034037 0.041382 0.026170 -0.002874 -0.019873 -0.024856 -0.006243 -0.005894 -0.008573 0.019123 0.039013 0.031399 0.014365 0.004743 -0.021080 0.000990 0.007856 -0.009271 -0.001701 0.000000 -0.007631 0.006684 -0.014230 0.017309 -0.031545 -0.010719 0.007254 -0.016237 -0.035896 -0.028442 -0.010921 -0.014961 0.011287 0.019707 0.006624 -0.003156 -0.004207 0.008976 -0.014033 0.007123 -0.015451 0.022032 0.018003 0.007098 -0.000186 -0.010407 -0.016847 -0.008890 -0.012221 -0.010578 -0.015500 -0.000003 -0.028947 -0.000852 0.016190 0.041043 0.000852 -0.023956 -0.027326 -0.030112 -0.000892 0.006852 0.000682 0.009027 -0.000476 0.000744 -0.014765 -0.004377 0.000559 0.021263 -0.006169 0.005737 0.022464 0.040153 0.024676 -0.010293 -0.025079 -0.019170 0.007637 -0.011853 -0.014310 0.006626 0.003279 -0.000007 -0.021082 -0.005166 0.009093 0.047888 0.020526 0.001598 -0.013561 -0.017596 -0.004830 -0.021422 -0.021401 -0.017184 -0.021414 0.021773 0.000405 -0.001246 0.002657 -0.010302 -0.018852 -0.022496 -0.008471 0.031592 0.035799 0.003350 -0.007987 -0.015847 -0.009596 -0.027156 -0.033519 0.020943 0.015566 -0.000007 0.006291 0.018891 0.010646 0.010633 -0.003182 0.024361 -0.002858 0.018026 0.022991 0.012980 -0.000899 0.006482 0.028560 0.022589 0.009026 0.011544 -0.004435 -0.013627 0.060227 0.032626 0.025302 0.037208 0.030620 0.035724 0.015268 0.019206 0.020524 0.011151 0.007160 0.031174 0.034433 -0.000007 0.033082 0.037198 0.018118 -0.008614 0.013131 0.008240 0.006426 -0.003720 -0.011638 0.022393 0.025151 0.032094 0.018003 0.024743 0.015465 0.010363 -0.014278 0.006464 0.060451 0.062133 0.037597 0.003369 0.019214 0.013118 0.004201 -0.013938 0.009303 0.054059 0.043343 0.009631 0.002626 -0.000016
-0.030836 -0.005425 -0.001485 -0.038671 -0.000442 0.006454 0.033083 0.043206 -0.001974 -0.010254 0.018494 0.012629 0.018693 0.034380 -0.000376 -0.017407 -0.052299 -0.001144 -0.016222 0.014761 -0.000111 -0.018142 0.024219 0.005854 0.001153 -0.000605 -0.014535 0.003010 0.000856 0.002046 -0.002788 -0.000946 -0.002279 0.011037 0.003413 -0.014774 0.012847 0.012370 0.030794 0.007823 0.004235 -0.031841 0.011376 0.003873 0.000517 0.022422 -0.015854 -0.000002 -0.021099 0.015893 -0.004351 0.027874 0.004718 -0.013059 0.038487 0.011043 0.017645 -0.002920 0.009176 0.012304 0.004630 0.004233 0.002758 -0.000949 -0.009750 -0.019643 0.000745 0.009486 -0.004754 -0.003856 -0.016540 -0.028468 -0.034290 -0.052721 0.008275 -0.003107 -0.003049 0.006893 -0.015864 -0.001682 0.014235 0.026498 -0.025606 -0.011874 0.001904 0.012686 -0.000458 -0.012539 -0.023225 -0.007422 -0.024051 -0.014921 -0.032976 0.006674 -0.018924 -0.000952 -0.024738 0.016875 0.023053 -0.001728 -0.019151 -0.023417 -0.028261 -0.046134 -0.038407 -0.005638 -0.023504 -0.016371 -0.025193 -0.024020 -0.025470 -0.022452 -0.000881 0.001564 0.003103 0.008682 0.019779 -0.020056 -0.033854 -0.039755 -0.041796 -0.050318 -0.032417 -0.057298 -0.060413 -0.001998 -0.014108 -0.000952 -0.000436 0.046625 0.007024 -0.006000 -0.018318 0.003921 -0.013496 0.015225 0.024807 0.024290 0.012918 -0.017883 -0.025465 -0.023504 -0.019581 -0.008209 -0.000851 -0.012272 0.052054 0.070098 0.009643 -0.023832 -0.024504 0.006170 -0.018321 0.016912 0.004646 -0.003527 -0.015315 0.004521 0.009039 -0.000952 -0.021717 0.011198 -0.030724 -0.018593 0.004700 0.029175 0.007974 0.012256 -0.004303 -0.022006 -0.003211 -0.006098 0.019063 0.043806 0.036934 0.026497 -0.014361 -0.022060 -0.001406 0.004655 -0.035518 0.008479 0.051192 0.064021 0.036151 0.000420 -0.015856 0.037785 0.015425 -0.007822 -0.022511 -0.000962
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>192</cols>
<dt>d</dt>
<data>
-0.017642 -0.024400 -0.011820 0.004054 0.011450 -0.010965 -0.020829 0.018655 0.051643 -0.013805 -0.041814 -0.020351 -0.020879 -0.017480 -0.006319 -0.012303 0.004894 0.020780 -0.003708 -0.063961 -0.033596 -0.018925 0.000243 -0.014948 -0.033368 0.012541 0.063650 -0.011555 -0.007685 -0.013310 -0.017954 0.019722 -0.006890 0.008169 -0.007992 -0.006987 -0.005121 0.003298 0.014654 0.018329 0.010666 -0.033695 -0.035814 -0.006297 0.007200 -0.001427 0.001191 -0.000317 0.018036 0.038357 -0.022398 -0.024098 -0.012953 0.000532 -0.003910 0.005825 0.010772 0.027306 0.012626 0.021187 0.042265 -0.029979 -0.026234 0.019800 -0.005940 -0.008552 -0.023007 -0.012200 -0.034393 -0.026544 -0.022869 -0.022177 -0.030193 -0.025374 -0.004548 -0.003690 0.004768 -0.007426 0.007743 -0.033923 -0.002807 0.009540 0.003775 -0.004865 -0.029048 -0.003889 -0.038303 -0.017869 -0.047192 -0.028626 -0.009258 -0.045847 -0.041182 -0.021653 -0.005203 0.019800 0.018340 0.021357 -0.002351 0.001219 0.001286 -0.010548 -0.011307 -0.003684 -0.001462 0.007597 0.003010 -0.011254 -0.018006 -0.022348 0.008443 -0.015762 -0.007118 -0.012727 0.072365 0.034784 -0.005881 -0.014514 -0.012279 -0.009585 -0.024755 -0.015775 -0.010054 -0.013323 -0.022019 0.001316 0.007951 0.019800 -0.001144 0.001974 0.002806 0.001255 0.043862 0.013906 0.005313 0.001520 -0.010680 -0.026901 0.015556 0.015020 0.020297 0.011946 0.032076 0.011111 0.008553 -0.026983 -0.009412 0.009181 0.016730 0.017972 0.050320 0.046679 0.016472 0.011381 -0.024674 0.059484 0.027058 -0.010726 -0.019489 0.010409 0.006926 -0.002632 0.006907 0.002025 0.053307 0.019080 0.023275 0.013379 -0.005483 -0.021592 -0.007352 -0.007544 0.045270 0.017105 0.038066 0.012114 0.014158 -0.027057 -0.002619 -0.007514 0.002344 0.036257 0.045256 0.038838 0.019797 0.037709 -0.024162 0.053676 0.028074 0.014579 -0.011500 0.010409
-0.013575 0.007468 0.006766 0.006876 -0.003329 -0.009732 -0.020676 0.001492 0.051088 -0.011185 -0.018198 -0.013289 0.003756 0.007000 0.008491 -0.013144 -0.018129 -0.014353 -0.004270 -0.027296 -0.001011 0.004264 0.022526 0.003014 -0.039943 -0.008543 0.048622 -0.006739 -0.010348 0.010504 -0.013533 0.019675 -0.014057 0.010208 -0.008625 -0.006395 -0.013514 -0.001704 0.003829 0.048722 0.039002 0.000025 0.004678 -0.004477 0.002781 -0.000418 -0.000259 -0.011841 0.002608 0.017179 0.020648 -0.004321 -0.005436 -0.004946 0.004619 -0.005791 -0.008940 0.042934 0.029459 0.013678 0.039449 -0.007741 -0.013452 0.019752 -0.009144 0.015215 -0.015404 0.010268 -0.021920 -0.015124 -0.016300 0.002160 -0.004230 -0.022837 -0.016689 -0.048334 -0.016898 -0.019922 -0.020578 -0.007435 -0.009701 0.008880 0.003747 -0.000386 -0.052694 -0.007817 -0.026180 -0.027969 -0.020666 -0.006740 0.004956 -0.040663 -0.030306 -0.026011 -0.001068 0.019752 0.019079 0.056189 -0.008010 0.015897 -0.013356 -0.020019 -0.013805 0.006085 0.005726 -0.007665 0.001572 -0.016042 -0.006737 -0.020128 -0.001955 -0.030822 -0.009325 -0.009744 0.081905 0.065178 -0.016395 -0.005646 -0.023862 -0.014639 -0.040391 -0.008942 0.001896 -0.013866 -0.012938 -0.004823 0.006614 0.019752 -0.010921 -0.025968 -0.009866 0.004202 0.041726 0.017870 -0.013081 0.011323 -0.005219 -0.033254 -0.009031 0.013805 -0.006611 0.013053 0.018353 0.009525 -0.009524 -0.027534 -0.028106 -0.019601 -0.001155 -0.001053 0.053795 0.027568 0.002125 0.003824 -0.031756 0.036317 0.034939 -0.040090 -0.041136 0.010361 -0.030164 -0.014320 -0.000991 -0.005066 0.042831 0.046073 0.006507 0.012057 0.004056 -0.006600 -0.007425 -0.016887 0.045311 0.019035 0.024114 0.011900 0.005651 -0.006456 -0.009446 -0.010773 -0.016288 0.034575 0.051438 0.045986 0.007183 0.014618 0.002795 0.041412 0.034514 -0.005385 -0.009435 0.010361
0.019576 0.014298 0.010259 0.002637 0.004011 -0.021301 -0.005929 -0.035293 -0.012595 0.000382 0.001696 -0.024893 0.026069 0.006103 0.020695 0.004003 -0.009862 0.011751 0.033347 0.008166 -0.006717 0.012961 0.019924 0.004101 -0.008250 -0.038867 -0.000021 -0.008357 -0.008460 0.016814 0.005474 0.015605 -0.005880 -0.013603 -0.002036 -0.002974 -0.004362 -0.008896 0.011743 -0.000885 0.028511 0.016199 0.039439 -0.028680 0.016331 0.002698 0.009193 0.003530 0.012728 0.016012 0.041350 0.027623 -0.017952 0.005777 0.010572 0.002905 0.011450 0.002020 0.039560 0.002728 0.031425 0.007600 0.000233 0.015683 -0.012517 -0.004024 0.001391 0.018192 0.013870 0.020452 0.004006 -0.042612 -0.022351 -0.014467 0.017423 -0.011113 0.003050 -0.025722 -0.007056 0.014664 0.013466 0.001558 -0.003789 0.009887 -0.001965 0.025917 -0.000392 0.012104 0.015402 -0.018802 0.006162 -0.025630 0.004718 -0.014096 0.020023 0.015683 0.011090 0.025503 0.009580 0.006811 -0.024383 0.000533 0.015182 0.018719 0.002635 -0.030187 0.009330 0.005773 -0.022038 -0.013237 0.000175 -0.024160 0.008150 0.018723 0.066862 0.039705 0.017275 -0.009589 -0.020043 -0.009741 -0.020947 0.006402 0.030637 0.000205 0.011495 -0.014815 0.011695 0.015683 -0.001034 -0.003129 -0.000896 -0.011548 -0.017638 -0.014542 0.005425 0.005860 0.004545 -0.013727 -0.026332 -0.025696 -0.003853 0.008527 -0.003676 0.002065 -0.007456 -0.033307 0.000925 -0.021775 -0.028408 -0.014901 -0.005443 -0.019870 -0.001211 -0.011934 -0.023621 0.022505 0.026575 -0.059690 -0.053695 0.006292 -0.016933 0.000451 0.000809 0.012007 0.022196 0.034846 0.000286 -0.006052 0.000565 -0.001142 -0.018393 -0.001580 0.024309 0.025391 0.033025 0.008755 -0.000603 0.015929 -0.002095 -0.000791 -0.010504 0.025947 0.057197 0.043138 0.003814 -0.006645 0.013956 0.026188 0.037814 0.002683 -0.003580 0.006292
-0.005424 -0.010245 -0.002451 0.015020 0.000943 -0.042199 -0.003684 -0.001501 -0.011858 0.027834 0.009108 0.006136 0.035769 0.032831 0.013473 0.022762 -0.019191 -0.017963 0.016530 -0.001123 0.011800 0.038436 0.030215 0.010208 0.007945 -0.014991 -0.020704 -0.014622 -0.004597 0.022699 0.019789 0.015605 0.003141 -0.007854 0.022778 -0.004984 -0.028289 -0.008264 0.017053 0.019452 0.032176 0.008744 0.018167 -0.002212 0.003017 0.001602 0.004380 0.015882 0.007795 -0.004845 0.022870 0.005769 0.014446 -0.001519 -0.016575 0.006152 0.029324 0.020361 0.023347 -0.013070 0.025099 0.011561 0.022484 0.015683 -0.023764 -0.027801 0.008857 0.036063 0.017235 -0.000537 0.024851 -0.019088 0.002667 -0.008983 -0.007524 -0.000438 0.005071 0.010741 0.015841 0.030623 0.020021 -0.035795 -0.016022 -0.032350 0.008516 0.044939 0.046542 0.012392 0.038246 -0.010373 -0.027826 -0.007259 0.012887 -0.006838 0.023856 0.015683 0.030843 0.043609 0.027660 0.010122 0.014881 -0.012441 -0.013701 0.032786 0.019984 -0.011688 0.003837 -0.003392 -0.009009 -0.005062 0.016746 0.034636 0.017323 0.001590 0.066457 0.032585 0.017165 0.010517 0.012903 -0.010903 0.006259 0.034737 0.028260 0.038585 0.038143 -0.007897 0.024847 0.015683 -0.013038 0.003467 -0.004154 0.013926 -0.001433 -0.014978 -0.006445 0.031146 -0.002873 -0.002679 -0.008405 -0.011118 0.010518 0.004566 -0.018236 0.000090 -0.016202 0.000753 0.005918 0.000105 -0.024047 0.018660 -0.005022 -0.023750 -0.011421 0.009466 -0.002948 0.053879 0.032908 -0.048361 -0.054969 0.006292 -0.031206 -0.016001 -0.005429 -0.001510 0.021429 0.010060 0.005288 -0.014336 -0.028000 -0.010511 -0.004398 -0.008653 0.026060 0.016673 0.013891 0.025861 0.022228 0.008565 -0.029611 -0.015931 -0.009378 0.016821 0.038939 0.018542 0.025374 0.006596 -0.009703 0.027464 0.005847 0.002768 -0.021932 0.006292
0.023824 -0.010428 0.001753 -0.003087 0.013982 0.027183 -0.003180 -0.008569 -0.028211 0.030570 0.014769 0.034518 0.006391 0.009748 -0.014008 0.038162 -0.009529 -0.022081 0.044353 0.007780 0.029719 0.004888 0.009706 0.001477 0.018742 -0.011667 -0.041359 0.000786 -0.010176 0.034313 0.023069 0.021605 0.015628 0.016070 0.009426 -0.005976 0.001812 0.058117 0.026175 0.032179 0.014717 0.060303 0.030984 0.014974 0.028925 -0.006638 0.012304 0.009531 -0.009024 0.007716 0.069875 0.046529 0.020520 0.035894 0.011887 0.041249 0.023327 0.026722 0.022071 0.031886 0.024014 0.050708 0.042931 0.021682 -0.022140 -0.030420 0.009292 0.021157 0.041874 0.022913 0.007914 0.005518 -0.003848 0.001297 -0.011786 0.005861 0.030424 0.043310 0.052586 0.025998 -0.003684 -0.017560 -0.011458 -0.038083 0.008887 0.048383 0.063203 0.061125 0.020896 0.003570 -0.022920 0.039409 0.007648 0.027650 0.009535 0.021682 0.052715 0.045375 0.057149 0.072423 0.044641 -0.018576 -0.023640 -0.001644 -0.003845 -0.010949 -0.018095 -0.007978 0.001500 0.014757 0.003864 0.022738 -0.002451 0.005520 0.049254 0.024777 0.041661 0.058938 0.051282 -0.003511 -0.011516 -0.005900 0.005800 0.075034 0.039578 0.009744 -0.014283 0.021682 0.010544 0.012613 0.012746 0.019283 0.012794 0.008452 -0.034786 -0.006023 -0.024706 -0.020705 -0.018665 0.018144 0.006414 0.001732 -0.015791 0.014581 0.016522 0.007465 0.007537 -0.009008 0.021329 0.014824 -0.005849 0.012211 -0.012701 -0.000587 -0.017177 0.051790 0.043168 -0.026821 -0.058419 0.012291 0.005730 0.016981 0.002389 0.008207 0.035049 -0.014610 -0.025900 -0.017156 -0.010334 -0.019824 -0.025219 0.004564 0.020019 0.008831 0.007375 0.012087 0.020134 -0.017274 -0.001391 -0.002368 0.004417 0.018802 0.011722 0.007109 -0.016274 0.002850 -0.026232 0.009888 0.014072 -0.005195 -0.013557 0.012291
-0.020052 -0.007517 -0.006545 -0.014973 0.053887 0.064595 0.036752 0.018318 -0.021182 -0.016969 -0.012825 -0.008308 -0.004845 0.003248 -0.027392 -0.012403 -0.008199 -0.019555 -0.033615 -0.017149 -0.010700 -0.015731 0.033781 0.054685 0.013931 0.000949 -0.038492 0.012430 -0.039203 0.040769 -0.015864 0.015729 -0.010451 -0.015959 -0.007881 0.005409 0.052709 0.044913 0.048985 0.007672 -0.007391 -0.000716 -0.016915 -0.005771 -0.004001 -0.003651 -0.011172 0.002265 -0.015992 -0.005675 -0.006314 -0.025788 -0.021266 0.000218 0.025561 0.034250 0.034277 -0.011271 -0.015514 0.035279 -0.027599 0.036984 -0.018088 0.015807 -0.014265 -0.013583 0.003930 0.011558 0.055517 0.039542 -0.003814 -0.020077 -0.021753 -0.007679 -0.016934 -0.000728 0.006771 -0.007118 0.025079 -0.002698 -0.003870 -0.008007 -0.016881 -0.026822 0.001668 0.001533 0.027190 0.045129 -0.013701 -0.027237 -0.024973 0.048010 -0.027525 0.027287 -0.037463 0.015807 0.008294 0.035271 0.024128 0.053190 0.029342 -0.001682 -0.043839 -0.023621 -0.030530 -0.017455 -0.024124 -0.023736 -0.036490 -0.014805 -0.023449 0.018568 0.012228 -0.006993 0.004360 0.005862 0.004055 0.012391 0.010024 -0.006717 -0.043551 -0.016689 -0.028112 0.048151 -0.017760 0.002427 -0.063790 0.015807 -0.017131 -0.008458 0.015507 0.009394 0.035625 0.011587 -0.001103 -0.006992 -0.004569 -0.010106 -0.023830 -0.015169 -0.005094 -0.015616 -0.019940 0.008658 0.001120 -0.000819 -0.006405 -0.021813 0.003250 0.014415 0.007714 0.002401 0.003924 -0.011174 -0.010489 0.045005 -0.006503 0.004881 -0.065509 0.007427 -0.000741 0.014472 0.031123 0.030255 0.067298 0.047116 0.002790 -0.005749 0.011998 -0.000449 -0.008935 -0.029870 -0.004493 0.013671 0.007275 -0.019267 0.000488 0.000285 0.004957 0.012008 0.007576 0.023905 0.046869 0.042156 0.000312 -0.008597 0.008677 0.037922 0.005124 0.037665 -0.006576 0.007427
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>192</cols>
<dt>d</dt>
<data>
0.031060 -0.023546 -0.024495 -0.018588 0.013122 0.047195 0.015312 -0.018387 -0.024813 0.024649 -0.031754 -0.021173 0.009040 0.052674 0.026868 0.004597 -0.013591 -0.005615 0.016204 -0.040981 -0.022022 -0.003090 0.048285 0.042631 0.019022 -0.030248 -0.022244 -0.033054 0.013746 0.008324 0.031043 0.003543 0.049329 0.002821 0.017834 0.007910 -0.022420 -0.027261 -0.035725 -0.023998 -0.012927 0.030546 -0.032417 -0.005595 -0.012701 0.005373 0.003464 -0.012139 -0.000879 -0.013334 0.043672 -0.003603 0.028824 -0.005563 -0.017558 -0.025131 -0.041917 -0.023737 -0.019039 -0.038356 -0.018160 -0.007982 0.025788 0.003543 0.027952 -0.006302 -0.000959 0.074602 0.065268 -0.008187 -0.028359 -0.029588 -0.020865 0.002923 -0.028886 -0.016107 0.030158 0.069746 0.005800 -0.017134 -0.038172 -0.012330 0.020654 -0.005599 0.027904 0.135706 0.105464 0.000824 -0.043685 -0.063367 -0.024595 -0.003981 0.003258 0.006635 0.026878 0.003543 0.008127 -0.028106 -0.024157 0.009432 0.078459 0.072276 0.026044 -0.027894 -0.010754 0.035341 -0.046328 -0.060579 -0.005460 0.038865 0.032119 0.045120 -0.014769 -0.000939 0.020851 -0.060107 -0.070615 0.038138 0.111098 0.109066 0.075309 -0.023084 -0.001620 0.008437 0.018804 0.015485 0.017046 0.003543 -0.018639 -0.035415 -0.014496 -0.050729 -0.008764 0.042881 0.044648 -0.003068 0.003012 0.042866 -0.019576 -0.047692 -0.059830 -0.011089 0.035814 0.075241 0.024162 -0.027390 0.002997 -0.049135 -0.053906 -0.088971 -0.016975 0.078376 0.111851 0.052297 -0.013111 -0.013616 0.029870 -0.023509 -0.005975 0.003541 0.045045 -0.037319 -0.019029 -0.017443 -0.014058 -0.018121 -0.002435 -0.021893 -0.008720 0.035732 0.000403 -0.009932 -0.022910 -0.006273 -0.006230 -0.023287 0.010731 -0.028079 0.041147 -0.018426 -0.018667 -0.035078 -0.017918 -0.025409 0.001126 0.005307 0.002023 -0.016772 0.023940 -0.061732 -0.013232 0.002777
0.002408 0.008590 0.003059 -0.008565 0.047364 0.028293 -0.000784 0.016027 -0.007932 0.005363 -0.026344 -0.024526 -0.026051 0.057618 0.047701 0.015448 -0.013115 -0.016760 -0.004147 -0.001726 -0.006301 -0.016671 0.056514 0.031784 0.018197 0.008138 -0.009634 -0.010911 0.004119 0.021773 0.035835 0.011858 0.031745 0.046876 0.021128 0.010254 -0.017560 -0.000751 -0.022719 -0.016496 -0.031743 -0.004592 0.055462 0.049076 -0.003200 -0.025938 -0.009948 -0.005443 0.001845 -0.022297 0.044708 0.122492 0.092338 0.024284 -0.038167 -0.014359 -0.024532 -0.006986 -0.035341 0.003976 -0.006508 0.005649 0.023139 0.011858 -0.026810 0.022724 0.016913 0.017371 -0.050979 -0.033922 -0.032825 -0.057706 -0.054360 -0.060654 0.018260 0.088595 0.075043 0.049864 0.005595 -0.014327 -0.019960 -0.018071 -0.047181 0.064840 0.114874 0.111763 0.016769 -0.014606 -0.041843 -0.066939 -0.065002 0.013914 -0.025240 -0.010700 -0.013448 0.011858 -0.040892 -0.020136 -0.030200 0.019850 -0.006154 -0.024133 -0.003398 -0.028575 -0.044116 -0.052455 -0.052330 -0.002443 0.014588 0.038316 0.047310 0.020000 -0.003424 -0.023870 -0.077387 -0.056004 -0.008223 0.045447 0.032031 0.042947 0.013543 -0.020133 -0.060103 -0.013986 -0.039729 0.000934 -0.037757 0.011858 -0.022762 -0.036376 -0.040584 -0.026044 -0.018109 -0.002805 0.025970 0.064871 0.065567 -0.003093 -0.029814 -0.031624 -0.029386 -0.018640 0.016102 0.060692 0.082241 0.001361 0.005507 -0.048473 -0.061115 -0.053893 -0.025549 0.033473 0.103032 0.149767 0.072941 0.000563 0.008927 0.025208 -0.007561 0.011856 0.042053 -0.009556 -0.011935 -0.021126 0.014003 -0.003398 -0.013962 0.015043 0.019630 0.016853 -0.013180 -0.027315 -0.020907 -0.010477 -0.044948 -0.024648 0.039643 0.051121 0.042963 -0.005189 -0.031756 -0.034160 -0.002667 -0.033021 -0.008214 0.076447 0.085913 0.004763 0.034041 -0.022643 -0.017626 0.011092
0.045317 0.023715 -0.050942 -0.018236 0.049893 0.024526 -0.008345 -0.013330 -0.026415 -0.004546 -0.001394 -0.038271 -0.019855 0.007494 0.038155 0.003017 -0.043179 -0.011793 0.018174 0.026146 -0.060035 -0.021977 0.023826 0.029682 0.001974 -0.040190 -0.013241 -0.026863 -0.019222 0.010732 0.014524 0.011865 0.019886 -0.016994 -0.053546 -0.035380 -0.014157 0.009493 -0.025852 0.002103 0.035124 0.059092 0.098325 0.043152 -0.010317 -0.016283 -0.039916 -0.030713 -0.001034 0.021807 0.098687 0.097572 0.030321 -0.033364 -0.040891 -0.034335 -0.050640 0.015523 0.069725 0.013250 0.003210 -0.001821 0.006475 0.011865 -0.026078 0.044318 0.015136 -0.027913 -0.044062 -0.034561 -0.023311 -0.041163 -0.033296 -0.025438 -0.011986 0.010940 0.030026 0.009661 -0.003607 -0.007385 0.018736 0.008407 -0.002927 0.038508 0.049988 0.020740 -0.019173 -0.020423 -0.024391 -0.011721 -0.013996 0.005360 -0.009840 -0.031423 -0.030836 0.011865 -0.014135 0.018229 -0.002652 0.011463 -0.011613 -0.015294 -0.011030 -0.028627 -0.041109 -0.055669 -0.063587 -0.028165 0.001574 0.011684 0.033710 -0.014405 0.016855 -0.020716 -0.049224 -0.034596 -0.010664 0.013642 0.003447 0.016941 -0.012471 -0.001036 -0.054905 -0.032746 -0.036059 -0.009583 -0.022250 0.011865 0.021355 0.076500 0.051800 0.039032 0.003645 0.013902 -0.011744 0.022532 0.003483 -0.012970 -0.013138 -0.027484 -0.011912 0.007507 -0.014420 -0.008461 0.019839 -0.008281 0.032681 0.075830 0.030095 0.026612 0.021856 0.012967 -0.003570 0.046968 0.021547 0.002357 0.006423 0.035208 0.027280 0.011863 0.046324 0.011660 0.020389 -0.018202 0.008124 0.013849 -0.049883 0.002643 0.012531 0.059055 0.023952 -0.013430 -0.006422 0.016132 -0.007575 -0.001371 -0.027427 0.062672 0.066535 0.042950 0.010650 -0.019856 0.012576 0.006263 -0.032898 0.009089 0.091481 0.029345 0.035455 0.004308 0.003025 0.011099
0.003929 -0.014416 -0.036521 0.002061 -0.007310 0.006688 -0.016109 -0.014196 -0.020826 -0.000242 -0.021703 -0.023990 -0.006494 0.013401 -0.017546 0.002012 -0.020583 -0.003328 0.005332 -0.003864 -0.034025 0.015419 -0.001498 -0.020421 0.002574 -0.025835 -0.009855 -0.043556 -0.040904 0.002198 -0.000316 0.012000 -0.004503 -0.019566 0.002852 -0.008954 0.003958 0.007613 0.016742 0.046405 0.076575 0.052453 0.023260 0.023632 0.000330 -0.016745 -0.030603 -0.030730 -0.004227 0.011025 0.082786 0.033819 0.052004 0.009035 0.001048 -0.017213 -0.002261 0.047318 0.086020 0.013398 0.029084 0.011668 0.016334 0.012000 0.011158 0.049220 0.026196 -0.016938 0.004578 0.036819 0.000575 0.013027 0.026648 0.006109 -0.023975 -0.019948 -0.007060 -0.039348 -0.025383 -0.001577 0.007963 0.028201 0.051483 0.028774 0.025027 0.003174 -0.011445 0.025619 0.007020 0.020688 0.044736 0.024789 0.042479 -0.020580 -0.010739 0.012000 -0.028171 0.036691 0.025620 0.020159 -0.004459 0.019213 0.000818 -0.022065 -0.046518 -0.030372 -0.041304 -0.034940 -0.028942 -0.001045 0.020342 0.021754 0.004993 -0.011837 -0.036366 0.009332 0.022383 0.012571 0.007815 0.027455 0.031798 -0.009575 -0.046871 -0.022993 -0.017611 -0.010126 0.003561 0.012000 -0.034665 0.090927 0.055317 0.018217 -0.009445 -0.001017 -0.014710 0.001521 -0.022849 0.015523 0.021745 0.038568 -0.012993 -0.028912 -0.015775 0.010760 -0.011589 -0.007574 0.002204 0.102257 0.100854 0.011795 -0.024358 -0.013696 0.002317 0.005441 -0.011029 -0.009781 -0.001582 0.023605 0.031621 0.011998 0.001490 0.025510 -0.003631 -0.040078 -0.012318 0.000918 -0.037312 -0.000125 0.015593 0.045713 0.011031 0.025813 -0.010506 0.030102 0.033409 0.027016 -0.007113 0.017264 0.038319 0.056992 0.021507 -0.029293 0.012867 0.022499 -0.001655 -0.007705 0.027933 0.016128 0.033417 -0.000124 0.008454 0.011233
0.007912 -0.011561 0.007858 0.049300 0.017240 -0.007835 -0.010198 0.006883 0.012273 -0.024480 -0.021100 -0.009836 0.022014 0.010611 0.009822 0.009213 -0.023159 -0.013007 0.006305 -0.006759 0.035874 0.055287 0.019304 -0.001960 0.001509 -0.013795 0.003270 -0.008888 -0.012169 0.006789 0.029330 -0.000000 -0.038170 -0.021018 0.006064 0.031604 0.062820 0.045153 0.054551 0.006236 0.018098 0.037476 0.009064 0.023969 0.034193 0.002865 -0.010865 -0.010858 -0.012495 -0.005081 0.028924 0.000708 0.048354 0.086028 0.071117 0.028154 0.039522 0.010280 0.023538 0.034116 0.026395 0.025191 0.024419 0.000000 -0.002775 -0.028751 -0.013264 -0.003702 0.021515 0.048097 0.006250 0.017414 0.002752 -0.017766 -0.001300 -0.050689 -0.019855 -0.045794 -0.052793 0.010240 0.016752 -0.008830 0.008010 -0.024547 -0.043782 -0.007112 -0.000175 0.020474 0.038000 0.029642 0.006039 -0.015391 0.009514 -0.023599 -0.028270 0.000000 -0.036108 -0.018839 -0.003480 -0.013233 -0.017492 -0.018827 0.000433 -0.030043 -0.018319 -0.022927 -0.030016 -0.014419 0.001786 -0.029585 -0.009404 0.043412 -0.024113 -0.027039 -0.043510 -0.032417 0.005056 -0.003595 -0.005440 0.003643 0.049786 -0.039218 -0.033122 -0.049010 -0.028132 -0.036412 -0.012881 0.000000 0.023354 0.056497 0.042687 -0.000772 0.001107 -0.004961 0.012990 -0.036805 -0.017668 -0.010848 0.031620 0.054593 0.013211 -0.009944 -0.001990 0.031120 0.037596 0.021565 0.036157 0.087591 0.089243 0.036564 0.007989 0.015132 0.053648 0.012560 0.019284 0.003127 0.023293 0.032054 0.056241 -0.000002 0.007293 -0.017555 -0.012468 -0.009828 0.043813 0.075938 -0.007237 0.008959 -0.018080 0.005528 0.013837 0.039684 -0.009851 0.030106 -0.003690 0.001722 -0.014166 -0.043978 0.002162 0.015937 0.044339 -0.025751 0.051677 0.062758 0.008453 0.000326 -0.042232 0.013201 0.025639 -0.006249 0.009847 -0.000767
-0.054206 -0.023030 0.035080 0.016814 -0.013872 -0.045755 -0.023438 -0.013884 -0.033815 -0.008312 0.020165 0.049932 0.084352 0.042736 0.013605 -0.011501 -0.036446 -0.058271 -0.041615 0.004981 0.116368 0.118457 0.046846 -0.024436 -0.030505 -0.045173 -0.074235 0.013495 -0.031647 -0.000156 -0.009903 -0.000000 -0.037432 -0.042693 -0.002471 -0.015628 -0.034272 -0.023578 -0.024571 0.007548 -0.024911 -0.015825 -0.000901 0.026447 0.043333 0.008351 0.010012 -0.009038 -0.023226 -0.004381 -0.049460 -0.030172 0.030494 0.054719 -0.005964 -0.015101 -0.034750 -0.021588 -0.037027 0.005390 -0.039804 -0.001148 -0.041387 0.000000 -0.045359 -0.043652 -0.040947 -0.034869 -0.011799 0.031311 0.061445 0.089015 0.019513 -0.026528 -0.025038 -0.024470 -0.030604 -0.045569 -0.014273 0.029816 0.001470 -0.012807 -0.055849 -0.060733 -0.058722 -0.052828 -0.035047 0.010435 0.062796 0.074791 0.001450 -0.013205 -0.022894 0.007722 -0.029768 0.000000 -0.018770 -0.004802 0.027739 0.009710 0.006354 -0.004211 0.034682 0.010345 -0.002804 -0.027245 0.013533 -0.005173 0.005281 -0.021277 0.004222 0.025900 -0.006529 -0.029106 -0.025566 0.011878 0.019954 0.009472 0.001049 0.006636 0.036080 0.011972 -0.025539 0.001466 -0.007861 0.013177 0.001632 0.000000 0.009251 0.055764 0.042679 -0.007045 -0.012915 0.001007 -0.001121 0.011756 -0.001771 -0.017930 0.029404 0.043155 0.012591 -0.015260 -0.001842 0.014796 0.025255 0.014568 0.004585 0.060065 0.074500 0.009647 -0.005890 0.013467 0.007255 0.019021 0.013724 0.038491 0.003105 0.034544 0.019243 -0.000002 -0.022602 -0.035394 -0.028047 -0.004844 -0.018902 0.004685 0.024997 0.035857 -0.018474 -0.014790 -0.046138 -0.009904 -0.016749 0.007145 0.037168 0.045392 0.001782 -0.018436 -0.018591 -0.070428 -0.024491 -0.033282 0.010398 0.044473 0.065598 0.034634 -0.019931 0.003656 -0.009869 0.002381 -0.032586 -0.000767
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>192</cols>
<dt>d</dt>
<data>
0.017717 0.028181 -0.010629 -0.013982 0.017096 0.011579 0.015172 0.012862 0.019658 -0.012893 -0.020622 -0.007029 -0.015480 0.001072 -0.021799 -0.028066 -0.025162 -0.009804 0.019320 -0.015443 -0.002702 -0.025035 0.007205 -0.008904 -0.009781 -0.000738 0.001812 0.004712 0.004563 -0.018822 -0.010312 0.015598 -0.004166 -0.013634 -0.018660 0.004195 -0.001386 -0.027812 -0.014553 0.010275 0.003043 -0.044965 0.002281 0.000003 0.003384 0.004575 -0.020995 0.005841 -0.007105 0.007358 0.008619 -0.016194 -0.017948 0.003634 0.001907 -0.035521 -0.006753 -0.000890 0.000962 -0.007195 0.007173 -0.029343 -0.023583 0.010797 -0.029801 0.029094 -0.011294 -0.012360 -0.014257 -0.027962 -0.025218 -0.030457 -0.016282 -0.013449 0.028443 0.017750 0.029095 -0.018817 -0.023077 -0.008201 0.009524 -0.005091 0.005377 0.041000 -0.003227 0.004729 -0.011004 -0.030552 -0.036936 -0.021240 -0.030384 -0.036389 -0.041162 0.002336 0.017535 0.010170 0.002108 0.016615 -0.002970 -0.022360 -0.001407 0.026671 -0.006601 0.000802 0.008776 -0.013696 0.025555 0.001008 -0.001187 0.002058 -0.010796 0.000849 -0.002038 -0.022041 0.018009 0.017998 0.004875 -0.020423 0.020783 0.012154 -0.018730 0.009805 0.002468 0.021800 -0.004893 -0.006698 -0.009573 0.004850 -0.052633 -0.014370 -0.015577 -0.010393 0.014561 0.032758 0.030011 0.016269 0.003046 -0.024910 0.001412 -0.014922 -0.020346 -0.010376 0.017080 0.013183 0.003933 -0.011398 -0.048640 -0.013343 -0.028357 -0.011393 0.020417 0.022302 0.023895 0.011074 -0.004931 0.035095 -0.003860 -0.016807 -0.034543 0.001899 -0.030796 -0.012060 -0.002666 0.024401 0.054863 0.049201 0.021322 0.026214 0.028299 -0.009536 -0.002570 0.003743 0.025604 0.001840 0.014264 0.006521 -0.003394 0.008439 -0.022791 -0.006014 -0.011362 0.045685 0.051757 0.035820 0.020318 0.010179 0.019178 0.051223 0.029623 0.027694 -0.012522 0.006155
0.002319 0.023288 0.019241 -0.003918 0.017837 0.019042 -0.002748 0.001402 0.023421 0.023061 -0.024486 -0.009223 -0.021682 0.009923 0.001603 -0.006093 -0.003735 0.012201 0.052899 0.000124 0.001774 -0.029926 0.028712 0.033214 -0.011761 0.001390 0.016099 0.007876 0.032983 -0.009249 0.006787 0.015353 -0.061994 -0.027560 -0.023061 0.000477 -0.018531 -0.010303 -0.010697 -0.009335 0.022749 -0.003291 -0.008215 -0.013946 -0.014719 -0.044586 -0.039376 -0.013299 -0.024237 -0.000117 -0.010499 -0.020956 -0.033037 -0.010378 -0.043157 -0.030328 -0.034193 -0.020762 0.011881 -0.040093 -0.012349 -0.055413 -0.033584 0.010552 -0.014593 0.039959 0.013934 -0.020576 -0.015996 -0.022986 -0.014017 -0.009511 -0.028408 -0.025445 0.039404 -0.015678 -0.007242 -0.023416 -0.027326 -0.004886 -0.000484 0.003634 0.013743 0.056318 -0.003522 -0.027394 -0.017278 -0.030105 -0.024543 -0.007758 -0.016770 -0.029265 -0.034590 -0.011536 0.012395 0.009925 -0.031638 0.055110 0.022207 -0.004428 0.010014 0.020192 -0.008433 0.000823 0.001933 0.001888 -0.002970 0.006158 -0.012006 -0.010694 -0.018476 -0.002072 0.001763 0.000895 0.015037 0.061821 0.025746 -0.008968 0.002512 0.009361 -0.005715 0.006765 -0.000416 0.039864 0.010468 -0.015439 -0.020626 0.004606 -0.032732 -0.025859 -0.007386 -0.019266 0.034478 0.022224 -0.007683 0.000510 -0.005397 -0.004484 0.004472 0.018954 0.012001 -0.000764 0.004564 0.019338 -0.015324 -0.034179 -0.022045 -0.021145 0.001475 -0.009840 0.043838 0.019730 0.020104 -0.019064 -0.029956 0.034739 0.012447 -0.024494 -0.039914 0.001654 -0.017230 -0.016153 -0.002358 0.023220 0.015692 0.015882 0.001464 0.017732 0.001537 0.011812 -0.004583 -0.019093 -0.010329 0.021512 0.007348 0.020005 0.002062 -0.009144 0.008587 -0.010821 -0.010698 0.012994 0.047349 0.022313 0.018770 0.009641 -0.008580 0.017200 0.011643 0.008839 -0.009693 0.005911
-0.009006 -0.000313 0.003560 0.018913 0.007270 -0.007940 -0.008434 0.002008 0.017953 0.035437 0.011431 -0.010199 -0.024901 -0.010342 0.001125 0.025785 0.024845 0.008510 0.040171 0.015237 0.002063 -0.010591 0.013279 0.007073 0.011810 0.024127 0.011957 -0.001775 0.024475 0.007270 0.010429 0.015352 -0.045605 -0.025527 -0.026908 0.001611 -0.009365 -0.014584 0.014943 0.023414 0.027723 -0.004923 0.003763 -0.002280 -0.013775 -0.014760 -0.015390 0.013099 -0.006992 0.017925 -0.002178 -0.024649 -0.024259 -0.022454 -0.011009 -0.018248 0.011375 0.028058 0.018587 -0.027982 0.017982 -0.022915 -0.003680 0.010551 -0.008692 0.039226 0.023246 0.033924 0.006179 0.006206 0.021350 0.009319 -0.025039 -0.043597 0.013782 0.001509 0.001829 0.008241 0.004956 -0.012499 -0.025827 0.036706 0.018197 0.052469 0.020553 0.030375 0.009556 0.020708 -0.006727 -0.005330 0.022352 0.001307 0.013755 -0.008155 0.035906 0.009924 0.006996 0.019812 0.004405 -0.019104 0.006028 -0.011528 0.008272 -0.003367 0.005958 -0.018240 -0.005759 -0.006665 0.006131 0.005000 0.006810 -0.001574 -0.020399 0.011493 0.010155 0.014908 -0.014346 -0.010080 -0.002972 0.007257 -0.000044 -0.015669 0.011980 0.034766 0.032054 -0.041539 -0.027982 0.004604 -0.042173 -0.044030 -0.035090 -0.017416 -0.006309 -0.004129 -0.000982 -0.003363 0.000689 0.015266 -0.018090 -0.013674 0.006674 0.012467 0.023305 0.012441 -0.017323 -0.024183 -0.012128 -0.058385 -0.046077 -0.002211 0.004659 0.016405 0.006186 -0.023962 -0.028758 0.014804 0.015419 -0.052793 -0.050931 0.001653 -0.022085 0.004350 0.002930 0.011828 0.012684 0.041627 0.013539 -0.004694 -0.033385 0.006293 -0.006468 -0.015789 0.010800 0.014079 -0.002637 0.028302 0.001516 0.004529 -0.011849 0.005625 -0.011053 0.013078 0.016694 0.031896 0.032617 -0.011300 -0.028869 0.013987 0.006911 0.006043 0.004840 0.005910
0.015428 -0.001165 0.005079 0.001609 -0.014876 0.027230 0.034920 0.038172 -0.005734 0.050120 0.032269 0.010001 0.006477 -0.012670 -0.037549 -0.013821 -0.018199 0.001571 0.057737 0.027626 0.019763 0.017233 -0.008403 0.000534 0.024527 0.021788 0.000975 -0.010578 0.012287 0.026979 0.027344 0.015078 -0.013274 -0.026188 -0.007032 0.029432 0.001255 -0.014751 0.023561 0.026821 0.041453 0.038027 -0.008369 0.023458 0.004612 -0.012732 0.008682 0.008212 -0.006170 -0.017316 0.027599 -0.023057 0.018478 0.019504 0.013188 -0.006899 0.025565 0.011164 0.006299 -0.006788 0.013996 0.010320 0.029462 0.010277 0.022512 0.014252 0.047652 0.063586 0.000742 0.007291 -0.008860 0.018361 -0.007466 -0.043195 -0.036343 0.010948 0.018907 0.009201 -0.011621 0.028918 0.032407 0.035126 0.021923 -0.016536 0.038172 0.050973 0.022175 -0.006367 0.022589 0.036906 0.028185 0.026228 0.039322 0.001037 0.028832 0.009650 -0.022770 -0.001772 0.017401 0.009953 -0.031901 -0.009062 -0.001895 0.001624 0.003451 -0.017109 -0.027848 -0.009246 0.006314 0.008927 -0.017530 0.019834 0.018364 0.002506 -0.009088 -0.029731 -0.005797 0.011716 -0.023820 -0.026249 0.014512 0.023845 0.013094 0.022239 0.038540 -0.050418 -0.034289 0.004331 -0.020147 -0.027250 -0.013116 -0.009222 -0.025453 0.008372 0.004349 -0.006553 -0.001421 0.006469 -0.036093 -0.037573 -0.010978 -0.028152 0.014796 0.007608 -0.010588 -0.017368 -0.006670 -0.059486 -0.047798 -0.025408 -0.039773 -0.002692 0.004503 -0.010595 -0.013164 0.016002 0.012558 -0.067268 -0.056665 0.001379 -0.011644 0.006425 0.015211 0.017992 -0.014221 0.006431 0.005396 -0.001133 -0.014803 0.003075 -0.023658 -0.024318 -0.020957 -0.028922 0.005429 0.021925 0.010479 0.019422 0.005436 -0.017009 -0.013703 0.002298 -0.030715 0.003263 0.006833 0.000301 0.003701 0.016532 -0.001945 -0.011323 -0.016403 0.005636
0.028071 0.004440 -0.038497 -0.031184 0.006804 0.027759 0.043143 0.014850 0.008480 0.039943 0.022074 0.011126 0.045915 0.036533 0.013617 -0.007539 -0.001658 0.000144 0.067595 0.029575 -0.020131 0.006274 0.028782 0.044247 0.041254 0.007155 0.017510 0.011720 0.004228 0.052955 0.036701 0.015078 0.008821 -0.025397 -0.012394 -0.013016 0.044089 0.064600 0.024410 0.011857 0.021535 0.014482 -0.010084 0.000257 0.039495 -0.011223 -0.001867 -0.003569 0.006654 -0.010466 0.023796 -0.027462 -0.007551 -0.001132 0.035682 0.046154 0.016529 0.010148 0.005436 0.021683 0.000747 0.029369 0.018056 0.010277 0.007531 -0.010152 0.016897 0.034418 0.064100 0.044457 -0.036694 -0.031994 -0.015445 -0.026703 -0.035840 -0.005633 0.034067 0.011991 0.008237 0.033824 0.024280 0.011562 -0.007563 -0.039229 0.005711 0.049252 0.037743 0.021595 -0.007476 -0.004285 0.001715 0.035199 0.014590 0.009008 0.001968 0.009650 -0.000561 0.000845 0.004643 0.034814 0.038372 -0.002802 -0.026595 -0.015673 -0.020418 -0.013878 -0.033601 -0.005567 -0.004893 0.034700 0.048605 0.073110 0.033952 -0.000054 0.003010 -0.024887 -0.010033 0.018976 0.009336 0.015437 0.039776 0.008813 -0.016746 0.055370 0.050804 -0.011528 -0.026293 0.004331 -0.000202 -0.017783 -0.000492 0.018291 0.054226 0.025984 -0.009375 -0.019595 -0.002083 0.004345 -0.018226 -0.033528 -0.012617 0.031588 0.061795 0.056938 0.034026 0.005794 0.017478 -0.030843 -0.028099 0.005975 0.027495 0.031413 0.047833 0.021536 0.011010 0.062775 0.067559 -0.019383 -0.026530 0.001379 0.015611 0.031031 0.029581 0.036115 0.029255 0.004409 -0.028488 -0.021068 -0.004624 0.003947 -0.009510 -0.001221 0.008119 0.013447 0.006368 0.012026 0.016381 0.003325 0.028074 0.026402 0.026676 0.043883 0.040492 -0.006242 -0.005022 0.001593 0.009220 0.043678 0.030768 -0.004018 -0.002214 0.005636
-0.015936 -0.027264 -0.028272 -0.010279 0.022428 0.047930 0.044135 0.004839 -0.007350 -0.003184 -0.016721 -0.016592 -0.001850 -0.012307 0.008897 0.005052 -0.003860 -0.005849 -0.005548 -0.036753 -0.040026 -0.008951 0.015348 0.023673 0.023389 -0.003704 -0.007986 0.027956 -0.053999 0.048194 -0.029781 0.020829 -0.030855 -0.033219 -0.035863 -0.033283 0.043236 0.064793 0.017365 -0.003326 0.002939 -0.013317 -0.031588 -0.011579 -0.009402 -0.002935 -0.010802 0.010039 -0.003394 -0.008009 -0.033109 -0.061053 -0.041964 -0.033998 0.027507 0.034773 0.015592 -0.008602 -0.001860 0.025097 -0.052892 0.029077 -0.043330 0.020829 -0.022494 -0.028602 -0.013164 0.006269 0.059436 0.067280 -0.039557 -0.027461 -0.012856 -0.013389 -0.041377 -0.005785 -0.025979 -0.004044 -0.014905 0.007497 0.012693 -0.001847 -0.030635 -0.059902 -0.020741 -0.003555 0.037790 0.023693 -0.034185 -0.008952 -0.017162 0.035696 -0.042356 0.017530 -0.057202 0.020829 -0.021638 0.014240 0.003727 0.019693 0.074971 0.065863 -0.039786 -0.016604 -0.023706 -0.020813 -0.034240 -0.008711 -0.006631 0.010976 0.008512 -0.006016 -0.014075 -0.014638 -0.038767 -0.014361 -0.006265 0.016979 0.034783 0.026540 -0.041903 -0.019719 -0.035758 0.053674 -0.015750 0.016971 -0.059079 0.020828 -0.001452 0.003901 0.022124 0.015159 0.083210 0.036574 -0.022447 -0.014394 0.003566 -0.008979 -0.014072 -0.007488 0.000388 0.022775 0.010424 -0.017963 -0.002344 -0.006549 -0.008812 -0.003001 0.011146 0.003201 0.046207 0.030187 -0.033333 -0.017630 -0.002034 0.061425 0.012148 0.025419 -0.050705 0.017876 0.023338 0.011711 0.004527 0.025057 0.028730 0.019642 0.008060 -0.017527 -0.002354 0.003021 -0.029120 0.001617 0.004851 -0.004992 0.008724 -0.004002 0.005607 -0.008375 0.033099 -0.006703 0.004504 0.013022 -0.000797 0.010076 0.001870 -0.001882 -0.001971 0.028676 0.017696 0.018462 -0.027822 0.022133
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>192</cols>
<dt>d</dt>
<data>
-0.005165 -0.020569 -0.049178 -0.041769 -0.020382 -0.001107 0.006554 -0.002643 0.013110 0.017122 -0.017870 -0.038902 -0.009349 0.003838 0.018910 0.003806 -0.002122 -0.006249 -0.003182 -0.021369 -0.067519 -0.040918 -0.013390 0.012493 0.020275 0.005584 0.012603 -0.036706 -0.014375 -0.003877 -0.016679 -0.001392 -0.015379 -0.016309 0.012595 -0.018038 0.005697 -0.002499 -0.005826 0.016853 0.016560 0.016383 -0.033434 -0.023825 0.001955 -0.008965 -0.012429 -0.001837 0.014386 -0.010769 -0.002784 -0.023437 0.039538 0.005050 0.001239 -0.007306 -0.004142 0.022706 0.006899 -0.017093 -0.019046 -0.006464 0.012018 -0.001385 -0.018761 -0.029683 0.006893 0.063167 0.057559 -0.001040 -0.016954 -0.007878 0.003545 0.022161 0.001551 0.025381 0.059706 0.022841 -0.022995 -0.012747 -0.015715 -0.038184 0.001230 -0.007001 0.077541 0.132418 0.070732 -0.009357 -0.027929 -0.021163 -0.026908 0.032108 -0.009978 0.010974 0.013492 -0.000000 -0.018226 -0.019300 -0.035163 0.035143 0.042219 0.034395 0.039961 0.029154 0.004159 0.007368 0.016668 0.027645 0.051591 0.001108 -0.001230 -0.014575 -0.020532 -0.029987 0.004351 -0.005050 0.010333 0.095164 0.060332 0.038434 0.011109 0.010736 -0.018429 0.036747 -0.000711 0.033507 0.001355 0.000000 -0.018350 -0.007329 -0.033498 -0.028223 -0.036839 -0.009661 0.014543 0.048091 0.012177 -0.024724 0.001117 0.012970 -0.011738 -0.034061 -0.023504 0.026728 0.023819 -0.024377 -0.025322 -0.014024 -0.013575 -0.016883 -0.033544 0.005605 0.022300 0.039271 -0.004158 -0.022441 -0.026296 0.012841 -0.017307 0.000000 -0.015037 -0.027330 -0.002623 -0.003375 -0.024028 -0.001396 -0.002979 -0.000675 0.007775 -0.012935 0.009320 0.016023 0.002207 -0.015861 -0.003948 0.040644 0.017008 -0.001305 -0.015717 -0.015845 0.029486 0.008684 -0.010239 0.023050 0.032293 0.020340 0.006465 -0.003561 -0.001582 0.001549 -0.005134 0.000000
0.011450 0.013668 -0.007870 -0.033543 0.012555 0.033838 0.004806 -0.004934 -0.019024 -0.006341 -0.024664 -0.019661 -0.023302 0.032832 0.016610 -0.019812 -0.021404 0.004605 -0.000143 0.001294 0.003328 -0.042106 0.022159 0.032155 -0.013550 -0.029992 -0.006776 -0.021435 -0.018864 0.001699 0.014940 -0.001392 -0.012014 0.054629 0.067587 -0.019917 -0.016450 -0.003073 -0.016373 -0.008169 -0.014647 -0.030387 0.000268 0.026091 0.070447 0.037278 -0.017665 -0.014272 -0.016695 -0.018229 -0.006267 0.084717 0.149221 0.078685 0.012516 -0.022437 -0.029704 -0.021397 -0.028239 0.036091 -0.008746 0.005166 -0.000263 -0.001385 -0.056340 -0.017944 0.007688 -0.027368 -0.038169 -0.043250 -0.034038 -0.025197 -0.042754 -0.032637 0.000595 0.006243 0.064081 0.034401 -0.008565 -0.008105 -0.019011 -0.041745 -0.067040 -0.020957 0.051357 0.054434 0.006855 -0.047206 -0.043393 -0.038261 -0.077232 0.028700 -0.058196 -0.035684 -0.067809 -0.000000 -0.021428 -0.023627 -0.080860 -0.068335 -0.065776 -0.047472 -0.021602 0.042561 0.003764 -0.018976 0.015540 0.011165 0.013386 0.002357 0.009511 0.003286 -0.017996 -0.007621 -0.044926 -0.013255 -0.063520 -0.035009 -0.042693 -0.037742 -0.015919 0.010710 -0.008454 -0.012272 -0.065466 0.014623 -0.065163 0.000000 -0.012622 -0.027099 -0.025668 -0.012593 -0.041168 -0.033309 -0.018588 0.031418 0.039590 -0.000434 -0.001121 -0.012180 -0.033944 0.000588 0.002730 0.016007 -0.001908 -0.007989 0.009237 -0.036649 -0.038137 -0.040936 -0.029088 -0.034674 -0.001693 0.007418 0.020015 -0.022025 -0.054596 0.034785 -0.023354 0.000000 -0.003120 -0.037246 -0.021603 0.025828 0.031579 0.014653 -0.009943 -0.008837 -0.005455 -0.023688 0.033855 0.003162 0.012987 -0.016694 0.019958 0.021687 0.003057 0.001513 0.001554 -0.015150 -0.021240 0.028539 0.012190 0.010219 0.005206 -0.009695 -0.011945 0.028371 -0.013411 0.024324 -0.019630 0.000000
0.030396 0.051337 -0.004752 -0.034228 0.021827 0.016922 0.009370 -0.007961 -0.006669 0.001219 0.026492 0.014987 -0.019278 0.012344 0.005857 0.009882 -0.001489 0.011834 0.032806 0.072021 0.037712 -0.034233 0.025314 0.011706 0.015616 -0.006289 0.014492 0.018256 0.006287 0.010799 0.029753 -0.001392 -0.003662 0.070587 0.022737 -0.050646 -0.020140 -0.028432 -0.023879 -0.005888 -0.021671 -0.017803 0.032909 0.023589 0.027913 -0.006467 -0.015549 0.011496 -0.010765 -0.017988 0.013883 0.090039 0.078137 -0.005610 -0.016413 -0.040950 -0.021288 -0.014153 -0.020153 0.039340 -0.007596 -0.023289 -0.024323 -0.001385 -0.021576 -0.025845 -0.091440 -0.079683 -0.048337 -0.043664 -0.027640 -0.004643 -0.036576 -0.021106 0.005371 -0.009636 0.031348 0.005835 0.012402 0.024993 0.012609 0.009691 -0.015690 -0.040720 -0.078068 -0.033406 -0.025959 -0.030182 -0.015074 0.002114 -0.024623 -0.000416 -0.017234 -0.047665 -0.079828 -0.000000 -0.010616 -0.020362 -0.047013 -0.062260 -0.053937 -0.062256 -0.042734 0.002137 -0.005542 -0.006619 0.021144 0.025026 0.041755 0.000010 0.031989 0.030060 0.010184 0.028441 -0.004366 -0.011163 -0.018577 -0.016840 -0.041655 -0.016048 -0.004034 0.004845 0.008434 -0.021594 -0.035987 0.008926 -0.008193 0.000000 0.003488 -0.021995 -0.022166 -0.023476 -0.016750 -0.012016 -0.012676 -0.000409 0.017447 0.003261 0.019729 0.000181 0.026891 0.029691 -0.005135 0.020543 0.005628 0.016298 0.011693 -0.012020 -0.023047 0.006330 0.004998 -0.012864 0.010650 0.007322 0.017076 -0.006807 -0.040575 0.043873 0.016958 0.000000 0.021169 -0.027382 -0.019033 0.000030 0.035215 0.020700 -0.021799 0.006018 0.006242 -0.009268 0.008202 0.001246 -0.002479 -0.008290 -0.000500 0.005743 0.011308 0.017370 0.023297 -0.029917 -0.016783 -0.004256 0.014339 0.014864 -0.016232 0.009545 0.002354 0.035773 -0.016657 0.018797 -0.016938 0.000000
0.017201 0.029521 0.020966 -0.033978 0.007895 -0.005464 0.007139 -0.002538 -0.028807 0.015903 0.029282 0.006668 0.008179 -0.000240 -0.011280 0.017007 0.016167 0.006858 0.046653 0.079137 0.035774 -0.018972 0.008580 -0.016638 0.010806 0.007191 -0.010804 0.019735 0.016848 -0.002508 0.013291 -0.001392 -0.011575 0.039368 -0.018457 -0.025408 -0.019234 -0.029793 -0.025946 -0.026660 -0.024920 -0.018596 0.015398 -0.023738 0.011402 -0.008589 0.009553 0.011297 0.010083 0.004127 0.002237 0.048127 -0.025002 -0.011476 -0.017716 -0.014961 -0.010024 -0.010692 -0.019886 0.025224 0.007295 -0.051008 -0.043589 -0.001385 0.007807 -0.006767 -0.041668 -0.026767 -0.019048 -0.039513 -0.025588 -0.009803 0.003319 0.009471 0.001002 0.012208 0.015470 0.026748 0.024648 0.028320 0.027710 0.037116 0.011289 -0.023245 -0.032791 -0.017561 0.009560 -0.011601 0.000554 0.004487 0.020337 0.007220 0.022586 -0.004706 -0.013472 -0.000000 0.003109 -0.017760 -0.013784 -0.013591 -0.013486 -0.034937 -0.037588 -0.029100 -0.011713 -0.004041 0.010893 0.015095 0.014735 0.005916 0.032571 0.043797 0.031505 0.040153 0.007886 -0.014693 -0.002620 -0.009083 -0.016071 -0.004702 0.005199 0.000518 -0.000592 -0.006495 -0.008640 0.007890 0.017509 0.000000 0.002101 0.005889 -0.005002 -0.011045 -0.013079 0.003475 -0.021973 -0.006271 -0.018846 -0.022692 0.010809 0.007916 0.011496 0.013532 0.011262 0.034528 -0.002574 0.053476 -0.022007 0.007965 -0.000323 -0.002723 0.003011 -0.013710 0.017357 -0.001646 0.017229 0.003570 -0.027934 0.025976 0.023373 0.000000 0.010679 -0.023055 -0.003758 -0.029988 -0.013237 -0.007971 0.005107 0.018955 0.022379 -0.006232 0.013488 0.010507 0.012512 0.013392 0.005819 0.008360 0.002753 0.012794 -0.001116 -0.019602 -0.002601 -0.011376 -0.010051 0.000437 0.000657 0.015703 0.002526 0.019782 0.004926 0.016587 -0.016544 0.000000
-0.005710 0.020337 -0.038735 -0.014938 0.018849 0.022061 0.014221 0.028847 -0.038005 0.001526 0.009215 0.005600 0.005427 0.011733 0.020199 0.015844 -0.005403 0.003143 0.022861 0.045592 -0.018914 -0.009730 0.028039 0.040288 0.025059 0.021386 -0.010163 0.008768 0.020833 -0.002385 0.007766 -0.001392 0.017569 0.025161 -0.016432 -0.010850 -0.027073 -0.016808 -0.007414 0.003034 -0.025594 -0.031081 0.022787 -0.000485 0.001305 -0.008655 -0.006998 0.003971 -0.027150 -0.001287 -0.002464 0.026853 -0.012426 -0.008746 -0.028295 -0.015716 0.000461 -0.026278 -0.012673 0.022913 0.031228 -0.057443 -0.046667 -0.001385 0.036928 0.002550 0.008909 0.003926 -0.036001 -0.038280 -0.033950 -0.010026 0.028807 -0.000985 0.002336 0.013158 0.038170 0.017122 0.002093 -0.012550 0.011008 0.035800 0.036113 -0.003573 0.013341 0.023931 -0.014176 -0.018590 -0.028553 0.001867 0.043381 0.019890 0.017651 -0.004341 -0.000667 -0.000000 0.027857 0.015909 -0.008963 -0.011471 -0.015228 -0.007248 -0.014780 -0.032538 0.009267 -0.003496 0.023712 0.004450 0.011592 0.016270 0.012690 0.029216 0.019757 0.044821 0.033146 0.022077 -0.013112 0.008490 -0.016805 0.001574 0.016268 -0.002499 0.029547 0.017180 0.001929 0.020963 0.017352 0.000000 -0.015015 0.012958 -0.015345 -0.007787 0.009998 -0.008117 0.000587 -0.007099 -0.026732 -0.018278 0.004775 -0.006393 -0.009621 0.016270 0.024921 0.011803 0.000438 0.006584 -0.029420 0.007361 -0.024556 -0.031447 0.014604 -0.005679 0.006958 -0.012953 -0.023974 0.002520 -0.017633 0.010700 -0.007869 0.000000 -0.009982 0.007414 -0.002716 0.000770 -0.000076 -0.030596 -0.024074 0.010821 0.010101 -0.005278 0.008453 0.007384 -0.001460 0.020222 0.013088 -0.014215 0.001349 -0.001912 0.002652 -0.002895 0.001112 -0.003622 0.008667 -0.012505 -0.020789 -0.000870 -0.008099 -0.000852 -0.012908 0.015420 -0.006707 0.000000
0.008020 0.007120 -0.045638 -0.016286 0.001007 -0.017124 -0.008151 -0.004052 -0.028396 -0.019515 0.011886 0.035892 0.004025 -0.021140 -0.004198 0.012029 0.016026 0.017611 0.033923 0.020113 -0.015644 -0.006756 -0.012655 -0.007682 0.006376 0.004247 0.001087 -0.000316 0.000755 -0.010658 -0.013768 -0.001392 0.006228 0.023407 -0.003780 -0.006593 -0.020473 0.000370 -0.008281 -0.020047 0.003580 -0.000446 -0.002221 0.018898 0.009727 -0.013979 0.008362 -0.006251 -0.005169 0.023791 0.009109 0.008604 0.002487 -0.009477 -0.031018 0.000890 -0.012021 -0.009774 0.022267 0.029605 0.046030 -0.035920 -0.036357 -0.001385 0.027103 0.024647 0.001406 -0.007281 0.006712 0.005382 -0.013491 -0.041958 0.013792 0.007339 0.008140 0.007069 0.008400 0.007959 0.002857 0.014873 0.004945 0.038337 0.019485 0.018875 0.004291 -0.000775 0.015204 -0.007209 -0.008599 -0.033243 0.030226 0.028276 0.026442 -0.005120 0.005193 -0.000000 0.022142 0.008195 0.001058 -0.008398 -0.004113 0.003806 0.017016 -0.015060 0.023558 -0.042244 -0.009654 -0.009545 -0.002046 0.015634 0.011729 0.019617 0.019446 0.027279 0.010803 0.001816 -0.006353 -0.019129 0.001323 0.008536 0.022821 0.017917 0.025666 0.018876 0.004483 0.003965 0.009643 0.000000 -0.000764 -0.000476 0.008452 -0.015221 -0.013222 0.001905 0.022265 -0.015711 -0.033274 -0.038196 0.000498 0.004596 0.015153 0.002658 0.020777 0.009962 0.013133 0.001597 -0.019482 -0.005154 0.003824 -0.008938 -0.021765 -0.004929 0.006418 0.005384 -0.033663 0.010367 -0.011763 0.004365 -0.010449 0.000000 -0.012598 0.026098 -0.005300 0.013623 -0.005510 0.019576 -0.006695 -0.001382 -0.015090 0.008828 0.006516 -0.000663 -0.001128 -0.007849 0.019702 0.013229 0.015327 0.033584 -0.002868 0.004268 -0.004348 0.006507 -0.011418 0.020136 0.005585 0.011924 0.012582 0.003940 -0.008675 0.038332 0.013670 0.000000
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>192</cols>
<dt>d</dt>
<data>
-0.033801 -0.007757 -0.026971 0.013715 0.033363 0.031407 0.013880 -0.014519 0.013213 -0.011980 -0.007676 -0.000449 0.025599 0.009530 0.010396 -0.010170 0.001485 -0.011413 -0.029742 -0.018122 -0.026963 0.030953 0.030923 0.042468 0.008687 -0.006617 0.005624 -0.016977 -0.026186 0.039732 0.016559 -0.011858 0.002626 0.013384 -0.013641 0.007643 0.019290 0.001671 0.001321 -0.002867 0.012654 0.000285 -0.018952 -0.001287 -0.002613 0.009498 -0.008602 0.004650 -0.007952 0.007988 0.018239 -0.008245 -0.016496 0.005239 0.028683 0.011444 0.014595 -0.009549 0.016939 -0.009260 -0.011786 0.025089 0.007787 -0.005955 0.015757 0.000781 0.002536 -0.016038 0.010080 0.021662 0.020502 -0.009923 0.026671 -0.003401 -0.005776 -0.033451 -0.034402 -0.012038 -0.034254 -0.015315 -0.021883 0.043138 0.047267 -0.001668 -0.021314 -0.044261 -0.006751 0.011386 0.009735 -0.014745 0.067636 0.009736 0.021827 -0.021114 -0.031829 0.005330 -0.053554 -0.027515 -0.017865 -0.004588 0.017742 0.009465 0.025756 -0.014748 -0.014373 -0.028209 -0.012068 -0.006300 -0.005844 0.017075 0.007266 0.008782 0.009483 -0.032660 -0.029485 -0.030638 -0.025438 -0.006121 0.014491 0.009845 0.024380 -0.009740 -0.028215 0.003545 0.004912 -0.034167 -0.031874 0.005330 -0.022567 -0.002184 -0.011979 0.011930 0.020114 -0.018906 0.002422 -0.007482 -0.008974 -0.019373 0.032764 0.005175 0.026144 0.025718 0.007598 -0.008639 -0.007941 -0.019258 -0.021368 0.013969 0.002239 0.023125 0.021996 0.018476 0.001798 -0.009718 -0.019526 -0.002995 -0.005565 0.006017 0.004693 0.005336 0.005987 0.018513 0.008834 0.023360 0.020539 0.001956 0.006013 0.005506 -0.002565 0.004133 0.024432 -0.022601 -0.006318 0.015416 -0.015816 -0.009542 -0.013714 0.036708 0.018173 0.039894 -0.003566 0.003146 0.021027 0.001343 0.002081 0.001125 0.043110 0.005432 0.026652 0.004470 0.010983 0.005336
-0.027342 -0.016282 -0.009632 -0.005326 0.035741 0.014772 -0.009381 -0.001095 0.009370 -0.009913 -0.019685 -0.011613 0.022518 0.025708 0.035348 0.010233 0.002814 -0.012520 -0.025112 -0.028739 -0.012472 0.017968 0.030047 0.023133 -0.001072 0.001858 -0.002603 -0.005536 -0.038043 0.045902 0.013571 -0.009140 -0.001130 -0.002013 -0.011158 -0.007384 0.023186 0.027321 0.009615 -0.017612 0.012418 -0.005654 -0.025470 -0.016981 0.007551 0.002197 -0.003631 -0.012181 -0.003124 -0.010200 0.006824 -0.024730 -0.034494 -0.001347 0.008390 0.025035 0.000343 -0.013196 -0.004822 -0.015856 -0.029315 0.029595 -0.000570 -0.003237 0.012482 0.003871 -0.008673 -0.003972 0.013430 0.026683 0.018148 -0.018122 0.036983 0.007279 0.010136 -0.009595 -0.015689 -0.017078 -0.012315 -0.001234 0.007886 0.015276 0.061087 0.006521 -0.013698 -0.020746 -0.012699 0.008134 0.014692 -0.005967 0.058640 0.024129 0.022369 -0.003612 -0.012012 0.008048 -0.056324 -0.043446 -0.025586 0.002844 0.001389 0.004340 0.017760 0.007555 0.011402 -0.005060 0.016856 0.022672 -0.012176 -0.005284 -0.046281 -0.002029 0.019613 -0.017285 -0.009654 -0.008682 -0.003251 -0.010205 -0.009743 -0.027565 0.008228 0.019126 0.007802 0.015181 0.001684 -0.031457 -0.036810 0.008048 -0.004143 0.002780 0.000855 0.014349 0.000142 0.014049 0.018725 -0.010169 -0.027520 -0.020196 0.011368 -0.005853 -0.020327 0.009167 -0.016406 -0.010935 -0.001005 -0.010687 -0.013439 0.004812 0.002303 -0.007363 -0.003799 0.000771 0.003690 -0.007163 -0.021113 -0.020427 -0.008842 0.007305 -0.004343 0.008054 0.018156 0.002524 0.014372 -0.017504 -0.020407 0.003631 0.012340 0.008271 0.018567 -0.004949 0.019865 -0.025943 -0.022896 0.013289 -0.005532 0.000531 -0.009512 0.035342 0.034084 0.022674 -0.000409 -0.033732 -0.010492 0.004571 0.010524 -0.005320 0.049710 -0.002486 0.013348 -0.003532 0.011594 0.008054
-0.019217 -0.010972 0.024213 0.026488 0.029678 0.042218 -0.000720 0.005455 0.005637 -0.004802 -0.010190 -0.020135 -0.009212 0.011112 0.020045 0.023689 -0.010084 -0.005813 -0.017899 -0.014539 0.005708 0.012282 0.018604 0.022265 0.024065 -0.007632 -0.001718 0.005004 -0.026730 0.045000 0.022637 -0.009159 -0.039831 -0.006114 -0.010626 -0.033020 -0.001118 0.037792 0.003014 -0.021925 0.014353 -0.016767 -0.007637 0.000432 0.010362 0.037294 0.016134 -0.002457 -0.004737 -0.042377 -0.020318 -0.018298 -0.014653 -0.023042 0.025345 0.013594 0.000157 -0.016089 -0.005851 -0.029529 -0.044148 0.040280 0.001705 -0.003255 -0.015126 0.022537 -0.010454 -0.022325 -0.011980 0.011869 0.003283 -0.007815 0.019526 -0.012548 0.024290 0.009997 0.003779 -0.009966 -0.001504 0.012918 0.013362 0.013461 0.046128 0.033598 0.001728 -0.009655 -0.017078 -0.007987 0.007690 0.006852 0.045499 0.028308 0.016433 -0.005155 -0.019172 0.008029 -0.060281 -0.040124 -0.019064 -0.007363 0.016511 0.020054 0.003081 0.009802 -0.008379 -0.010151 0.019549 0.025594 -0.015855 -0.049885 -0.037246 0.003011 0.004195 -0.030628 -0.040098 -0.015788 0.003042 -0.014677 -0.032621 -0.015110 0.002241 0.013413 -0.028010 0.016819 -0.000159 -0.047618 -0.052564 0.008029 -0.008714 -0.012812 -0.004171 0.012097 0.024351 0.022740 -0.000236 -0.016054 -0.030594 -0.042542 0.024018 0.018536 -0.004481 -0.022988 -0.022122 -0.018418 -0.015874 -0.017961 -0.047271 0.018030 0.027273 0.005620 -0.011869 0.002177 -0.011704 -0.030089 -0.033703 -0.023643 -0.038771 0.015567 -0.007469 0.008036 0.021821 0.008409 0.013731 0.008699 0.000470 0.017747 -0.005851 0.000435 0.009375 0.001407 0.045256 0.008430 -0.002036 -0.014515 -0.020296 -0.007218 0.002222 0.042854 0.028543 0.051027 0.020375 0.002571 -0.017588 0.002258 -0.011783 -0.009832 0.037165 0.018633 0.014342 0.017513 0.011238 0.008036
-0.011511 -0.000495 -0.002528 0.002289 0.032054 0.048676 0.007787 -0.002759 -0.009853 -0.006734 -0.028172 0.006885 -0.006523 0.003769 0.008621 0.012807 -0.008484 -0.004290 -0.009260 -0.024362 0.002935 0.003624 0.025520 0.030521 0.015727 -0.000640 -0.015841 -0.024078 -0.012503 0.027165 0.028996 -0.013392 -0.046769 0.009163 0.028659 0.018022 -0.000317 0.022442 0.004494 -0.012150 -0.009434 -0.008140 0.016952 -0.005799 -0.010358 0.004973 -0.014678 -0.006250 -0.017853 -0.030146 -0.017359 0.007448 0.025631 0.011336 0.008586 -0.004112 -0.001535 -0.026311 -0.032602 -0.032784 -0.041732 0.017792 0.029766 -0.007489 -0.004139 0.023650 0.023603 0.006440 0.013572 0.034124 0.003736 -0.021081 -0.010410 0.015746 0.066367 0.024630 -0.022584 -0.026863 -0.011754 -0.003407 0.031371 0.004269 0.077043 0.057408 0.028583 -0.002549 -0.006569 0.003425 -0.006497 0.000732 0.000313 0.042128 0.024765 0.008293 -0.005763 0.003796 -0.077851 -0.044115 -0.018380 0.021923 0.014038 0.020030 0.012271 -0.000164 -0.011408 -0.018778 0.030358 0.047678 0.011163 -0.020486 -0.030219 -0.006443 -0.004601 -0.031559 -0.057055 -0.005466 0.021967 0.033905 -0.002266 -0.000630 0.005095 -0.003103 -0.041795 0.008559 0.020502 -0.033978 -0.045307 0.003796 0.005984 0.018056 0.006817 0.025890 0.003658 -0.014245 -0.021165 -0.021839 -0.018111 -0.040740 0.041405 0.042993 0.015439 -0.022095 -0.013736 -0.011386 -0.029201 -0.018063 -0.020201 0.051621 0.036746 0.022428 -0.006668 -0.018539 -0.032843 -0.039778 -0.026213 -0.034549 -0.020920 0.010293 0.021446 0.003802 0.020402 0.054415 0.033869 0.000114 0.005699 -0.017334 -0.009341 -0.004285 0.004095 0.006370 0.015033 -0.008707 -0.008159 -0.023387 -0.005691 0.001493 0.017460 0.028174 0.037722 0.066113 0.037380 -0.014381 -0.013800 -0.006217 -0.009703 0.007732 0.039893 0.002345 0.023993 0.003121 0.022498 0.003802
0.002499 0.015223 0.023454 -0.002489 0.038837 0.046754 -0.000383 0.003566 -0.015641 -0.024752 -0.026305 -0.012738 0.005124 0.008266 -0.000547 0.016106 -0.013907 0.008010 -0.022822 -0.016999 0.023521 0.004964 0.045494 0.021059 0.009576 -0.007864 -0.007205 -0.021349 -0.007752 0.019769 0.042838 -0.013393 -0.034770 0.018196 0.016662 0.012974 0.022645 0.013369 0.003364 0.003558 -0.012192 -0.007043 0.035600 0.001031 -0.015645 -0.027463 -0.011533 0.003318 0.002459 -0.025658 -0.017031 0.032257 0.010521 0.004548 0.003383 -0.003695 0.003954 0.000690 -0.033454 -0.015047 -0.025649 0.012321 0.027844 -0.007489 -0.026943 0.031421 -0.018803 0.018310 0.014228 0.001400 0.003009 -0.015476 -0.003642 0.012287 0.064705 0.068269 -0.007152 -0.041244 -0.013910 0.002693 0.022403 -0.017454 0.048675 0.081971 0.031095 0.013423 -0.018986 -0.007058 0.006349 0.006190 -0.005745 0.036660 0.024226 -0.004592 -0.011935 0.003795 -0.074604 -0.026659 -0.035146 0.022901 0.004490 -0.003521 0.005501 -0.013488 -0.033086 -0.029355 -0.001278 0.062023 0.026911 -0.035019 -0.037348 -0.010124 -0.015228 -0.035600 -0.066667 -0.030257 0.032487 0.026421 -0.024011 -0.028361 -0.003414 -0.024527 -0.056280 -0.035662 -0.004591 -0.029973 -0.037551 0.003795 0.035544 0.068660 0.051308 -0.003411 0.005586 -0.026546 -0.012521 -0.006780 -0.022541 -0.025011 -0.002234 0.037208 0.020084 -0.025713 -0.018648 -0.007140 -0.024171 -0.026143 0.027215 0.043376 0.080945 0.007418 -0.020615 -0.040626 -0.017667 -0.024375 -0.031483 -0.042788 -0.010020 0.009014 0.052059 0.003802 0.000952 0.050413 0.018506 -0.015964 0.020706 0.017747 -0.009330 -0.001899 0.001112 0.006856 -0.019100 0.012094 0.002279 -0.008388 -0.004394 0.008267 0.011137 -0.005921 0.035182 0.041211 0.029629 -0.023307 -0.002253 0.008305 -0.000233 0.008256 0.001012 0.002148 0.023940 -0.009842 0.023856 0.003802
-0.017150 0.013633 0.017338 0.002187 0.012307 0.042182 0.004077 0.011590 -0.009323 -0.010912 -0.016245 -0.001666 0.003247 -0.000390 -0.008974 0.007079 -0.010930 -0.010993 -0.016444 -0.006866 0.023962 -0.005465 0.026525 0.027626 0.002879 0.001496 -0.013311 -0.013640 -0.022377 0.028571 0.020200 -0.014962 -0.047901 -0.015045 -0.014958 -0.000935 0.024925 0.022731 0.031119 -0.003315 0.000291 0.005084 0.041387 0.010826 -0.006555 -0.001009 -0.002571 0.010369 -0.005103 -0.008109 -0.001096 0.010325 0.000402 -0.002335 0.017314 0.016833 0.022844 -0.002519 -0.004902 -0.014529 -0.010776 0.023052 0.021689 -0.009058 -0.050913 -0.025421 -0.032543 -0.004008 0.013383 0.012021 0.013636 0.008856 0.008914 0.013995 0.022808 0.031404 -0.002881 -0.002807 -0.012233 0.026709 0.008927 -0.004539 0.039589 0.006704 0.009620 -0.013710 0.014421 0.009154 0.025746 0.014186 0.021802 0.012584 0.030011 -0.017638 -0.013027 0.002226 -0.058911 -0.022694 -0.025368 0.006352 0.005097 -0.011029 -0.016013 0.003739 -0.016321 -0.041068 -0.029908 0.018761 0.036568 -0.007330 -0.017580 0.005313 -0.015643 -0.026126 -0.055028 -0.041532 0.010285 0.028667 -0.004179 -0.010599 -0.009148 -0.012736 -0.038548 -0.048301 -0.015890 -0.026353 -0.009469 0.002226 0.043740 0.050456 0.047649 0.020319 0.006525 -0.006775 -0.010211 -0.010261 0.019415 -0.004091 0.023307 0.019579 0.027997 0.006269 0.010245 0.004886 0.003947 -0.016532 0.037755 0.056521 0.046014 0.029584 0.014423 0.008448 -0.005303 -0.002280 -0.000119 0.006667 0.004463 0.034771 0.065570 0.002233 -0.008293 0.009715 -0.023969 -0.006688 0.016702 0.004314 -0.000400 0.007664 0.025023 -0.033117 0.003488 -0.008620 0.012881 0.005652 0.021603 -0.005958 -0.021427 -0.033323 -0.006052 0.008884 -0.021455 -0.000882 0.019477 0.026674 -0.002527 -0.021601 -0.015789 0.010841 -0.001994 -0.013313 -0.011918 0.002233
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>192</cols>
<dt>d</dt>
<data>
-0.002835 -0.010102 -0.017685 -0.004100 0.002027 -0.012640 -0.002024 -0.004693 -0.017596 -0.014718 -0.005833 0.005636 0.015133 0.013250 0.030174 0.021164 -0.015613 0.012475 0.005615 -0.016297 -0.004675 0.010143 0.016970 0.005842 0.014189 -0.019220 -0.002702 0.004396 -0.007427 0.001709 -0.002439 0.000000 -0.016434 -0.023551 -0.021354 0.011309 0.003362 0.004262 -0.001304 0.013172 -0.000071 -0.021893 -0.013860 0.016286 0.030185 0.025093 0.000508 -0.014540 -0.020011 0.011057 -0.024194 -0.024811 -0.004492 0.023536 0.026685 0.024879 -0.010144 0.004135 0.010954 0.011070 -0.015343 0.003416 -0.007527 0.000000 -0.000441 0.012959 0.015952 0.014290 0.006825 -0.004288 0.025846 -0.001113 0.009217 0.019262 0.013829 0.008847 0.011445 0.010193 -0.018127 -0.017473 -0.009884 0.025427 0.026397 0.024391 0.027921 0.033417 0.018664 0.012577 0.016269 -0.000468 0.021111 0.020920 0.010480 0.021172 0.005300 -0.001155 -0.036584 -0.019697 0.000414 0.010283 0.005815 -0.007865 0.000280 0.030078 0.006801 0.026478 -0.012941 0.002200 0.013697 -0.001432 -0.038691 -0.020005 0.000765 0.017799 0.013021 -0.033576 -0.001842 0.024668 0.013305 -0.022426 -0.010102 0.026401 0.011369 -0.034784 -0.019436 0.024309 0.019255 -0.006192 -0.003438 0.023331 -0.001238 0.018763 0.012741 -0.001433 0.018437 0.017646 0.001188 -0.022846 -0.024749 -0.019885 -0.014388 -0.013041 -0.006628 -0.017941 0.001008 0.020339 0.014397 -0.003186 -0.010856 0.012043 0.011515 0.004063 -0.000804 0.012522 0.025265 -0.027135 -0.011618 0.005722 0.027312 -0.006192 0.019387 0.040190 0.000401 0.011788 0.010121 0.000034 0.008883 0.004252 0.019811 -0.016071 -0.012518 -0.002795 -0.022636 0.009007 0.002950 -0.007732 -0.015967 -0.001963 0.006393 0.034721 0.003608 -0.017107 0.002507 0.010725 -0.000994 0.002084 0.012021 0.006566 0.008720 -0.002467 0.009405 -0.006270
-0.027940 -0.041277 -0.014544 -0.005511 0.021902 0.018286 -0.005446 -0.005076 -0.018954 -0.033834 0.030579 0.001350 -0.008215 -0.024220 0.004712 0.030087 -0.009511 0.003709 -0.033429 -0.018324 -0.011906 0.001237 0.005995 0.029684 0.012058 -0.000076 -0.004396 0.015676 -0.030630 0.004041 -0.028638 0.000000 -0.022218 -0.030859 0.010947 0.016317 0.006349 0.017145 -0.001352 0.009007 0.019280 -0.023462 -0.002968 -0.017812 -0.012309 0.010756 -0.012120 0.003674 0.002220 -0.017819 -0.022760 -0.015821 0.001762 -0.000522 0.009345 0.011758 0.015079 0.016866 -0.004208 0.013146 -0.018783 0.014870 -0.030552 0.000000 -0.046787 -0.021617 0.010437 0.011686 -0.006106 -0.010213 0.007478 0.034092 0.012131 0.026481 0.033096 0.011008 0.020080 -0.009425 -0.018736 0.001114 -0.006759 0.010645 -0.001502 0.017188 0.009352 0.025882 -0.006298 -0.001201 0.011721 0.022967 0.014688 0.008766 0.003487 0.019679 -0.004305 -0.001155 -0.013406 -0.041547 0.006114 -0.007077 -0.018070 -0.014676 -0.008625 0.018223 0.043072 0.011597 -0.004999 0.000254 -0.008948 -0.020328 -0.015555 -0.006372 -0.002663 0.020944 0.032606 -0.035900 -0.000397 -0.013158 -0.030818 -0.016843 -0.003336 0.028397 0.030076 -0.040394 -0.034861 0.027176 0.018823 -0.006192 0.001355 0.016832 -0.001910 0.006351 -0.021751 -0.012780 -0.017461 -0.002056 0.027271 -0.007626 -0.013649 -0.003248 -0.022516 -0.015359 -0.003688 0.002743 0.013373 0.032813 0.007037 0.014123 -0.003899 -0.010195 -0.034456 -0.011476 -0.014072 0.014851 0.027413 -0.007973 -0.023551 0.007691 0.013789 -0.006192 0.025703 0.031174 -0.019276 0.011112 0.017662 0.009250 0.001780 -0.009826 0.014272 0.006853 -0.019090 0.004976 -0.007134 0.017268 0.002737 0.015285 -0.000084 0.018777 0.022191 0.017564 -0.005547 0.002525 0.028339 0.009772 0.012978 -0.005336 0.022567 0.034384 0.009298 0.013818 -0.000253 -0.006270
-0.028994 -0.023000 -0.006675 -0.006815 -0.008459 0.020142 -0.009973 -0.017652 -0.020775 -0.050475 0.005479 0.020574 0.009853 -0.005516 0.014391 0.043884 0.021803 -0.013402 -0.052616 -0.018409 0.012099 0.006652 -0.007824 0.023622 0.020877 0.010680 -0.019400 0.007257 -0.007706 -0.010473 -0.015292 0.000000 -0.015202 0.008024 0.014920 0.015760 -0.005969 -0.006117 -0.007043 -0.023074 -0.014069 -0.019333 -0.000613 0.051845 0.044774 0.006965 -0.001699 0.032865 -0.004866 -0.010921 -0.012372 0.012681 0.052064 0.040675 -0.011128 -0.003266 0.025623 -0.007991 -0.010051 0.011283 -0.000494 0.017597 0.002842 0.000000 -0.040995 0.004170 0.005514 -0.008213 0.001794 -0.008479 -0.004112 0.018288 0.003326 -0.004805 0.005593 0.024344 0.033436 -0.019689 -0.006168 0.009993 -0.008940 -0.001606 -0.011607 0.016981 0.008408 0.012481 -0.020049 -0.010178 0.001763 0.011046 0.005851 -0.029884 0.004471 0.016565 0.010475 -0.001155 0.002135 -0.021664 0.013315 -0.034266 -0.017043 -0.002726 -0.006622 0.019092 0.036858 0.015177 0.017525 -0.023759 0.002033 -0.012600 -0.018673 -0.008201 -0.005926 -0.002017 0.035397 0.002633 -0.006816 -0.024589 -0.023339 -0.003628 -0.016636 0.003319 0.022610 -0.049465 -0.026417 0.006299 0.047257 -0.006192 0.034390 0.002621 -0.007732 -0.014193 0.005722 -0.007330 -0.008138 -0.008284 0.005808 0.003683 -0.004588 -0.023055 -0.017165 -0.000899 -0.013267 0.009440 -0.015560 0.021096 0.049820 0.014025 -0.019976 -0.019685 0.013868 -0.000826 0.000983 -0.017831 0.015257 -0.004454 -0.009685 -0.014889 0.011374 -0.006192 0.025289 0.015998 -0.020428 0.002913 0.009380 0.014551 0.017378 0.015295 -0.010220 0.012321 -0.016232 -0.036568 -0.009160 0.015233 0.016182 0.002506 -0.029519 0.015714 0.014572 0.012277 -0.052844 -0.003634 0.023281 0.030824 0.010634 -0.011115 0.025503 0.037892 0.005756 -0.012221 -0.012272 -0.006270
-0.010888 -0.018699 -0.013754 -0.001391 0.005247 0.001827 0.046173 0.018502 -0.004598 -0.043363 -0.034194 -0.013136 -0.004617 -0.021684 0.008279 0.005142 0.034655 0.026113 -0.027315 -0.042635 -0.013785 -0.003508 0.007109 0.029488 0.047366 0.043178 0.021358 -0.010278 0.017985 -0.013876 -0.003442 0.000000 -0.010588 0.001278 0.011269 0.035766 0.007300 0.001751 -0.013322 -0.010498 -0.009918 -0.026060 -0.033521 0.000228 0.002237 0.026618 0.019845 0.018847 -0.009131 -0.005952 -0.007416 -0.028100 0.018029 0.025218 0.045839 0.032607 0.019225 -0.012170 -0.014802 -0.000608 0.005015 -0.012359 0.010852 0.000000 -0.043827 -0.001323 0.026652 0.024045 0.015320 -0.022146 -0.012239 -0.026785 -0.027677 -0.036226 -0.000330 -0.001770 0.022997 0.014605 0.012662 0.020714 -0.006773 -0.017149 -0.042636 0.005600 0.012825 0.030138 0.041570 0.027887 0.017577 -0.030324 -0.037497 -0.040923 -0.020896 0.016471 0.017419 -0.001155 -0.011872 -0.005687 -0.001611 -0.006456 -0.011086 -0.020222 0.000678 0.015512 0.015220 -0.030227 0.013337 0.001020 0.035280 0.037400 -0.014627 -0.000137 -0.000960 -0.026648 0.017624 0.020150 0.005906 0.028917 0.031800 -0.008212 -0.007295 0.001791 -0.013250 -0.035626 -0.017709 0.006731 0.041378 -0.006192 0.008555 -0.021429 -0.001460 -0.011118 0.016552 0.005607 0.015757 0.012434 0.028082 0.017623 0.018103 -0.003871 0.015370 0.003592 -0.026364 -0.019485 -0.035139 0.007346 0.045164 0.007520 0.007054 0.007800 0.035013 0.007006 0.003954 -0.015176 0.012322 0.004245 0.016688 -0.015026 0.008309 -0.006192 0.004669 0.013307 -0.011347 0.013500 0.021774 0.010500 -0.004610 -0.012270 -0.005696 0.026688 -0.008321 0.006120 -0.009381 -0.002789 0.001272 -0.007000 -0.021710 0.017873 0.006953 -0.005047 -0.000070 0.001027 0.033982 0.023915 -0.000271 -0.023795 0.003861 0.035141 0.031280 -0.028417 -0.022645 -0.006270
-0.007929 0.008727 0.000623 0.005041 0.031998 0.025861 0.042567 0.016907 0.028979 0.013878 0.006069 -0.010913 -0.015176 -0.017448 -0.013271 -0.019007 -0.012386 0.007907 0.006900 0.008263 0.000952 -0.009199 0.021565 0.019488 0.020110 0.014135 0.036907 0.006277 0.016454 0.005268 0.015572 0.005995 -0.003168 0.009840 0.013186 0.034545 0.038053 0.012706 0.028407 0.010736 -0.007722 -0.034826 -0.031044 -0.006716 -0.001954 -0.006571 -0.004634 -0.019287 -0.013001 0.007832 -0.012593 -0.026658 0.009005 0.024481 0.025668 0.010512 0.012298 -0.004129 0.005564 0.012032 0.014907 -0.010579 -0.003923 0.005995 -0.011294 0.007693 0.009529 0.040529 0.017161 -0.016380 -0.031692 -0.032750 -0.029903 -0.055540 -0.041360 -0.043230 -0.029507 -0.012951 -0.001107 -0.001490 -0.017159 0.013868 -0.021724 -0.027394 -0.042547 0.001137 0.002543 -0.006279 -0.022677 -0.036201 0.003741 -0.040916 -0.057925 -0.005431 -0.006783 0.004840 0.011173 -0.000171 -0.012828 0.010283 0.008295 -0.019391 -0.032797 -0.032491 -0.001575 -0.041038 -0.013172 -0.022512 -0.019219 0.015968 -0.022362 -0.020112 -0.003239 0.021950 0.047770 0.012818 -0.032229 -0.011988 0.021694 -0.020176 -0.047808 -0.036569 0.022517 -0.040310 -0.045651 0.007076 -0.002780 -0.000197 0.001784 0.012500 0.000847 0.027335 0.020322 0.023741 0.001609 0.012071 0.027908 0.010419 0.009510 0.012852 -0.006469 0.019937 -0.006645 -0.006886 -0.003413 0.015666 0.050185 0.021597 0.014929 0.023285 0.022956 0.009390 -0.011095 0.006041 0.027716 0.018487 0.033558 0.014881 0.014667 -0.000197 -0.016013 0.014014 0.003099 0.013834 0.026825 0.021446 -0.004369 -0.006662 0.002051 0.018151 0.010176 0.044730 0.030430 0.011044 0.009780 0.001231 -0.018080 -0.027401 0.004017 0.033817 0.030050 0.039555 0.035121 0.025309 -0.006325 -0.033531 -0.014546 0.055329 0.051431 -0.027430 -0.016028 -0.000275
0.015551 0.022803 0.002399 0.013462 0.011296 -0.004827 0.004213 -0.004314 0.068995 0.036270 0.037902 -0.016508 -0.012766 -0.009565 -0.023125 -0.026586 -0.015656 0.003493 0.027985 0.042949 -0.002808 -0.000885 -0.023868 -0.030620 -0.018710 -0.012652 0.057767 -0.001911 0.015595 0.018962 0.015927 0.003956 -0.003268 0.027062 0.011831 0.032117 0.032577 0.011605 0.016577 -0.001266 0.032725 -0.003935 0.010651 -0.009359 -0.031016 -0.034453 -0.038172 -0.018494 -0.007810 0.036973 0.005168 0.032130 0.008234 -0.004778 -0.010838 -0.028098 -0.007632 -0.004539 0.052894 0.011212 0.034750 -0.018861 0.003232 0.003956 -0.033896 0.008044 0.005847 0.016832 -0.005945 -0.028620 -0.023378 -0.017998 -0.035801 -0.070161 -0.022822 -0.035822 -0.046564 -0.037653 -0.031095 -0.005328 0.007753 0.018637 -0.039887 -0.025036 -0.036091 -0.031367 -0.042976 -0.051373 -0.032426 -0.012177 -0.001195 -0.042213 -0.062045 -0.034064 -0.020997 0.002801 0.026835 0.048677 -0.002190 0.012322 -0.005131 -0.037501 -0.034595 -0.030098 -0.022331 -0.038679 -0.013200 -0.025793 -0.035479 -0.026729 -0.032744 0.008237 -0.003697 0.040387 0.047008 0.042368 -0.030354 -0.035597 -0.031992 -0.049282 -0.029542 -0.035469 0.004114 -0.038145 -0.049157 0.013311 -0.006953 -0.002236 -0.022521 0.006343 -0.019929 -0.007486 -0.005537 0.008653 -0.004824 0.035927 0.015975 0.010573 -0.002851 -0.021185 0.011428 0.029572 0.013229 0.010827 0.016257 0.006685 0.031518 0.012467 -0.035045 -0.003406 0.015210 0.008597 0.005588 0.029623 0.026513 0.015146 0.004504 0.016581 0.002017 -0.002236 -0.060006 -0.037814 -0.034503 -0.023268 0.014574 0.045957 0.023916 0.004663 -0.013258 0.007540 0.009103 -0.003820 0.014642 0.034944 0.033370 0.006771 0.008058 -0.031091 -0.034114 -0.027049 -0.037090 -0.003921 0.039689 0.046902 0.028233 0.007613 -0.038653 0.038747 0.032328 -0.027336 -0.043843 -0.002314
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>192</cols>
<dt>d</dt>
<data>
-0.032399 -0.006572 -0.007588 -0.042167 -0.009128 0.014523 0.034144 0.015545 0.006977 -0.007082 0.004368 0.026201 0.006338 -0.008541 -0.009630 0.006254 0.013832 0.026168 -0.017670 -0.015435 0.015944 0.005226 -0.004971 0.001188 0.028021 0.035114 0.017770 0.025936 -0.018230 0.020120 -0.013098 -0.000000 -0.027176 -0.017319 0.011645 -0.011187 -0.033380 -0.003488 -0.000143 0.007458 -0.041079 -0.038859 -0.011253 -0.003357 -0.005650 0.006838 0.011418 0.009403 0.009893 0.027492 -0.046410 -0.037067 0.006424 -0.004486 -0.000179 0.007694 0.024006 0.009383 -0.011391 0.020301 -0.041510 0.003579 -0.033632 -0.000000 -0.012297 0.007502 0.015163 0.004723 -0.028669 -0.019671 -0.033930 -0.017142 -0.025764 -0.040201 -0.005914 -0.007005 0.042039 -0.000439 0.015415 0.013522 -0.002348 0.005895 -0.031441 -0.002046 0.026544 0.036794 -0.001928 0.002754 0.005104 -0.010039 -0.015902 0.014709 -0.055966 0.036970 -0.037726 -0.000636 0.012754 0.022374 0.017377 -0.008421 -0.028393 0.003681 0.044345 0.004262 -0.008696 -0.042917 -0.042673 -0.019128 -0.006419 0.006720 0.008975 0.036813 0.030234 0.040836 0.002410 -0.015550 0.005113 -0.006739 0.000820 0.017123 0.074531 0.039351 0.028797 0.007029 -0.011674 0.060659 -0.022202 -0.001161 -0.014824 -0.015040 0.006595 0.010418 -0.013568 -0.002675 0.022956 0.059139 0.059540 0.005827 -0.006301 -0.015309 -0.024901 0.001173 0.036740 0.039450 0.013571 -0.007062 0.038383 -0.018852 -0.008175 -0.017263 -0.002190 0.036501 0.068857 0.105286 0.071478 0.006982 0.027959 0.028350 0.010120 -0.001176 0.002341 0.000009 0.016592 0.021270 0.018740 -0.017671 -0.026041 -0.005443 0.003379 -0.003016 -0.001668 -0.007026 0.004447 0.005414 0.012767 0.001100 -0.027341 -0.049243 0.009821 -0.012158 0.008034 0.021808 0.027024 0.004609 -0.008513 -0.012555 -0.023277 0.004482 0.013987 -0.027938 -0.014757 -0.001176
-0.028325 0.008240 0.001582 -0.038409 -0.012531 -0.010285 -0.007318 0.011957 -0.010632 -0.016939 0.002899 -0.005177 -0.000181 -0.009086 0.008777 -0.004890 -0.014474 0.029898 -0.017280 -0.006808 -0.000139 -0.025235 -0.015612 -0.008508 -0.008396 0.012419 -0.011753 0.002099 -0.033079 0.013838 -0.027591 -0.000000 -0.035407 -0.024169 0.014308 -0.002781 -0.007838 -0.035488 -0.038753 -0.006806 -0.007074 0.003515 0.008661 0.004549 0.024269 0.018582 0.010085 0.025890 0.009729 0.011177 -0.023707 -0.027034 0.017164 0.020549 0.011916 -0.019747 -0.014027 0.024066 0.005806 0.014283 -0.008398 0.006252 -0.025124 -0.000000 -0.005965 -0.015817 0.013789 0.002008 -0.029200 -0.014904 -0.033794 -0.039351 -0.038901 -0.028215 0.012267 0.026314 0.034054 0.050078 -0.014515 -0.006533 0.009592 -0.005812 -0.015406 -0.008528 0.032805 0.019142 0.015991 -0.018562 -0.035540 -0.022281 -0.046238 0.026430 -0.037619 -0.003503 -0.025331 -0.000636 -0.029153 -0.033241 -0.000371 -0.027648 -0.030273 -0.046590 -0.061399 -0.043909 -0.048225 -0.047110 0.003998 -0.009916 0.022021 -0.002159 0.010649 0.007905 -0.010331 0.012186 -0.039617 -0.031633 -0.019711 -0.009077 -0.025054 -0.030336 -0.045175 -0.047129 -0.031910 -0.037521 -0.078246 0.007776 -0.049252 -0.001161 -0.014422 -0.022364 0.003471 -0.020769 -0.030569 -0.043991 -0.009868 0.055455 0.064823 0.007152 0.002051 -0.037462 -0.012356 -0.027293 0.006986 0.035248 -0.001187 0.049675 0.037660 -0.021842 -0.030471 -0.023165 -0.049127 -0.023485 0.032741 0.065648 0.083755 -0.017148 -0.018290 0.046803 -0.009207 -0.001176 0.003361 0.018740 0.014322 0.005789 0.029459 -0.016952 -0.017766 0.024028 0.045288 0.032858 -0.027180 -0.030273 -0.021592 0.005634 0.013795 -0.011034 -0.001320 0.011556 0.039428 -0.014419 -0.018325 -0.011996 0.026526 -0.005220 -0.009194 0.049362 0.065033 0.009553 0.035514 -0.000790 -0.007171 -0.001176
0.013290 0.023735 -0.015241 -0.029245 0.013905 0.032737 0.008790 0.002723 0.001608 -0.010352 -0.011075 -0.019882 0.002527 -0.009530 0.012797 -0.012855 0.001784 0.038911 -0.001186 -0.003828 -0.022778 -0.020537 0.004088 0.037163 -0.010923 0.001567 0.017612 0.007168 -0.016893 0.042012 -0.011250 -0.000000 -0.020812 -0.007861 -0.012627 -0.021599 0.018621 0.036462 0.018173 -0.017885 -0.003977 -0.010635 0.000887 0.019871 0.018762 0.013507 0.034433 0.015629 -0.000099 0.012407 -0.021386 -0.021475 0.004477 0.001501 0.018886 0.043410 0.015904 0.012316 0.011614 0.013830 0.008073 0.025206 -0.003148 -0.000000 -0.018777 0.002766 0.013348 -0.011177 0.000461 -0.005558 -0.007346 0.002417 -0.008071 0.008418 0.025830 0.033395 0.034832 0.020981 0.022729 0.008732 -0.024987 -0.001823 0.000437 0.012578 0.018136 0.016126 0.020928 0.011083 -0.000776 -0.014344 -0.018781 0.027632 0.024940 -0.004443 -0.002792 -0.000636 -0.028280 -0.008934 0.006168 -0.019613 -0.026470 -0.048304 -0.040978 -0.008647 -0.026640 -0.015526 0.053113 0.043066 0.029389 -0.010361 0.003889 0.011361 -0.014036 0.001997 -0.017952 0.026894 0.022199 0.011425 -0.036196 -0.031375 -0.020386 -0.028197 -0.027450 -0.012475 -0.039597 0.002945 0.002551 -0.001161 -0.016695 -0.002220 -0.004825 -0.027193 -0.030476 -0.047148 -0.041760 -0.023884 0.032232 -0.014898 -0.008983 -0.005220 0.000982 -0.037608 -0.020498 0.004188 0.001553 0.026342 0.019253 -0.018643 -0.017862 -0.022347 -0.068217 -0.061441 -0.031681 0.002145 0.032649 -0.055784 -0.061205 0.021038 -0.005924 -0.001176 -0.012568 -0.006490 0.004785 0.002073 0.008782 -0.010387 -0.025431 0.013583 0.066238 0.021379 -0.003794 0.005815 -0.012570 -0.009337 -0.011581 -0.007018 0.019739 0.010615 0.052760 -0.006265 0.005528 -0.005327 0.002290 -0.015089 -0.015426 0.042404 0.077709 0.007101 0.008569 0.011743 -0.002036 -0.001176
-0.009685 -0.011728 -0.004701 0.000167 0.002800 0.002594 -0.024240 -0.022400 -0.004118 0.003074 0.026726 0.007269 0.004890 0.001290 0.011215 -0.016808 -0.010900 0.021282 0.009101 0.010401 0.006590 -0.011875 -0.020204 0.005610 -0.032981 -0.015400 0.010446 -0.006423 -0.026530 0.013817 0.008163 -0.000000 -0.011908 -0.020927 -0.027355 -0.017922 -0.013256 -0.000062 -0.015034 0.005901 0.012294 0.002643 0.021357 -0.002606 0.037765 0.007816 0.004831 -0.011380 0.008215 0.031255 0.015496 -0.010658 -0.009548 0.003670 -0.023754 0.000438 -0.011343 0.034117 0.007211 0.002847 -0.014988 0.019466 -0.001844 -0.000000 -0.033802 -0.005400 -0.016626 -0.020687 -0.013009 -0.039712 -0.007850 0.029021 0.036418 0.018520 0.027681 0.008384 0.023556 0.004210 0.006182 -0.009710 -0.029446 -0.010397 -0.005942 -0.016136 -0.008215 0.007867 -0.021181 -0.030873 -0.013667 0.008471 0.008516 -0.012530 0.011174 0.002706 -0.016750 -0.000636 -0.020360 -0.017844 -0.020123 -0.019089 -0.008048 -0.023024 -0.021627 -0.014782 0.002859 0.035934 0.047340 0.038902 0.017693 -0.003172 0.001801 -0.013234 0.001234 0.027471 0.013189 0.030895 -0.001099 0.008702 -0.015258 -0.016673 -0.031234 -0.006482 0.004445 -0.008710 0.001407 -0.007780 0.020708 -0.001161 0.006164 0.016515 -0.001552 -0.009044 0.007875 -0.008645 -0.018296 -0.039582 -0.019007 -0.030593 -0.028634 0.009454 -0.006188 -0.017398 -0.023531 -0.005330 -0.001429 0.019785 0.003914 -0.011479 -0.002961 -0.017903 -0.022451 -0.029175 -0.016716 -0.022930 0.005367 -0.039956 -0.056167 0.007715 0.017964 -0.001176 0.000939 -0.014206 -0.012207 -0.011143 0.005255 0.004867 -0.022847 0.021238 0.050434 -0.005870 0.003816 -0.009159 0.000971 -0.003703 -0.014116 0.002818 0.004433 0.028410 0.048348 0.006428 -0.002932 -0.002910 -0.000812 -0.003980 -0.007356 0.035025 0.071989 -0.001164 -0.006835 0.022560 -0.000452 -0.001176
-0.040369 -0.006190 -0.005988 0.021820 0.026978 0.013945 0.004713 -0.012940 -0.007571 -0.010673 0.017339 0.014559 0.009440 0.023199 0.030311 0.013751 -0.006393 0.007536 -0.018962 -0.012724 -0.001119 0.018767 0.015512 0.019987 0.014813 -0.009439 -0.012190 0.023921 -0.005640 0.008706 0.017073 -0.000000 -0.013842 0.003971 -0.002388 -0.015643 -0.019216 -0.002779 -0.005874 -0.013968 0.004934 -0.000595 0.023106 0.015276 0.031794 0.020846 0.016850 0.001501 0.000322 0.010791 0.000121 0.019426 0.008102 0.005201 0.000842 -0.004875 -0.000459 -0.017033 0.007231 0.002129 -0.012033 0.026954 0.008918 -0.000000 -0.003893 0.014849 0.014283 0.006933 -0.004202 -0.009079 -0.004392 0.009198 0.042687 0.003779 0.036053 -0.001289 0.015002 -0.012570 0.014215 -0.021563 -0.018234 -0.009548 0.013064 0.020499 -0.006593 0.024468 -0.022251 -0.000171 -0.010688 -0.006478 0.018316 -0.009713 -0.006437 0.034453 0.015746 -0.000636 -0.011134 -0.010357 -0.018400 0.018268 -0.001176 -0.015152 -0.000300 -0.004680 0.024396 0.049144 0.056615 0.005154 -0.025112 -0.027869 0.025573 -0.014365 0.003352 -0.003154 0.040878 0.044025 -0.006716 -0.003245 -0.027470 0.003089 -0.024054 0.009969 0.014975 -0.010131 0.009064 0.009328 0.015688 -0.001161 -0.021110 0.009718 -0.016085 0.027246 0.009633 -0.015257 -0.000868 -0.017531 -0.015323 -0.019503 0.000494 0.011625 -0.011241 -0.021645 0.005610 0.002011 0.024500 0.003333 -0.019672 -0.005702 -0.010294 0.006458 -0.009417 -0.011076 -0.010059 0.009677 -0.006304 -0.008891 -0.025498 -0.002358 0.015820 -0.001176 0.005468 -0.012654 -0.006204 -0.001139 0.007688 0.013331 -0.012398 -0.035670 0.039702 -0.010329 -0.005622 0.030418 0.020577 0.008032 -0.024580 -0.019752 -0.013242 0.008666 0.030737 0.010730 0.014201 0.018224 0.013395 -0.005317 -0.012894 -0.031645 0.047154 -0.000509 -0.019523 0.018106 -0.001708 -0.001176
-0.007967 -0.014081 -0.015491 -0.013378 0.007256 0.016140 0.017866 -0.010535 0.021725 -0.004238 0.021324 0.018218 -0.004845 -0.022408 -0.023216 -0.009340 0.014793 0.018551 0.018310 0.002112 -0.007330 -0.017674 -0.005189 -0.020202 0.009886 0.007771 0.013883 0.013113 -0.004582 -0.003826 0.000187 -0.000000 -0.017401 -0.006502 -0.011116 -0.002889 -0.000161 0.013832 0.028184 0.011731 -0.003147 -0.045404 -0.006141 0.020744 0.022545 -0.000806 -0.013136 -0.015796 -0.001620 -0.000858 -0.034938 -0.010168 0.001183 0.009870 0.002279 0.007126 0.007700 0.002900 0.002866 -0.007144 -0.020776 0.012533 0.002217 -0.000000 0.009790 -0.003301 0.001222 -0.023249 -0.012638 0.019052 0.022173 0.017335 0.031695 -0.018071 -0.002639 0.027598 0.016422 -0.006959 -0.025219 -0.012547 -0.000635 -0.025169 0.011526 0.015690 0.026378 -0.008429 -0.028525 -0.015890 0.008220 0.000547 0.013903 -0.026841 -0.020989 0.033922 0.020914 -0.000636 -0.002497 0.005572 0.004125 -0.009569 -0.001393 -0.008651 -0.020429 0.038576 0.054654 0.038153 -0.022445 0.000734 -0.017703 -0.001035 0.009923 -0.004441 0.003044 -0.005170 0.037325 0.000374 0.006254 -0.025271 0.001824 0.004558 -0.021481 0.039386 0.039303 -0.008896 -0.002238 0.017432 0.022668 -0.001161 -0.017389 -0.013155 -0.007049 0.016363 0.007497 0.000188 -0.016915 0.006874 -0.010968 -0.010152 -0.009086 -0.009083 0.002642 0.005921 0.037069 0.027175 0.013723 0.009187 -0.015566 -0.024936 -0.016238 0.015274 0.019389 0.026511 0.003990 0.026989 -0.004105 0.006104 0.003735 -0.004363 0.010005 -0.001176 -0.002305 0.009852 0.012123 0.005634 -0.011660 -0.003301 -0.033986 -0.014551 -0.037517 -0.015428 0.002568 0.005188 0.024740 0.046255 0.034421 0.027315 0.001002 0.021972 0.017023 0.012822 0.016664 0.030302 0.021157 0.023358 -0.000840 -0.009062 0.016202 0.013665 -0.004408 0.017007 0.007829 -0.001176
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>192</cols>
<dt>d</dt>
<data>
-0.013129 -0.008701 -0.014452 -0.008913 -0.006485 -0.020601 -0.014373 -0.004936 0.005500 -0.021969 -0.003063 -0.005439 -0.010178 0.027659 0.035017 -0.008737 0.000592 -0.005133 0.003311 -0.011842 -0.017995 -0.015161 0.008370 0.020842 -0.015413 0.007875 -0.004657 0.000860 -0.009615 -0.000237 -0.027467 -0.000016 -0.005525 0.058052 0.014757 -0.019465 -0.021809 -0.007451 0.014249 -0.013811 0.006968 -0.013573 0.000399 0.032908 0.012330 -0.000777 -0.012751 -0.015220 -0.004448 -0.006084 0.019834 0.053228 0.029373 -0.008820 -0.015146 -0.000446 0.011933 -0.005888 0.005471 0.033612 0.020458 -0.017273 -0.027958 -0.000007 0.011283 0.054733 0.023154 -0.007931 -0.003681 -0.000799 0.021262 0.013343 0.002922 -0.022384 -0.001824 -0.000467 -0.009453 -0.013819 -0.017324 -0.002697 0.011478 0.000196 0.003433 0.040594 0.031279 -0.013649 -0.014225 -0.024341 0.014912 0.025069 0.008121 0.017451 0.006481 0.006293 -0.002887 -0.000007 -0.045289 -0.011365 -0.006588 0.016380 0.009254 0.018593 -0.004984 -0.012478 -0.003813 -0.025730 0.009790 0.018920 0.015824 -0.005930 -0.012538 -0.005597 0.006567 0.002202 -0.034794 -0.000775 0.015255 0.019723 -0.002542 -0.012971 -0.011517 0.000292 0.000344 -0.000268 -0.009945 0.001009 -0.008135 -0.000007 -0.030531 -0.006097 -0.005218 -0.008030 -0.005595 0.017911 -0.000506 -0.032154 0.002988 0.012685 0.004717 -0.008406 -0.033407 -0.003541 0.013415 0.000255 0.015767 0.022805 0.008432 0.006724 -0.014305 -0.039264 -0.011230 -0.002290 -0.007169 -0.022839 0.008964 -0.003154 0.000070 -0.007042 -0.010116 -0.000003 -0.020005 0.002204 -0.011726 -0.019403 -0.014803 -0.013230 0.008348 0.006416 0.006290 -0.010258 -0.013930 0.009392 0.010811 -0.005807 0.006054 -0.002057 -0.009860 0.016211 -0.011252 -0.009466 -0.005395 -0.006855 -0.043854 -0.010355 0.003068 -0.000941 -0.000494 -0.004201 -0.007658 -0.005520 -0.008714 0.000000
0.011073 0.016938 0.000463 -0.003525 0.011047 0.000078 -0.023483 -0.016372 0.001387 -0.009529 -0.012761 0.004327 -0.004307 -0.008813 -0.008212 -0.009992 -0.000656 -0.008020 0.039689 0.001961 -0.001998 -0.010363 0.016018 0.004092 -0.030011 -0.012636 -0.004644 -0.018512 -0.005106 0.003642 -0.008476 -0.000016 -0.006359 0.066405 0.022241 -0.019173 -0.018524 -0.019667 -0.015877 -0.027075 0.003880 -0.020539 0.018777 0.009139 -0.007012 -0.017785 -0.019321 -0.023716 -0.019307 -0.032892 0.021916 0.070701 0.036370 -0.016034 -0.021833 -0.022981 -0.030982 -0.034673 -0.020887 -0.002606 0.016754 -0.043537 -0.030388 -0.000007 0.000754 0.014663 -0.010654 -0.012299 -0.002142 -0.002606 0.026277 0.004693 0.010444 -0.037224 0.010590 -0.012846 -0.011359 -0.046699 -0.005785 0.006177 0.033983 0.000746 -0.017930 0.019030 -0.013699 -0.025176 -0.032428 0.000092 0.018338 0.041435 0.013045 -0.003054 0.007950 -0.017417 -0.003170 -0.000007 -0.013477 -0.014433 -0.006494 -0.007202 0.033343 0.042078 0.032178 0.027520 0.010500 -0.029628 -0.014249 0.007708 -0.012632 -0.012355 -0.004270 0.015634 0.006209 -0.012382 -0.025495 -0.021725 -0.013343 -0.021238 0.013866 0.021367 0.031280 0.018479 0.017908 0.011301 0.004129 0.001928 0.005291 -0.000007 0.004127 -0.009338 0.004880 0.021417 0.001178 0.034518 0.024723 -0.001364 -0.001966 -0.012229 -0.010094 0.000479 -0.016785 0.012739 0.004887 -0.014115 -0.010852 0.010945 0.021404 -0.020220 0.002465 -0.002409 0.010485 0.024842 -0.003661 -0.020053 0.011173 0.012336 0.002160 0.005394 0.000450 -0.000003 -0.016928 -0.003055 -0.002332 0.003207 -0.014059 -0.011819 0.010517 0.013914 -0.002087 0.004032 -0.000060 0.016409 0.035465 0.028662 0.019576 0.027606 -0.023557 0.001743 0.004934 -0.001476 0.004585 0.029816 0.029964 0.011722 0.019074 -0.000639 -0.007077 0.010065 0.006524 0.015396 0.009137 0.000000
0.040854 0.038791 -0.014128 -0.004258 0.038394 0.031493 0.001846 -0.023086 0.014822 0.013095 -0.006406 -0.009549 -0.016262 -0.025211 -0.021547 -0.021249 0.011388 0.002152 0.044553 0.025047 -0.009907 -0.013404 0.020563 0.009631 -0.020537 -0.016217 0.031828 -0.012888 0.002012 0.017134 0.017851 -0.000016 -0.004744 0.049500 0.002976 -0.007564 -0.001433 0.013380 0.020512 0.005169 0.006753 0.014897 0.017913 -0.020635 -0.018958 -0.021768 -0.016653 -0.017115 0.012776 -0.007298 0.043907 0.037499 -0.021660 -0.021652 -0.008704 0.012295 0.013217 0.008826 -0.004404 0.005757 0.037350 -0.020020 -0.010026 -0.000007 -0.034980 -0.014770 0.012197 0.015973 0.009238 0.002383 -0.003017 -0.009050 -0.018851 -0.030939 0.006822 -0.000561 -0.007342 -0.027492 -0.008672 0.014903 0.009549 -0.018697 -0.044531 -0.009702 0.001834 0.002101 -0.017797 0.007290 -0.006752 -0.001281 -0.026880 -0.015615 0.003079 -0.030333 -0.005830 -0.000007 -0.013726 -0.023679 0.009590 -0.000433 0.021194 0.024393 -0.013439 0.012057 -0.011138 -0.023597 0.003341 0.005720 -0.005358 -0.020987 -0.015160 0.029931 0.001402 -0.005560 -0.016125 -0.009767 0.012900 -0.007236 -0.009909 0.003812 0.020035 0.019274 -0.005331 -0.010348 0.006093 -0.011752 0.004011 -0.000007 -0.031379 -0.022550 0.001187 -0.012968 0.008084 0.003757 0.004533 0.011585 -0.000230 -0.002458 -0.001334 0.003899 0.011194 0.004744 0.009881 0.007836 0.003034 0.001834 0.004881 -0.023780 0.009629 -0.005196 0.014864 -0.002893 0.019313 0.024852 0.003142 -0.011118 0.011609 -0.007703 0.007519 -0.000003 -0.005616 -0.001176 -0.010244 -0.019287 0.008405 -0.013599 0.026525 0.009487 -0.002299 -0.012876 -0.011774 0.006105 0.029968 -0.002397 -0.010252 -0.011821 -0.012284 -0.006172 0.001560 0.001976 0.004224 0.016722 0.011510 -0.017852 0.006213 -0.011008 -0.008494 -0.017284 0.006536 -0.022484 0.014702 0.000000
0.038692 0.025866 0.001324 0.009491 0.020401 -0.001345 -0.017904 -0.008035 0.020385 0.031451 0.008985 -0.007934 -0.001988 -0.014058 -0.034061 0.003363 0.041538 0.013162 0.075795 0.058481 -0.005047 0.000876 0.011201 -0.013791 -0.016357 0.033983 0.042920 -0.009936 0.007588 0.027392 0.035923 -0.000016 -0.004677 0.033602 0.002767 -0.015409 -0.020139 0.014126 0.014167 0.010590 0.017669 -0.004683 0.007150 -0.014406 -0.008376 0.003061 -0.012409 0.010704 0.000374 -0.012840 0.044456 0.026967 -0.004978 -0.019009 0.005181 0.030232 0.020058 0.023833 0.024400 0.002493 0.030473 -0.017970 -0.004970 -0.000007 -0.013474 -0.010142 -0.019751 0.009809 0.001831 0.012756 0.031984 -0.023016 -0.026850 -0.024639 -0.005015 -0.016965 -0.008284 0.000977 -0.014039 0.003280 -0.019180 -0.014683 -0.042051 -0.014960 -0.035161 0.002164 0.032395 0.031117 0.021116 -0.045933 -0.027868 0.005087 -0.001549 -0.040853 -0.026513 -0.000007 -0.021040 -0.015304 -0.009527 0.015812 0.017860 0.026485 0.033728 -0.024638 -0.041526 -0.042204 -0.005799 0.026122 -0.001524 -0.003545 0.009305 0.024571 -0.006351 -0.003282 -0.041244 -0.010385 0.019204 0.030172 0.031783 0.055553 0.036667 -0.014147 -0.031222 0.014439 -0.010946 -0.002587 -0.010739 -0.000007 -0.032561 -0.006359 -0.006495 0.011552 -0.005213 0.011353 0.009925 -0.020842 -0.028890 -0.034584 -0.012244 0.005913 0.004703 0.009034 0.016352 0.009094 -0.006422 0.002586 -0.040546 -0.010989 -0.006324 0.031000 0.010805 0.033520 0.024131 -0.013251 -0.006291 0.005743 -0.023923 0.005467 -0.021746 -0.000003 -0.022829 0.012128 0.010492 0.011149 0.011723 0.000453 0.009662 -0.016800 -0.003744 -0.005414 -0.019086 0.014769 0.032963 0.026649 0.007346 -0.002086 -0.006485 0.001147 -0.010267 -0.004863 0.009263 0.031167 0.041467 0.046311 0.021184 -0.023148 0.005549 0.015268 -0.000301 0.024639 -0.010363 0.000000
0.022393 -0.011638 -0.003720 0.006426 0.008240 0.013131 -0.008614 0.018118 0.037198 0.033082 0.006464 -0.014278 0.010363 0.015465 0.024743 0.018003 0.032094 0.025151 0.060451 0.009303 -0.013938 0.004201 0.013118 0.019214 0.003369 0.037597 0.062133 0.009631 0.002626 0.054059 0.043343 -0.000016 0.012980 0.022991 0.018026 -0.002858 0.024361 -0.003182 0.010633 0.010646 0.018891 0.006291 -0.013627 -0.004435 0.011544 0.009026 0.022589 0.028560 0.006482 -0.000899 0.060227 0.020524 0.019206 0.015268 0.035724 0.030620 0.037208 0.025302 0.032626 0.031174 0.034433 0.011151 0.007160 -0.000007 -0.021422 -0.004830 -0.017596 -0.013561 0.001598 0.020526 0.047888 0.009093 -0.005166 -0.021082 -0.010302 0.002657 -0.001246 0.000405 0.021773 -0.021414 -0.017184 -0.021401 -0.018852 -0.009596 -0.015847 -0.007987 0.003350 0.035799 0.031592 -0.008471 -0.022496 0.020943 0.015566 -0.027156 -0.033519 -0.000007 0.006852 -0.000892 -0.030112 -0.027326 -0.023956 0.000852 0.041043 0.016190 -0.000852 -0.028947 0.021263 0.000559 -0.004377 -0.014765 0.000744 -0.000476 0.009027 0.000682 -0.006169 0.007637 -0.019170 -0.025079 -0.010293 0.024676 0.040153 0.022464 0.005737 0.006626 0.003279 -0.011853 -0.014310 -0.000007 -0.028442 -0.035896 -0.016237 0.007254 -0.010719 -0.031545 0.017309 -0.014230 0.006684 -0.007631 0.008976 -0.004207 -0.003156 0.006624 0.019707 0.011287 -0.014961 -0.010921 -0.014033 -0.016847 -0.010407 -0.000186 0.007098 0.018003 0.022032 -0.015451 0.007123 -0.010578 -0.015500 -0.008890 -0.012221 -0.000003 0.001881 -0.006090 0.025593 0.023951 -0.003458 -0.026994 -0.019428 -0.030791 -0.004970 -0.015216 -0.024856 -0.019873 -0.002874 0.026170 0.041382 0.034037 0.008926 -0.011899 -0.006243 -0.021080 0.004743 0.014365 0.031399 0.039013 0.019123 -0.008573 -0.005894 -0.009271 -0.001701 0.000990 0.007856 0.000000
-0.022006 -0.004303 0.012256 0.007974 0.029175 0.004700 -0.018593 -0.030724 0.011198 -0.021717 -0.022060 -0.014361 0.026497 0.036934 0.043806 0.019063 -0.006098 -0.003211 -0.001406 -0.015856 0.000420 0.036151 0.064021 0.051192 0.008479 -0.035518 0.004655 -0.007822 -0.022511 0.037785 0.015425 -0.000962 0.024290 0.024807 0.015225 -0.013496 0.003921 -0.018318 -0.006000 0.007024 0.046625 -0.000436 -0.012272 -0.000851 -0.008209 -0.019581 -0.023504 -0.025465 -0.017883 0.012918 0.052054 0.004646 0.016912 -0.018321 0.006170 -0.024504 -0.023832 0.009643 0.070098 0.004521 0.009039 -0.003527 -0.015315 -0.000952 -0.005638 -0.038407 -0.046134 -0.028261 -0.023417 -0.019151 -0.001728 0.023053 0.016875 -0.024738 0.001564 -0.000881 -0.022452 -0.025470 -0.024020 -0.025193 -0.016371 -0.023504 0.003103 -0.032417 -0.050318 -0.041796 -0.039755 -0.033854 -0.020056 0.019779 0.008682 -0.001998 -0.014108 -0.057298 -0.060413 -0.000952 -0.052721 -0.034290 -0.028468 -0.016540 -0.003856 -0.004754 0.009486 0.000745 -0.019643 -0.009750 0.026498 0.014235 -0.001682 -0.015864 0.006893 -0.003049 -0.003107 0.008275 -0.025606 -0.024051 -0.007422 -0.023225 -0.012539 -0.000458 0.012686 0.001904 -0.011874 0.006674 -0.018924 -0.014921 -0.032976 -0.000952 -0.031841 0.004235 0.007823 0.030794 0.012370 0.012847 -0.014774 0.003413 0.011037 -0.002279 0.015893 -0.021099 -0.000002 -0.015854 0.022422 0.000517 0.003873 0.011376 -0.004351 0.009176 -0.002920 0.017645 0.011043 0.038487 -0.013059 0.004718 0.027874 0.004233 0.002758 0.012304 0.004630 -0.000949 -0.010254 -0.001974 0.043206 0.033083 0.006454 -0.000442 -0.038671 -0.001485 -0.005425 -0.030836 -0.001144 -0.052299 -0.017407 -0.000376 0.034380 0.018693 0.012629 0.018494 -0.016222 -0.014535 -0.000605 0.001153 0.005854 0.024219 -0.018142 -0.000111 0.014761 0.002046 -0.002788 0.003010 0.000856 -0.000946
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>192</cols>
<dt>d</dt>
<data>
-0.021592 -0.005483 0.013379 0.023275 0.019080 0.053307 0.002025 0.006907 -0.002632 0.006926 -0.027057 0.014158 0.012114 0.038066 0.017105 0.045270 -0.007544 -0.007352 -0.002619 -0.024162 0.037709 0.019797 0.038838 0.045256 0.036257 0.002344 -0.007514 0.014579 -0.011500 0.053676 0.028074 0.010409 -0.026901 -0.010680 0.001520 0.005313 0.013906 0.043862 0.001255 0.002806 0.001974 -0.001144 -0.026983 0.008553 0.011111 0.032076 0.011946 0.020297 0.015020 0.015556 -0.009412 -0.024674 0.011381 0.016472 0.046679 0.050320 0.017972 0.016730 0.009181 -0.010726 -0.019489 0.059484 0.027058 0.010409 0.007597 -0.001462 -0.003684 -0.011307 -0.010548 0.001286 0.001219 -0.002351 0.021357 0.018340 -0.012727 -0.007118 -0.015762 0.008443 -0.022348 -0.018006 -0.011254 0.003010 0.072365 -0.010054 -0.015775 -0.024755 -0.009585 -0.012279 -0.014514 -0.005881 0.034784 0.001316 0.007951 -0.013323 -0.022019 0.019800 -0.025374 -0.030193 -0.022177 -0.022869 -0.026544 -0.034393 -0.012200 -0.023007 -0.008552 -0.005940 0.009540 -0.002807 -0.033923 0.007743 -0.007426 0.004768 -0.003690 -0.004548 0.003775 -0.009258 -0.028626 -0.047192 -0.017869 -0.038303 -0.003889 -0.029048 -0.004865 -0.021653 -0.005203 -0.045847 -0.041182 0.019800 -0.033695 0.010666 0.018329 0.014654 0.003298 -0.005121 -0.006987 -0.007992 0.008169 -0.006890 0.038357 0.018036 -0.000317 0.001191 -0.001427 0.007200 -0.006297 -0.035814 -0.022398 0.012626 0.027306 0.010772 0.005825 -0.003910 0.000532 -0.012953 -0.024098 -0.029979 -0.026234 0.021187 0.042265 0.019800 -0.013805 0.051643 0.018655 -0.020829 -0.010965 0.011450 0.004054 -0.011820 -0.024400 -0.017642 0.020780 0.004894 -0.012303 -0.006319 -0.017480 -0.020879 -0.020351 -0.041814 -0.003708 0.063650 0.012541 -0.033368 -0.014948 0.000243 -0.018925 -0.033596 -0.063961 -0.013310 -0.017954 -0.011555 -0.007685 0.019722
-0.006600 0.004056 0.012057 0.006507 0.046073 0.042831 -0.005066 -0.000991 -0.014320 -0.030164 -0.006456 0.005651 0.011900 0.024114 0.019035 0.045311 -0.016887 -0.007425 -0.009446 0.002795 0.014618 0.007183 0.045986 0.051438 0.034575 -0.016288 -0.010773 -0.005385 -0.009435 0.041412 0.034514 0.010361 -0.033254 -0.005219 0.011323 -0.013081 0.017870 0.041726 0.004202 -0.009866 -0.025968 -0.010921 -0.027534 -0.009524 0.009525 0.018353 0.013053 -0.006611 0.013805 -0.009031 -0.028106 -0.031756 0.003824 0.002125 0.027568 0.053795 -0.001053 -0.001155 -0.019601 -0.040090 -0.041136 0.036317 0.034939 0.010361 -0.007665 0.005726 0.006085 -0.013805 -0.020019 -0.013356 0.015897 -0.008010 0.056189 0.019079 -0.009744 -0.009325 -0.030822 -0.001955 -0.020128 -0.006737 -0.016042 0.001572 0.081905 0.001896 -0.008942 -0.040391 -0.014639 -0.023862 -0.005646 -0.016395 0.065178 -0.004823 0.006614 -0.013866 -0.012938 0.019752 -0.022837 -0.004230 0.002160 -0.016300 -0.015124 -0.021920 0.010268 -0.015404 0.015215 -0.009144 0.008880 -0.009701 -0.007435 -0.020578 -0.019922 -0.016898 -0.048334 -0.016689 0.003747 0.004956 -0.006740 -0.020666 -0.027969 -0.026180 -0.007817 -0.052694 -0.000386 -0.026011 -0.001068 -0.040663 -0.030306 0.019752 0.000025 0.039002 0.048722 0.003829 -0.001704 -0.013514 -0.006395 -0.008625 0.010208 -0.014057 0.017179 0.002608 -0.011841 -0.000259 -0.000418 0.002781 -0.004477 0.004678 0.020648 0.029459 0.042934 -0.008940 -0.005791 0.004619 -0.004946 -0.005436 -0.004321 -0.007741 -0.013452 0.013678 0.039449 0.019752 -0.011185 0.051088 0.001492 -0.020676 -0.009732 -0.003329 0.006876 0.006766 0.007468 -0.013575 -0.014353 -0.018129 -0.013144 0.008491 0.007000 0.003756 -0.013289 -0.018198 -0.004270 0.048622 -0.008543 -0.039943 0.003014 0.022526 0.004264 -0.001011 -0.027296 0.010504 -0.013533 -0.006739 -0.010348 0.019675
-0.001142 0.000565 -0.006052 0.000286 0.034846 0.022196 0.012007 0.000809 0.000451 -0.016933 0.015929 -0.000603 0.008755 0.033025 0.025391 0.024309 -0.001580 -0.018393 -0.002095 0.013956 -0.006645 0.003814 0.043138 0.057197 0.025947 -0.010504 -0.000791 0.002683 -0.003580 0.026188 0.037814 0.006292 -0.013727 0.004545 0.005860 0.005425 -0.014542 -0.017638 -0.011548 -0.000896 -0.003129 -0.001034 -0.033307 -0.007456 0.002065 -0.003676 0.008527 -0.003853 -0.025696 -0.026332 0.000925 -0.023621 -0.011934 -0.001211 -0.019870 -0.005443 -0.014901 -0.028408 -0.021775 -0.059690 -0.053695 0.022505 0.026575 0.006292 -0.030187 0.002635 0.018719 0.015182 0.000533 -0.024383 0.006811 0.009580 0.025503 0.011090 0.018723 0.008150 -0.024160 0.000175 -0.013237 -0.022038 0.005773 0.009330 0.066862 0.030637 0.006402 -0.020947 -0.009741 -0.020043 -0.009589 0.017275 0.039705 -0.014815 0.011695 0.000205 0.011495 0.015683 -0.014467 -0.022351 -0.042612 0.004006 0.020452 0.013870 0.018192 0.001391 -0.004024 -0.012517 0.001558 0.013466 0.014664 -0.007056 -0.025722 0.003050 -0.011113 0.017423 -0.003789 0.006162 -0.018802 0.015402 0.012104 -0.000392 0.025917 -0.001965 0.009887 -0.014096 0.020023 -0.025630 0.004718 0.015683 0.016199 0.028511 -0.000885 0.011743 -0.008896 -0.004362 -0.002974 -0.002036 -0.013603 -0.005880 0.016012 0.012728 0.003530 0.009193 0.002698 0.016331 -0.028680 0.039439 0.041350 0.039560 0.002020 0.011450 0.002905 0.010572 0.005777 -0.017952 0.027623 0.007600 0.000233 0.002728 0.031425 0.015683 0.000382 -0.012595 -0.035293 -0.005929 -0.021301 0.004011 0.002637 0.010259 0.014298 0.019576 0.011751 -0.009862 0.004003 0.020695 0.006103 0.026069 -0.024893 0.001696 0.033347 -0.000021 -0.038867 -0.008250 0.004101 0.019924 0.012961 -0.006717 0.008166 0.016814 0.005474 -0.008357 -0.008460 0.015605
-0.010511 -0.028000 -0.014336 0.005288 0.010060 0.021429 -0.001510 -0.005429 -0.016001 -0.031206 0.008565 0.022228 0.025861 0.013891 0.016673 0.026060 -0.008653 -0.004398 -0.029611 -0.009703 0.006596 0.025374 0.018542 0.038939 0.016821 -0.009378 -0.015931 0.002768 -0.021932 0.027464 0.005847 0.006292 -0.002679 -0.002873 0.031146 -0.006445 -0.014978 -0.001433 0.013926 -0.004154 0.003467 -0.013038 0.000753 -0.016202 0.000090 -0.018236 0.004566 0.010518 -0.011118 -0.008405 0.005918 -0.002948 0.009466 -0.011421 -0.023750 -0.005022 0.018660 -0.024047 0.000105 -0.048361 -0.054969 0.053879 0.032908 0.006292 -0.011688 0.019984 0.032786 -0.013701 -0.012441 0.014881 0.010122 0.027660 0.043609 0.030843 0.001590 0.017323 0.034636 0.016746 -0.005062 -0.009009 -0.003392 0.003837 0.066457 0.028260 0.034737 0.006259 -0.010903 0.012903 0.010517 0.017165 0.032585 -0.007897 0.024847 0.038585 0.038143 0.015683 -0.008983 0.002667 -0.019088 0.024851 -0.000537 0.017235 0.036063 0.008857 -0.027801 -0.023764 -0.035795 0.020021 0.030623 0.015841 0.010741 0.005071 -0.000438 -0.007524 -0.016022 -0.027826 -0.010373 0.038246 0.012392 0.046542 0.044939 0.008516 -0.032350 -0.006838 0.023856 -0.007259 0.012887 0.015683 0.008744 0.032176 0.019452 0.017053 -0.008264 -0.028289 -0.004984 0.022778 -0.007854 0.003141 -0.004845 0.007795 0.015882 0.004380 0.001602 0.003017 -0.002212 0.018167 0.022870 0.023347 0.020361 0.029324 0.006152 -0.016575 -0.001519 0.014446 0.005769 0.011561 0.022484 -0.013070 0.025099 0.015683 0.027834 -0.011858 -0.001501 -0.003684 -0.042199 0.000943 0.015020 -0.002451 -0.010245 -0.005424 -0.017963 -0.019191 0.022762 0.013473 0.032831 0.035769 0.006136 0.009108 0.016530 -0.020704 -0.014991 0.007945 0.010208 0.030215 0.038436 0.011800 -0.001123 0.022699 0.019789 -0.014622 -0.004597 0.015605
-0.019824 -0.010334 -0.017156 -0.025900 -0.014610 0.035049 0.008207 0.002389 0.016981 0.005730 -0.017274 0.020134 0.012087 0.007375 0.008831 0.020019 0.004564 -0.025219 -0.001391 -0.026232 0.002850 -0.016274 0.007109 0.011722 0.018802 0.004417 -0.002368 -0.005195 -0.013557 0.009888 0.014072 0.012291 -0.020705 -0.024706 -0.006023 -0.034786 0.008452 0.012794 0.019283 0.012746 0.012613 0.010544 0.007465 0.016522 0.014581 -0.015791 0.001732 0.006414 0.018144 -0.018665 0.007537 -0.017177 -0.000587 -0.012701 0.012211 -0.005849 0.014824 0.021329 -0.009008 -0.026821 -0.058419 0.051790 0.043168 0.012291 -0.010949 -0.003845 -0.001644 -0.023640 -0.018576 0.044641 0.072423 0.057149 0.045375 0.052715 0.005520 -0.002451 0.022738 0.003864 0.014757 0.001500 -0.007978 -0.018095 0.049254 0.005800 -0.005900 -0.011516 -0.003511 0.051282 0.058938 0.041661 0.024777 0.009744 -0.014283 0.075034 0.039578 0.021682 0.001297 -0.003848 0.005518 0.007914 0.022913 0.041874 0.021157 0.009292 -0.030420 -0.022140 -0.017560 -0.003684 0.025998 0.052586 0.043310 0.030424 0.005861 -0.011786 -0.011458 -0.022920 0.003570 0.020896 0.061125 0.063203 0.048383 0.008887 -0.038083 0.027650 0.009535 0.039409 0.007648 0.021682 0.060303 0.014717 0.032179 0.026175 0.058117 0.001812 -0.005976 0.009426 0.016070 0.015628 0.007716 -0.009024 0.009531 0.012304 -0.006638 0.028925 0.014974 0.030984 0.069875 0.022071 0.026722 0.023327 0.041249 0.011887 0.035894 0.020520 0.046529 0.050708 0.042931 0.031886 0.024014 0.021682 0.030570 -0.028211 -0.008569 -0.003180 0.027183 0.013982 -0.003087 0.001753 -0.010428 0.023824 -0.022081 -0.009529 0.038162 -0.014008 0.009748 0.006391 0.034518 0.014769 0.044353 -0.041359 -0.011667 0.018742 0.001477 0.009706 0.004888 0.029719 0.007780 0.034313 0.023069 0.000786 -0.010176 0.021605
-0.000449 0.011998 -0.005749 0.002790 0.047116 0.067298 0.030255 0.031123 0.014472 -0.000741 0.000285 0.000488 -0.019267 0.007275 0.013671 -0.004493 -0.029870 -0.008935 0.004957 0.008677 -0.008597 0.000312 0.042156 0.046869 0.023905 0.007576 0.012008 0.037665 -0.006576 0.037922 0.005124 0.007427 -0.010106 -0.004569 -0.006992 -0.001103 0.011587 0.035625 0.009394 0.015507 -0.008458 -0.017131 -0.000819 0.001120 0.008658 -0.019940 -0.015616 -0.005094 -0.015169 -0.023830 -0.006405 -0.010489 -0.011174 0.003924 0.002401 0.007714 0.014415 0.003250 -0.021813 0.004881 -0.065509 0.045005 -0.006503 0.007427 -0.017455 -0.030530 -0.023621 -0.043839 -0.001682 0.029342 0.053190 0.024128 0.035271 0.008294 -0.006993 0.012228 0.018568 -0.023449 -0.014805 -0.036490 -0.023736 -0.024124 0.004360 -0.028112 -0.016689 -0.043551 -0.006717 0.010024 0.012391 0.004055 0.005862 0.002427 -0.063790 0.048151 -0.017760 0.015807 -0.007679 -0.021753 -0.020077 -0.003814 0.039542 0.055517 0.011558 0.003930 -0.013583 -0.014265 -0.008007 -0.003870 -0.002698 0.025079 -0.007118 0.006771 -0.000728 -0.016934 -0.016881 -0.024973 -0.027237 -0.013701 0.045129 0.027190 0.001533 0.001668 -0.026822 0.027287 -0.037463 0.048010 -0.027525 0.015807 -0.000716 -0.007391 0.007672 0.048985 0.044913 0.052709 0.005409 -0.007881 -0.015959 -0.010451 -0.005675 -0.015992 0.002265 -0.011172 -0.003651 -0.004001 -0.005771 -0.016915 -0.006314 -0.015514 -0.011271 0.034277 0.034250 0.025561 0.000218 -0.021266 -0.025788 0.036984 -0.018088 0.035279 -0.027599 0.015807 -0.016969 -0.021182 0.018318 0.036752 0.064595 0.053887 -0.014973 -0.006545 -0.007517 -0.020052 -0.019555 -0.008199 -0.012403 -0.027392 0.003248 -0.004845 -0.008308 -0.012825 -0.033615 -0.038492 0.000949 0.013931 0.054685 0.033781 -0.015731 -0.010700 -0.017149 0.040769 -0.015864 0.012430 -0.039203 0.015729
</data>
</_>
</PartFilters>
<PartPCAFilters>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>36</cols>
<dt>d</dt>
<data>
0.050104 -0.048011 -0.029705 -0.052442 -0.008172 0.002777 -0.006393 0.062358 -0.195551 -0.031130 0.001042 0.003541 -0.095971 0.169039 -0.067480 -0.108019 0.033076 0.003543 -0.061280 0.089053 0.158444 -0.049996 0.003997 0.003543 0.035513 -0.053194 0.049545 -0.044923 -0.021001 0.003543 -0.024375 0.084447 -0.019257 -0.084879 -0.014608 0.003543
-0.014044 -0.093978 -0.089508 -0.027631 0.027392 0.011092 -0.050732 -0.009775 -0.252586 0.062109 -0.012190 0.011856 0.057014 0.156507 0.017135 0.039924 -0.060268 0.011858 0.004658 0.038590 0.226086 0.092015 -0.095687 0.011858 -0.042125 -0.096865 0.121319 0.021700 -0.002115 0.011858 -0.053228 0.081484 -0.021754 -0.052300 -0.000094 0.011858
-0.077128 -0.098976 0.003875 -0.090088 -0.004011 0.011099 -0.092554 -0.042010 0.031147 0.014762 0.042880 0.011863 0.075888 0.090175 0.010854 0.022614 -0.025184 0.011865 0.036023 -0.029841 0.070137 0.042758 -0.059677 0.011865 -0.035189 -0.177750 0.018205 -0.064991 -0.005077 0.011865 0.009431 0.043379 -0.012490 -0.114811 0.010945 0.011865
-0.062252 -0.043291 0.003299 -0.055978 -0.055156 0.011233 -0.052678 -0.071774 0.098359 0.066509 0.024603 0.011998 0.016644 0.073673 0.012180 0.031044 0.012922 0.012000 -0.058476 -0.060230 -0.023807 -0.009671 0.054925 0.012000 -0.094103 -0.115167 -0.015307 -0.001114 0.041597 0.012000 0.056798 0.014034 0.001058 -0.028828 -0.003202 0.012000
-0.057680 0.076910 0.028664 -0.042264 0.029081 -0.000767 -0.133369 -0.058850 0.059343 0.054349 -0.017765 -0.000002 0.086189 0.058320 -0.008109 0.042540 -0.011641 0.000000 0.022700 0.020028 -0.082459 0.001391 0.074930 0.000000 -0.136299 0.050534 0.042012 0.020930 0.061374 0.000000 -0.031107 0.028781 0.050403 0.022491 0.007456 -0.000000
0.014961 0.088769 -0.111421 0.022697 -0.022923 -0.000767 -0.086821 -0.052040 0.042662 0.056652 -0.007746 -0.000002 -0.013673 0.031110 0.000574 0.060421 0.018839 0.000000 0.056111 0.046832 -0.181882 0.069537 0.050904 0.000000 0.064345 0.043024 0.066133 0.055179 -0.055074 0.000000 -0.001848 0.070872 0.201505 0.091126 -0.068298 -0.000000
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>36</cols>
<dt>d</dt>
<data>
-0.087144 0.078769 -0.009122 0.015409 0.042013 0.006155 0.012795 0.077597 -0.056245 0.022885 0.023624 0.001899 -0.011695 -0.004607 0.004760 -0.023270 0.007527 0.004850 0.052658 -0.034361 0.064009 0.013566 -0.026206 0.010170 0.043488 -0.006393 -0.001554 0.018222 -0.011459 0.010797 0.017410 -0.008921 -0.008594 -0.030732 0.042169 0.015598
-0.039628 0.050375 -0.016947 -0.011759 0.009177 0.005911 0.006382 0.078597 0.008354 -0.003342 0.003225 0.001654 -0.028479 -0.025202 0.028363 0.006395 0.030720 0.004606 0.051218 -0.055860 0.031464 0.005268 -0.000086 0.009925 0.120364 -0.022333 -0.013201 0.012755 0.028128 0.010552 -0.043743 -0.009106 -0.013888 -0.060987 0.025397 0.015353
-0.029707 0.061829 -0.003868 0.001136 0.012762 0.005910 0.063673 0.071206 -0.034410 -0.024000 -0.029951 0.001653 0.000956 -0.006326 -0.001487 -0.019022 -0.004979 0.004604 -0.056953 -0.003447 0.045906 0.015306 0.022544 0.009924 0.031931 -0.010473 -0.062987 0.029283 0.007558 0.010551 -0.045600 -0.032611 -0.027340 -0.013122 0.005130 0.015352
0.017014 -0.006871 -0.033331 0.012942 0.015777 0.005636 0.092278 0.024076 -0.063263 -0.013661 0.004084 0.001379 0.023100 -0.006168 -0.027631 0.055932 -0.012652 0.004331 -0.090925 -0.001637 0.012172 0.068314 0.011328 0.009650 -0.043955 -0.010173 -0.011246 0.019742 0.010863 0.010277 -0.061706 -0.061511 0.001204 -0.003111 0.041673 0.015078
-0.072998 -0.002756 0.058256 -0.006006 0.003721 0.005636 -0.075587 0.073064 -0.063865 -0.031067 -0.018236 0.001379 -0.050854 0.065892 -0.022976 0.009397 -0.039518 0.004331 -0.051296 0.082061 0.029972 -0.001012 0.011227 0.009650 -0.065595 0.048453 -0.032511 -0.034664 0.041882 0.010277 -0.109007 -0.006280 -0.028993 -0.062086 -0.018496 0.015078
-0.032901 0.006692 0.010888 -0.022062 0.025585 0.022133 -0.038380 0.067582 0.046099 -0.045883 0.039392 0.017876 0.010383 0.106269 0.050001 -0.033937 0.047796 0.020828 0.040339 0.098606 -0.006232 -0.036102 0.044273 0.020829 0.035841 0.100117 -0.070597 -0.030603 0.038922 0.020829 0.006741 0.067180 -0.058975 -0.020837 0.033482 0.020829
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>36</cols>
<dt>d</dt>
<data>
-0.011370 0.009977 -0.028176 0.053808 -0.021791 0.000000 0.040942 -0.010569 -0.076901 0.062932 -0.003305 0.000000 -0.088711 0.076282 0.046030 0.019258 0.036742 0.000000 -0.069735 0.058445 0.152172 0.036438 0.020301 -0.000000 0.008565 -0.002449 -0.013702 0.023211 0.013668 -0.001385 0.055049 0.013528 -0.094118 -0.047114 -0.025295 -0.001392
-0.013610 0.043585 0.003965 -0.001567 -0.000719 0.000000 0.069358 -0.037342 -0.071923 -0.002569 -0.029638 0.000000 0.125968 -0.017864 -0.064479 0.016189 -0.084275 0.000000 0.109876 0.061394 0.121088 0.072992 -0.076793 -0.000000 -0.059438 -0.020033 0.177455 0.079425 -0.027135 -0.001385 0.012940 0.042226 -0.004891 -0.069099 0.006905 -0.001392
-0.013585 0.013595 -0.021576 -0.034995 0.010815 0.000000 -0.008884 -0.011732 -0.024182 -0.005143 -0.049676 0.000000 0.055548 -0.039052 -0.034533 0.016825 -0.121085 0.000000 0.132954 0.009647 -0.070327 -0.012631 -0.106702 -0.000000 0.002228 -0.076287 0.093708 0.034217 -0.036079 -0.001385 -0.071492 -0.035836 0.013933 -0.041348 0.000938 -0.001392
-0.006445 -0.008682 -0.031073 0.006842 -0.029355 0.000000 -0.013059 0.001115 -0.009132 0.017514 -0.042080 0.000000 0.002945 -0.012373 -0.017162 0.003862 -0.081739 0.000000 0.002157 -0.015103 -0.042886 -0.022196 -0.084498 -0.000000 0.047741 -0.024455 0.011151 -0.007586 -0.043961 -0.001385 -0.052678 -0.061520 0.027899 -0.008354 -0.010445 -0.001392
0.011080 -0.004608 0.019788 -0.004182 -0.027031 0.000000 0.025536 0.039597 -0.010377 -0.009243 -0.023517 0.000000 -0.045365 -0.044510 -0.013744 -0.018447 -0.050139 0.000000 -0.023912 -0.071676 0.026430 -0.002839 -0.054554 -0.000000 0.046490 -0.026630 0.016789 0.000763 -0.016666 -0.001385 -0.054799 0.027583 -0.027005 -0.027277 -0.005880 -0.001392
-0.033906 -0.000114 -0.017391 0.004220 -0.005974 0.000000 0.021199 0.025468 -0.003636 0.031463 -0.025630 0.000000 -0.033137 -0.002650 -0.046547 0.002409 -0.015348 0.000000 -0.036748 -0.030196 0.023522 -0.039041 -0.018974 -0.000000 0.005226 -0.037719 0.005093 -0.007164 -0.015197 -0.001385 0.009473 -0.032524 -0.012102 -0.002470 -0.025752 -0.001392
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>36</cols>
<dt>d</dt>
<data>
-0.051682 -0.026721 0.009171 -0.020624 0.025254 0.005336 -0.010678 0.046723 0.042185 0.012607 -0.018768 0.005336 0.042527 0.088741 -0.024868 0.017808 -0.000381 0.005330 0.001513 -0.046171 -0.055367 -0.057963 0.051575 0.005330 -0.022124 0.013444 -0.009298 -0.024010 0.011204 -0.005955 -0.021540 0.084394 -0.003455 -0.003150 0.015368 -0.011858
-0.023328 -0.052113 -0.037224 -0.029741 0.001759 0.008054 0.022100 0.021031 0.011049 0.007141 0.021874 0.008054 0.037466 -0.001729 -0.025179 0.047150 0.020281 0.008048 -0.036132 -0.049629 -0.042775 -0.043947 0.033414 0.008048 0.011863 0.041404 -0.018182 -0.036912 0.023624 -0.003237 -0.015642 0.081557 -0.007783 -0.006185 -0.015734 -0.009140
-0.050213 -0.068180 0.022385 -0.010614 0.019815 0.008036 0.046075 0.037673 0.057584 0.027674 0.036675 0.008036 0.074209 0.020589 -0.014858 0.057200 0.042170 0.008029 -0.030254 -0.054769 -0.020527 -0.001385 -0.009756 0.008029 0.023494 0.070774 -0.007807 -0.020517 -0.017170 -0.003255 -0.037874 0.064297 -0.005427 0.003390 0.028000 -0.009159
-0.052642 -0.089345 0.020197 -0.003074 0.011934 0.003802 0.023378 -0.014089 0.111110 0.027694 0.003577 0.003802 0.037280 0.063521 0.042350 0.079839 0.027002 0.003796 -0.066608 -0.066028 0.035431 -0.021604 0.030829 0.003796 0.019702 0.035105 0.054061 0.022175 0.028963 -0.007489 -0.022658 0.068995 -0.009466 -0.010027 0.028729 -0.013392
-0.041401 -0.030569 0.013895 -0.012124 0.017116 0.003802 -0.002869 -0.065020 0.112081 0.031867 0.013259 0.003802 0.096914 0.056950 0.063853 0.094804 0.015225 0.003795 -0.051578 -0.068026 0.051508 0.023294 0.014455 0.003795 0.001174 0.012565 0.030536 0.028937 0.039000 -0.007489 -0.033951 0.068643 0.012874 -0.001700 0.034109 -0.013393
0.007055 0.047515 0.006351 -0.022985 0.000228 0.002233 -0.096654 -0.042786 0.077028 0.000542 -0.004791 0.002233 0.080479 0.073239 0.032787 0.067239 -0.008081 0.002226 -0.034596 -0.002789 -0.029655 0.007710 0.000743 0.002226 -0.024920 0.033568 -0.006847 0.006283 0.019383 -0.009058 -0.018921 0.048367 0.009549 0.008772 0.032552 -0.014962
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>36</cols>
<dt>d</dt>
<data>
-0.023160 -0.013947 0.001836 -0.017637 0.021676 -0.006270 -0.010857 -0.001883 -0.018935 0.004047 0.037970 -0.006192 0.003038 -0.011152 -0.003689 0.025038 0.022886 -0.006192 -0.068563 -0.023530 0.030784 0.005410 0.016963 -0.001155 -0.005075 0.054599 0.009004 0.011173 -0.011582 0.000000 -0.003489 0.033746 0.000913 -0.007586 -0.037395 0.000000
-0.055019 -0.004619 -0.006002 -0.034133 0.002105 -0.006270 0.012748 -0.054332 -0.024510 0.009247 -0.003362 -0.006192 0.021803 -0.051723 -0.045882 0.011688 0.005081 -0.006192 -0.030905 -0.021425 0.002799 0.047604 0.006731 -0.001155 0.006876 0.042579 -0.019606 0.025734 0.021123 0.000000 0.021587 0.059742 -0.021910 0.017813 0.004935 0.000000
-0.025948 0.018422 -0.037557 -0.063729 0.012888 -0.006270 0.000553 -0.034593 -0.014918 -0.059560 0.004256 -0.006192 0.017093 -0.055570 -0.026786 -0.023328 0.006562 -0.006192 -0.000305 -0.011056 0.012324 0.049694 -0.004053 -0.001155 -0.033098 0.012222 0.061427 0.067757 -0.032322 0.000000 0.017054 0.068511 -0.014055 0.059933 -0.030049 0.000000
-0.020881 0.018305 0.017509 -0.043121 0.017770 -0.006270 -0.033194 -0.015649 0.016405 -0.037457 0.026484 -0.006192 -0.014466 0.010309 0.035567 0.018557 -0.027304 -0.006192 0.004556 0.088741 0.059078 0.038667 -0.022275 -0.001155 -0.024821 0.076316 0.023747 0.008662 -0.011255 0.000000 -0.009864 0.048040 -0.092494 0.051285 0.016282 0.000000
-0.061641 0.033226 0.080494 -0.007913 0.002725 -0.000275 -0.079358 -0.021411 0.020169 -0.024159 0.025176 -0.000197 0.051566 -0.021216 0.026077 -0.060678 -0.002155 -0.000197 0.088496 0.044860 0.011614 -0.012441 0.020595 0.004840 -0.018745 0.049989 0.010076 0.020590 0.053980 0.005995 -0.049576 -0.001875 -0.031005 -0.010673 0.064362 0.005995
-0.006184 0.121101 -0.042441 -0.011369 -0.017006 -0.002314 -0.041392 -0.003039 -0.050042 -0.017926 -0.019353 -0.002236 0.074577 -0.083742 0.016145 -0.034168 0.007169 -0.002236 0.148323 -0.004155 -0.015409 0.038189 0.025172 0.002801 -0.019221 -0.058575 0.004297 0.006776 0.077527 0.003956 -0.027773 -0.093572 0.013614 -0.032632 0.039650 0.003956
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>36</cols>
<dt>d</dt>
<data>
0.006008 0.031156 0.049453 -0.013458 0.001053 -0.001176 -0.097564 -0.018126 -0.136463 0.034637 -0.000110 -0.001176 -0.048780 0.010099 -0.086235 0.050568 -0.011887 -0.001161 0.020463 0.029020 0.043994 0.050534 -0.048540 -0.000636 0.037528 0.049475 -0.028581 0.052594 -0.030802 -0.000000 -0.019718 0.002574 -0.045015 0.052368 -0.002941 -0.000000
-0.045982 -0.036450 -0.047688 -0.037617 0.020289 -0.001176 -0.008457 -0.092268 -0.127211 0.030699 -0.019112 -0.001176 0.144026 0.027176 0.040515 0.010445 -0.077258 -0.001161 0.037436 0.028122 0.088559 0.020694 -0.062330 -0.000636 0.009068 0.012855 0.015981 0.042306 -0.056997 -0.000000 0.043033 -0.002068 -0.017978 0.015006 -0.017613 -0.000000
-0.039420 -0.070850 -0.034986 -0.007477 0.011105 -0.001176 0.099092 -0.090138 -0.021007 0.016995 -0.028507 -0.001176 0.052217 -0.031275 0.070531 0.044553 -0.064896 -0.001161 -0.035472 0.020876 0.049548 0.003423 -0.036606 -0.000636 -0.042881 0.065607 -0.023776 -0.000085 -0.016970 -0.000000 -0.014271 0.013642 -0.040248 -0.041506 0.014464 -0.000000
-0.036016 -0.055866 -0.043885 -0.012882 0.005027 -0.001176 0.064299 -0.019574 0.016435 -0.003757 0.004673 -0.001176 0.003403 -0.050256 0.034570 -0.011113 -0.040895 -0.001161 0.027575 -0.028377 0.000839 0.018773 -0.028968 -0.000636 -0.002614 -0.020068 -0.023965 0.002406 -0.033876 -0.000000 0.014467 -0.016337 0.026864 -0.026601 -0.014972 -0.000000
-0.016212 -0.022774 0.040835 -0.022454 0.003983 -0.001176 0.024860 0.009405 0.001698 0.029496 0.001661 -0.001176 -0.020797 -0.066020 0.001233 -0.033120 0.001647 -0.001161 -0.021300 -0.035956 0.023304 -0.000734 0.005578 -0.000636 -0.016964 -0.006241 0.023871 0.002336 -0.044485 -0.000000 -0.030524 0.065688 0.014941 0.011227 -0.012136 -0.000000
-0.049098 0.024135 0.035363 -0.006480 -0.064175 -0.001176 -0.019019 0.053257 -0.027555 0.010567 -0.024414 -0.001176 -0.031536 -0.050078 -0.038386 -0.024850 0.004371 -0.001161 -0.004680 -0.035907 -0.000754 0.026261 0.017922 -0.000636 0.009315 0.038222 -0.002417 0.044403 0.012357 -0.000000 -0.000170 -0.030380 -0.024559 0.002702 0.021056 -0.000000
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>36</cols>
<dt>d</dt>
<data>
0.035332 -0.011570 -0.019290 0.024212 -0.016216 0.000000 0.026048 -0.006521 -0.023799 -0.032759 -0.002186 -0.000003 0.016161 0.028305 0.028440 0.046954 0.009586 -0.000007 -0.024011 -0.048576 -0.000229 0.038573 0.026159 -0.000007 -0.019834 -0.046082 0.034007 0.018298 -0.005313 -0.000007 0.021058 0.029246 -0.015558 -0.022289 -0.039486 -0.000016
-0.043740 0.030778 0.014504 0.016379 -0.039686 0.000000 -0.019423 0.025322 -0.002966 -0.026683 0.027143 -0.000003 -0.019384 0.052288 -0.061074 0.020500 0.045008 -0.000007 0.012217 -0.025185 -0.062337 0.042016 0.021798 -0.000007 0.040833 -0.062436 0.082190 -0.003818 0.005948 -0.000007 0.013097 -0.012108 0.024606 -0.039942 0.007626 -0.000016
0.008999 0.007165 0.015855 0.016307 0.002651 0.000000 -0.011239 0.023117 -0.024296 0.020620 -0.008438 -0.000003 0.004688 0.022417 -0.018634 0.036072 0.022878 -0.000007 0.046855 0.040240 0.008589 0.047631 0.017702 -0.000007 -0.018141 -0.042574 -0.022228 -0.026677 0.039102 -0.000007 -0.029561 -0.036512 0.004030 -0.071810 0.053858 -0.000016
-0.045905 0.061282 0.032106 0.005550 -0.012498 0.000000 0.009071 0.076557 0.005154 0.030652 -0.013106 -0.000003 -0.018141 0.103958 0.014379 0.036236 0.008523 -0.000007 0.044656 0.083775 -0.000350 -0.009467 0.019123 -0.000007 -0.038034 -0.026655 -0.036391 -0.013934 0.010067 -0.000007 -0.069083 -0.095976 -0.002501 -0.037606 0.021463 -0.000016
-0.019070 0.058709 0.004813 -0.002420 -0.043418 0.000000 0.023048 0.035653 -0.016662 0.008804 -0.027517 -0.000003 0.000361 -0.000148 -0.065787 0.016359 -0.004032 -0.000007 0.010720 0.063145 -0.027321 0.001664 0.016040 -0.000007 -0.106790 -0.008503 -0.017457 -0.012644 -0.003381 -0.000007 -0.100983 -0.040210 -0.052586 -0.039022 -0.015142 -0.000016
-0.002926 0.032980 -0.005173 0.001345 -0.002859 -0.000946 -0.033613 0.020357 0.000328 -0.001146 0.014546 -0.000949 0.051159 0.028860 -0.027302 0.025542 -0.014008 -0.000952 0.114255 -0.030812 -0.061091 -0.004079 0.006471 -0.000952 -0.012653 -0.083939 -0.002041 -0.025056 0.027542 -0.000952 -0.045937 0.094721 0.030394 -0.026624 -0.031513 -0.000962
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>36</cols>
<dt>d</dt>
<data>
0.047708 -0.006833 0.061998 -0.010708 0.020040 0.019722 -0.001425 0.016894 0.051069 0.033320 0.000584 0.019800 0.099552 -0.017323 -0.020898 -0.017078 -0.035212 0.019800 0.011628 -0.055818 -0.020442 -0.053380 0.012370 0.019800 -0.065706 0.075155 -0.019798 0.004023 -0.004041 0.010409 -0.083455 0.081681 0.003249 0.010931 0.002077 0.010409
0.010229 0.005898 -0.008153 -0.015866 0.000121 0.019675 -0.028564 -0.033484 0.040703 0.010218 0.004668 0.019752 0.083603 -0.025183 0.022605 -0.009308 0.014179 0.019752 0.008577 -0.085740 -0.033729 -0.046862 0.015526 0.019752 -0.003751 0.093446 -0.004255 -0.004552 0.007209 0.010361 -0.066336 0.089639 0.011801 -0.006899 0.006814 0.010361
-0.010915 -0.001556 -0.036956 -0.043003 -0.025340 0.015605 -0.047888 -0.035993 0.022665 -0.021736 -0.013556 0.015683 -0.002925 0.020063 -0.014586 0.010650 0.018311 0.015683 -0.021464 -0.073888 -0.002640 -0.005382 0.016267 0.015683 0.060676 0.012929 0.016937 -0.006602 -0.005744 0.006292 -0.067747 0.070257 -0.003580 -0.024174 -0.006622 0.006292
-0.032662 0.022861 -0.046524 -0.003406 -0.046139 0.015605 -0.043380 -0.037834 0.030629 0.024184 -0.011145 0.015683 -0.031284 0.082679 -0.010920 0.034479 -0.000718 0.015683 -0.089359 -0.058517 0.006729 -0.000002 0.002137 0.015683 0.017702 -0.009638 -0.003557 0.013011 0.006754 0.006292 -0.021642 0.075312 0.012502 0.019872 -0.021696 0.006292
-0.041647 -0.000653 -0.034863 -0.020469 -0.001974 0.021605 -0.144215 -0.038903 0.002712 -0.026232 0.022363 0.021682 -0.084527 0.123083 -0.011204 -0.002224 -0.019214 0.021682 -0.105395 -0.011670 -0.084361 -0.009405 0.023988 0.021682 -0.007982 0.009862 -0.031668 0.012899 0.000405 0.012291 -0.005221 0.031654 -0.032777 0.002226 -0.012924 0.012291
-0.004185 0.099510 0.022231 -0.010970 0.068600 0.015729 -0.023345 0.073430 0.030274 -0.015384 0.059768 0.015807 -0.006246 0.088731 -0.020157 -0.029938 0.026682 0.015807 0.028039 0.008420 -0.053096 -0.012195 0.036474 0.015807 0.013748 0.033590 -0.005347 0.010199 0.036894 0.007427 -0.075879 0.056215 -0.023791 -0.036016 0.061326 0.007427
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>36</cols>
<dt>d</dt>
<data>
-0.024280 0.084133 0.020951 -0.084917 -0.015158 0.003543 0.035113 -0.052842 -0.050787 -0.045266 -0.020270 0.003543 -0.063072 0.091803 -0.156315 -0.054722 0.005445 0.003543 -0.095642 0.168031 0.071852 -0.108853 0.031954 0.003543 -0.004505 0.059216 0.196574 -0.027572 -0.001024 0.003541 0.050267 -0.048232 0.028693 -0.052593 -0.008527 0.002777
-0.053228 0.081322 0.023861 -0.053194 -0.000296 0.011858 -0.042562 -0.095572 -0.122550 0.023832 0.000287 0.011858 0.003121 0.041681 -0.227377 0.091790 -0.092582 0.011858 0.056886 0.156514 -0.016366 0.039727 -0.059935 0.011858 -0.048879 -0.013202 0.252156 0.063173 -0.015903 0.011856 -0.013866 -0.094969 0.088928 -0.030137 0.025588 0.011092
0.009605 0.043019 0.014111 -0.114287 0.011372 0.011865 -0.035183 -0.176707 -0.019927 -0.064315 -0.005257 0.011865 0.035551 -0.029254 -0.071875 0.042710 -0.058506 0.011865 0.075850 0.089604 -0.010600 0.022825 -0.024767 0.011865 -0.092831 -0.041970 -0.030423 0.014222 0.043262 0.011863 -0.077298 -0.098951 -0.003928 -0.091014 -0.004307 0.011099
0.056658 0.014174 -0.001216 -0.029622 -0.003595 0.012000 -0.094098 -0.114624 0.014980 -0.001639 0.040729 0.012000 -0.058135 -0.061195 0.024260 -0.008626 0.054675 0.012000 0.016767 0.072931 -0.011218 0.032222 0.013606 0.012000 -0.053082 -0.070815 -0.098985 0.067938 0.026639 0.011998 -0.062139 -0.043243 -0.003614 -0.055241 -0.054952 0.011233
-0.031610 0.029486 -0.049938 0.021498 0.007991 -0.000000 -0.136768 0.051765 -0.039554 0.019738 0.061506 0.000000 0.023320 0.018853 0.083553 0.001745 0.073525 0.000000 0.086350 0.057982 0.007692 0.043338 -0.011294 0.000000 -0.133662 -0.058549 -0.059728 0.055131 -0.016109 -0.000002 -0.057706 0.077692 -0.026227 -0.041344 0.029478 -0.000767
-0.003426 0.074370 -0.202107 0.089625 -0.065774 -0.000000 0.063931 0.044082 -0.067151 0.055288 -0.054536 0.000000 0.057643 0.044494 0.182249 0.071508 0.048248 0.000000 -0.013536 0.031073 -0.000265 0.061326 0.019351 0.000000 -0.086907 -0.051900 -0.043103 0.057894 -0.006649 -0.000002 0.015926 0.087028 0.111952 0.024069 -0.024306 -0.000767
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>36</cols>
<dt>d</dt>
<data>
0.017326 -0.008800 0.009155 -0.031534 0.042010 0.015598 0.043209 -0.006021 0.000791 0.016432 -0.011703 0.010797 0.052194 -0.033338 -0.065333 0.013351 -0.025207 0.010170 -0.011653 -0.004446 -0.004327 -0.022865 0.007512 0.004850 0.013338 0.076794 0.057634 0.023779 0.022912 0.001899 -0.087129 0.078832 0.011533 0.015014 0.041565 0.006155
-0.043694 -0.009392 0.014942 -0.061281 0.025171 0.015353 0.120504 -0.022329 0.012240 0.012949 0.027543 0.010552 0.051017 -0.055494 -0.032590 0.005329 0.000751 0.009925 -0.028576 -0.024934 -0.027933 0.006757 0.031326 0.004606 0.006319 0.079117 -0.007136 -0.003443 0.003493 0.001654 -0.039627 0.050393 0.018189 -0.012596 0.008619 0.005911
-0.045443 -0.032939 0.027346 -0.013405 0.004759 0.015352 0.032282 -0.010914 0.062460 0.028839 0.006376 0.010551 -0.057226 -0.003159 -0.045150 0.015438 0.023393 0.009924 0.000955 -0.006380 0.001505 -0.019148 -0.004665 0.004604 0.063984 0.071032 0.034585 -0.023695 -0.030626 0.001653 -0.029579 0.061611 0.005094 0.001645 0.012680 0.005910
-0.061575 -0.061151 -0.001228 -0.002243 0.041371 0.015078 -0.043912 -0.009912 0.011197 0.019604 0.010517 0.010277 -0.091273 -0.001999 -0.012021 0.066717 0.011190 0.009650 0.023186 -0.006637 0.026620 0.055226 -0.013414 0.004331 0.092986 0.022743 0.062813 -0.012019 0.003254 0.001379 0.017441 -0.008057 0.033080 0.014052 0.015480 0.005636
-0.108736 -0.006179 0.029830 -0.061452 -0.019065 0.015078 -0.065288 0.048097 0.034449 -0.033959 0.041209 0.010277 -0.051720 0.082036 -0.028307 -0.002481 0.011442 0.009650 -0.050798 0.065226 0.023504 0.008504 -0.039464 0.004331 -0.075202 0.071842 0.065380 -0.031558 -0.018854 0.001379 -0.073634 -0.002154 -0.057639 -0.007669 0.004520 0.005636
0.007275 0.066267 0.060456 -0.019892 0.032605 0.020829 0.036324 0.099269 0.072653 -0.030453 0.037688 0.020829 0.040252 0.098318 0.008401 -0.037058 0.043741 0.020829 0.009993 0.106717 -0.047414 -0.034585 0.048397 0.020828 -0.038916 0.068338 -0.043705 -0.047431 0.040061 0.017876 -0.032956 0.006527 -0.010190 -0.021981 0.025908 0.022133
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>36</cols>
<dt>d</dt>
<data>
0.055811 0.012275 0.093874 -0.046208 -0.026698 -0.001392 0.008542 -0.002540 0.013586 0.022563 0.013225 -0.001385 -0.071244 0.061466 -0.150884 0.033186 0.021639 -0.000000 -0.089039 0.077580 -0.043932 0.018928 0.036883 0.000000 0.041704 -0.011506 0.075899 0.064397 -0.004421 0.000000 -0.010984 0.009421 0.027703 0.055017 -0.022160 0.000000
0.013009 0.041961 0.006208 -0.068740 0.006950 -0.001392 -0.060744 -0.017552 -0.178112 0.078720 -0.024686 -0.001385 0.108846 0.063553 -0.122628 0.071541 -0.075446 -0.000000 0.126519 -0.018191 0.062055 0.016923 -0.085460 0.000000 0.069808 -0.038033 0.070396 -0.002667 -0.031008 0.000000 -0.013562 0.043576 -0.003270 -0.001211 -0.000568 0.000000
-0.071566 -0.035676 -0.013358 -0.041151 0.001742 -0.001392 0.001642 -0.074949 -0.095469 0.034398 -0.034120 -0.001385 0.133428 0.008949 0.067992 -0.012718 -0.107801 -0.000000 0.055908 -0.039495 0.031723 0.017720 -0.121418 0.000000 -0.008904 -0.011615 0.023389 -0.006104 -0.050502 0.000000 -0.013503 0.013315 0.022293 -0.035439 0.010387 0.000000
-0.052907 -0.061037 -0.028485 -0.008593 -0.009519 -0.001392 0.047754 -0.024554 -0.012348 -0.007259 -0.043315 -0.001385 0.002245 -0.015534 0.041626 -0.023396 -0.085232 -0.000000 0.003063 -0.012929 0.015734 0.003941 -0.081692 0.000000 -0.013053 0.000671 0.008647 0.017338 -0.042190 0.000000 -0.006229 -0.008878 0.030523 0.006961 -0.029918 0.000000
-0.054467 0.027314 0.028021 -0.026530 -0.005967 -0.001392 0.046521 -0.026519 -0.017782 0.001489 -0.016053 -0.001385 -0.024258 -0.071396 -0.028081 -0.003777 -0.054570 -0.000000 -0.045250 -0.045014 0.012878 -0.018250 -0.050234 0.000000 0.025553 0.039442 0.010618 -0.009539 -0.023293 0.000000 0.010785 -0.004013 -0.020182 -0.005198 -0.026833 0.000000
0.009593 -0.032706 0.011191 -0.002289 -0.025569 -0.001392 0.005392 -0.038104 -0.005822 -0.005997 -0.014929 -0.001385 -0.037027 -0.030134 -0.023596 -0.039713 -0.018568 -0.000000 -0.032867 -0.003613 0.046576 0.002342 -0.015834 0.000000 0.021386 0.024989 0.003181 0.032557 -0.025247 0.000000 -0.033577 -0.000926 0.017599 0.005454 -0.006167 0.000000
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>36</cols>
<dt>d</dt>
<data>
-0.021510 0.084494 0.005217 -0.003079 0.015026 -0.011858 -0.022257 0.013491 0.010011 -0.025142 0.010936 -0.005955 0.001811 -0.047026 0.055936 -0.058273 0.050736 0.005330 0.042656 0.088707 0.025705 0.017505 -0.000696 0.005330 -0.011062 0.047844 -0.041647 0.011901 -0.018109 0.005336 -0.051968 -0.026383 -0.008499 -0.022040 0.025238 0.005336
-0.015678 0.081564 0.008991 -0.006686 -0.016011 -0.009140 0.011983 0.041117 0.019263 -0.036813 0.023241 -0.003237 -0.035777 -0.050344 0.043096 -0.043465 0.032822 0.008048 0.037500 -0.001252 0.024831 0.046208 0.019419 0.008048 0.022040 0.021197 -0.010617 0.007227 0.022052 0.008054 -0.023061 -0.052732 0.036994 -0.029484 0.001212 0.008054
-0.037779 0.063982 0.007028 0.003787 0.027867 -0.009159 0.023581 0.070879 0.008707 -0.020076 -0.017600 -0.003255 -0.029988 -0.055178 0.019899 -0.000610 -0.009989 0.008029 0.074498 0.020757 0.014781 0.058127 0.042003 0.008029 0.045817 0.038433 -0.056918 0.028484 0.037764 0.008036 -0.050265 -0.068053 -0.022509 -0.010021 0.020115 0.008036
-0.022531 0.068641 0.011119 -0.009565 0.028587 -0.013392 0.019390 0.035924 -0.053401 0.022513 0.029611 -0.007489 -0.066602 -0.065779 -0.035250 -0.020284 0.031659 0.003796 0.037111 0.064712 -0.041832 0.080284 0.027348 0.003796 0.022699 -0.012568 -0.111541 0.028114 0.005514 0.003802 -0.052768 -0.089482 -0.020796 -0.003009 0.012738 0.003802
-0.034148 0.068515 -0.011053 -0.002220 0.034313 -0.013393 0.001086 0.013045 -0.029940 0.029548 0.039753 -0.007489 -0.051658 -0.067114 -0.052013 0.024623 0.015692 0.003795 0.096539 0.058281 -0.064324 0.095039 0.016054 0.003795 -0.003653 -0.063749 -0.113215 0.031883 0.015634 0.003802 -0.041426 -0.030606 -0.013698 -0.011719 0.017712 0.003802
-0.018913 0.048317 -0.008246 0.009292 0.032599 -0.014962 -0.024800 0.033905 0.007845 0.006726 0.019323 -0.009058 -0.034390 -0.002604 0.029826 0.007636 0.000168 0.002226 0.080169 0.074024 -0.033007 0.066641 -0.007880 0.002226 -0.097150 -0.041943 -0.077026 0.000749 -0.003342 0.002233 0.007107 0.047784 -0.005441 -0.022468 0.000506 0.002233
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>36</cols>
<dt>d</dt>
<data>
-0.003529 0.033681 -0.000911 -0.007743 -0.037200 0.000000 -0.005259 0.055039 -0.008297 0.010414 -0.011954 0.000000 -0.068901 -0.022836 -0.030346 0.004620 0.017257 -0.001155 0.002734 -0.010585 0.003565 0.023064 0.022031 -0.006192 -0.010850 -0.002344 0.019545 0.003354 0.037657 -0.006192 -0.023179 -0.013982 -0.001307 -0.017693 0.021957 -0.006270
0.021911 0.059344 0.022705 0.018792 0.004861 0.000000 0.006964 0.042521 0.020365 0.025462 0.020532 0.000000 -0.030913 -0.020844 -0.003112 0.047553 0.006414 -0.001155 0.022087 -0.052199 0.044854 0.011751 0.004036 -0.006192 0.012970 -0.055056 0.023584 0.009608 -0.003752 -0.006192 -0.055130 -0.004727 0.006673 -0.035085 0.002012 -0.006270
0.017403 0.067919 0.014133 0.061441 -0.030043 0.000000 -0.033465 0.013019 -0.062063 0.068071 -0.031283 0.000000 -0.000317 -0.010707 -0.012928 0.050139 -0.003847 -0.001155 0.017336 -0.055735 0.026061 -0.022762 0.005939 -0.006192 0.000509 -0.034793 0.014873 -0.060372 0.004144 -0.006192 -0.025685 0.017788 0.038695 -0.063791 0.012379 -0.006270
-0.009216 0.046392 0.093156 0.051596 0.015172 0.000000 -0.025089 0.076428 -0.022662 0.007987 -0.010947 0.000000 0.004052 0.089563 -0.058307 0.038048 -0.021146 -0.001155 -0.014965 0.011507 -0.035840 0.017043 -0.027260 -0.006192 -0.033486 -0.014776 -0.015748 -0.038476 0.026422 -0.006192 -0.021046 0.018520 -0.016436 -0.043549 0.018086 -0.006270
-0.049385 -0.002097 0.032459 -0.010717 0.063927 0.005995 -0.018980 0.050001 -0.008589 0.019592 0.054202 0.005995 0.088225 0.044420 -0.011184 -0.013606 0.020920 0.004840 0.050994 -0.020787 -0.026238 -0.063000 -0.002088 -0.000197 -0.079609 -0.020892 -0.019301 -0.024991 0.025028 -0.000197 -0.062111 0.034609 -0.079405 -0.007748 0.003901 -0.000275
-0.027960 -0.092957 -0.013899 -0.033209 0.039590 0.003956 -0.019406 -0.058514 -0.003825 0.005779 0.077587 0.003956 0.148269 -0.004853 0.014381 0.037221 0.025150 0.002801 0.074261 -0.084000 -0.017614 -0.035363 0.007827 -0.002236 -0.041119 -0.003444 0.050194 -0.018416 -0.020543 -0.002236 -0.005724 0.120930 0.044191 -0.010493 -0.017839 -0.002314
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>36</cols>
<dt>d</dt>
<data>
-0.019354 0.002049 0.044897 0.052843 -0.003685 -0.000000 0.037786 0.048640 0.028332 0.053092 -0.031160 -0.000000 0.020231 0.029113 -0.044719 0.051004 -0.047804 -0.000636 -0.048186 0.008161 0.086181 0.050993 -0.012847 -0.001161 -0.096470 -0.019998 0.136655 0.035757 -0.002099 -0.001176 0.005585 0.032046 -0.049006 -0.014162 0.001883 -0.001176
0.043226 -0.002460 0.017417 0.015525 -0.017666 -0.000000 0.008726 0.013327 -0.016920 0.040783 -0.057074 -0.000000 0.036613 0.029563 -0.089424 0.019299 -0.061486 -0.000636 0.143699 0.027438 -0.042308 0.010220 -0.076558 -0.001161 -0.007610 -0.094000 0.125371 0.030822 -0.021089 -0.001176 -0.045975 -0.036898 0.048149 -0.039583 0.019375 -0.001176
-0.013854 0.012584 0.041245 -0.040503 0.014012 -0.000000 -0.042551 0.065055 0.024960 0.001029 -0.017198 -0.000000 -0.035761 0.021811 -0.049483 0.003630 -0.035790 -0.000636 0.051848 -0.030129 -0.072572 0.045163 -0.063565 -0.001161 0.099155 -0.090591 0.018341 0.016746 -0.028874 -0.001176 -0.039393 -0.071011 0.034551 -0.008735 0.010096 -0.001176
0.014396 -0.016068 -0.027097 -0.025921 -0.014577 -0.000000 -0.002401 -0.020234 0.023208 0.002759 -0.034607 -0.000000 0.027505 -0.027617 -0.002025 0.018327 -0.029231 -0.000636 0.003193 -0.049376 -0.035716 -0.011063 -0.040534 -0.001161 0.064037 -0.019678 -0.017128 -0.004455 0.005117 -0.001176 -0.035859 -0.056258 0.043619 -0.013651 0.003895 -0.001176
-0.030598 0.065976 -0.013929 0.011292 -0.011853 -0.000000 -0.017086 -0.005863 -0.024399 0.002706 -0.044234 -0.000000 -0.021291 -0.035587 -0.023540 0.000292 0.005918 -0.000636 -0.020510 -0.065917 -0.001723 -0.031525 0.001854 -0.001161 0.024844 0.009218 -0.001909 0.029383 0.001899 -0.001176 -0.016668 -0.021971 -0.040726 -0.023344 0.004111 -0.001176
-0.000030 -0.030537 0.024423 0.002688 0.020644 -0.000000 0.009335 0.038295 0.002837 0.044574 0.012185 -0.000000 -0.004579 -0.035709 0.000249 0.027138 0.017767 -0.000636 -0.031304 -0.050402 0.038180 -0.025012 0.003539 -0.001161 -0.018784 0.052594 0.028083 0.010725 -0.024803 -0.001176 -0.049366 0.024284 -0.035411 -0.006738 -0.063738 -0.001176
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>36</cols>
<dt>d</dt>
<data>
0.021170 0.029079 0.015591 -0.022294 -0.039663 -0.000016 -0.019944 -0.045683 -0.034638 0.019049 -0.004449 -0.000007 -0.024018 -0.048769 -0.000161 0.038597 0.026524 -0.000007 0.015951 0.028780 -0.028243 0.046802 0.009707 -0.000007 0.026339 -0.007171 0.023833 -0.031929 -0.002443 -0.000003 0.035581 -0.011898 0.018401 0.024981 -0.016367 0.000000
0.012860 -0.011878 -0.024475 -0.040362 0.008022 -0.000016 0.040407 -0.061399 -0.083169 -0.003133 0.007651 -0.000007 0.012848 -0.026406 0.061941 0.043339 0.021433 -0.000007 -0.018918 0.051492 0.062515 0.020918 0.044222 -0.000007 -0.019326 0.025020 0.004053 -0.026164 0.026920 -0.000003 -0.043886 0.031241 -0.014491 0.016077 -0.039644 0.000000
-0.029654 -0.036663 -0.002982 -0.072147 0.054005 -0.000016 -0.017817 -0.042967 0.022499 -0.025729 0.039054 -0.000007 0.046944 0.040167 -0.008446 0.048370 0.018073 -0.000007 0.004891 0.022092 0.018956 0.036528 0.022739 -0.000007 -0.011142 0.022985 0.024431 0.020315 -0.008867 -0.000003 0.008735 0.007741 -0.015990 0.015456 0.002906 0.000000
-0.069296 -0.095888 0.002166 -0.039041 0.021231 -0.000016 -0.037640 -0.027183 0.036575 -0.013082 0.009551 -0.000007 0.044677 0.083796 0.001620 -0.009417 0.019215 -0.000007 -0.018055 0.103833 -0.012772 0.037286 0.009127 -0.000007 0.009165 0.076299 -0.004383 0.031398 -0.012957 -0.000003 -0.046211 0.061804 -0.030977 0.005037 -0.012095 0.000000
-0.100664 -0.040981 0.052799 -0.039174 -0.016274 -0.000016 -0.106739 -0.008794 0.018137 -0.013051 -0.003323 -0.000007 0.011169 0.062742 0.028423 0.003289 0.015976 -0.000007 0.001051 -0.001106 0.065687 0.017969 -0.004630 -0.000007 0.023187 0.035657 0.016588 0.008999 -0.027617 -0.000003 -0.019144 0.058362 -0.004406 -0.002668 -0.043066 0.000000
-0.046272 0.094981 -0.028772 -0.027335 -0.031100 -0.000962 -0.012879 -0.083856 0.001562 -0.026352 0.027410 -0.000952 0.114693 -0.031190 0.059863 -0.003950 0.005397 -0.000952 0.051480 0.028681 0.027052 0.026378 -0.014243 -0.000952 -0.033441 0.020003 0.000622 -0.000251 0.014514 -0.000949 -0.002836 0.032140 0.005763 0.001585 -0.002796 -0.000946
</data>
</_>
<_ type_id="opencv-matrix">
<rows>6</rows>
<cols>36</cols>
<dt>d</dt>
<data>
-0.083431 0.081622 -0.001544 0.011238 0.001836 0.010409 -0.065606 0.074778 0.021422 0.003913 -0.004796 0.010409 0.011651 -0.055869 0.019998 -0.054038 0.011720 0.019800 0.099586 -0.017274 0.019538 -0.017701 -0.035477 0.019800 -0.001721 0.017864 -0.050973 0.033609 0.001407 0.019800 0.047545 -0.006025 -0.061998 -0.009210 0.021460 0.019722
-0.066393 0.089669 -0.009781 -0.006694 0.007239 0.010361 -0.003630 0.093098 0.005906 -0.003877 0.007021 0.010361 0.008695 -0.085962 0.032898 -0.047381 0.014830 0.019752 0.083495 -0.024639 -0.023373 -0.008959 0.014698 0.019752 -0.028801 -0.033164 -0.040899 0.010514 0.005670 0.019752 0.010432 0.005711 0.008422 -0.015012 0.000458 0.019675
-0.067688 0.070383 0.005323 -0.023971 -0.006470 0.006292 0.060624 0.013021 -0.017411 -0.006111 -0.005468 0.006292 -0.021585 -0.073514 0.002038 -0.006220 0.016127 0.015683 -0.002940 0.020277 0.015077 0.009960 0.017898 0.015683 -0.048015 -0.035882 -0.022834 -0.021606 -0.013086 0.015683 -0.010572 -0.001782 0.036871 -0.042538 -0.026141 0.015605
-0.021598 0.075441 -0.011637 0.020665 -0.021512 0.006292 0.017886 -0.010062 0.003163 0.014320 0.007018 0.006292 -0.089322 -0.058203 -0.006971 0.000649 0.001914 0.015683 -0.031087 0.082392 0.011933 0.035209 -0.000867 0.015683 -0.043724 -0.037431 -0.031259 0.023254 -0.010678 0.015683 -0.032164 0.021662 0.046275 -0.002189 -0.046718 0.015605
-0.004835 0.031210 0.033003 0.003386 -0.013613 0.012291 -0.007739 0.009695 0.031717 0.013363 -0.000074 0.012291 -0.104426 -0.012598 0.085214 -0.006728 0.022584 0.021682 -0.084411 0.122767 0.013357 -0.001938 -0.019305 0.021682 -0.144592 -0.038754 -0.001773 -0.028410 0.022557 0.021682 -0.041457 -0.001343 0.034994 -0.020746 -0.002555 0.021605
-0.075588 0.055948 0.026477 -0.035251 0.060991 0.007427 0.013913 0.033529 0.006132 0.011086 0.036771 0.007427 0.028571 0.008127 0.053569 -0.010739 0.035586 0.015807 -0.006204 0.088755 0.022158 -0.030508 0.026072 0.015807 -0.023523 0.073615 -0.028127 -0.015345 0.060076 0.015807 -0.004357 0.099503 -0.019565 -0.011215 0.068908 0.015729
</data>
</_>
</PartPCAFilters>
<PrunThreshold>
<_>
-6.850464 -6.793309 -6.912827 -5.803307 -5.874741 -4.743514 -4.771012 -4.384721 -4.399468 -3.625808 -3.653779 -3.232490 -3.254691 -2.797562 -2.965886 -2.658716 -2.761589 -2.543310 -2.543310 -2.249782 -2.189291 -2.014064 -2.014064 -1.613193 -1.613193 -1.410005 -1.410005 -1.116263 -1.210045 -1.067070 -1.443769 -0.848852 -0.848852 -0.688849 -0.721822 -0.500000
</_>
<_>
-6.850464 -6.793309 -6.912827 -5.803307 -5.874741 -4.743514 -4.771012 -4.384721 -4.399468 -3.625808 -3.653779 -3.232490 -3.254691 -2.797562 -2.965886 -2.658716 -2.761589 -2.543310 -2.543310 -2.249782 -2.189291 -2.014064 -2.014064 -1.613193 -1.613193 -1.410005 -1.410005 -1.116263 -1.210045 -1.067070 -1.443769 -0.848852 -0.848852 -0.688849 -0.721822 -0.500000
</_>
</PrunThreshold>
<Anchor>
<_>
2.000000 0.000000
</_>
<_>
0.000000 24.000000
</_>
<_>
4.000000 5.000000
</_>
<_>
4.000000 18.000000
</_>
<_>
0.000000 13.000000
</_>
<_>
0.000000 6.000000
</_>
<_>
4.000000 12.000000
</_>
<_>
4.000000 24.000000
</_>
<_>
2.000000 0.000000
</_>
<_>
4.000000 24.000000
</_>
<_>
0.000000 5.000000
</_>
<_>
0.000000 18.000000
</_>
<_>
4.000000 13.000000
</_>
<_>
4.000000 6.000000
</_>
<_>
0.000000 12.000000
</_>
<_>
0.000000 24.000000
</_>
</Anchor>
<Deformation>
<_>
0.024528 -0.003497 0.041338 -0.008311
</_>
<_>
0.024796 -0.008092 0.019619 0.004872
</_>
<_>
0.020152 0.007819 0.042346 -0.019964
</_>
<_>
0.034107 0.009676 0.021890 0.000311
</_>
<_>
0.025096 0.002402 0.027100 0.011309
</_>
<_>
0.019926 0.003670 0.031569 -0.023732
</_>
<_>
0.033039 -0.006518 0.021318 0.004460
</_>
<_>
0.018722 0.013806 0.019424 0.002923
</_>
<_>
0.024528 0.003497 0.041338 -0.008311
</_>
<_>
0.024796 0.008092 0.019619 0.004872
</_>
<_>
0.020152 -0.007819 0.042346 -0.019964
</_>
<_>
0.034107 -0.009676 0.021890 0.000311
</_>
<_>
0.025096 -0.002402 0.027100 0.011309
</_>
<_>
0.019926 -0.003670 0.031569 -0.023732
</_>
<_>
0.033039 0.006518 0.021318 0.004460
</_>
<_>
0.018722 -0.013806 0.019424 0.002923
</_>
</Deformation>
<NumParts>
8.000000 8.000000 </NumParts>
<PartOrder>
<_>
0.000000 8.000000 1.000000 5.000000 2.000000 3.000000 4.000000 6.000000 7.000000 0.000000 8.000000 1.000000 5.000000 2.000000 3.000000 4.000000 6.000000 7.000000
</_>
<_>
0.000000 8.000000 1.000000 5.000000 2.000000 3.000000 4.000000 6.000000 7.000000 0.000000 8.000000 1.000000 5.000000 2.000000 3.000000 4.000000 6.000000 7.000000
</_>
</PartOrder>
<LocationWeight>
<_>
0.000000 -0.190969 0.191105
</_>
<_>
0.000000 -0.190969 0.191105
</_>
</LocationWeight>
</opencv_storage>
modules/dpm/src/dpm_cascade.cpp
+561
View File
@@ -0,0 +1,561 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2015, Itseez Inc, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Itseez Inc or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "dpm_cascade.hpp"
#include "dpm_nms.hpp"
#include <limits>
#include <fstream>
#include <iostream>
#include <stdio.h>
using namespace std;
namespace cv
{
namespace dpm
{
void DPMCascade::loadCascadeModel(const string &modelPath)
{
// load cascade model from xml
bool is_success = model.deserialize(modelPath);
if (!is_success)
{
string errorMessage = format("Unable to parse the model: %s", modelPath.c_str());
CV_Error(cv::Error::StsBadArg, errorMessage);
}
model.initModel();
}
void DPMCascade::initDPMCascade()
{
// compute the size of temporary storage needed by cascade
int nlevels = (int) pyramid.size();
int numPartFilters = model.getNumPartFilters();
int numDefParams = model.getNumDefParams();
featDimsProd.resize(nlevels);
tempStorageSize = 0;
for (int i = 0; i < nlevels; i++)
{
int w = pyramid[i].cols/feature.dimHOG;
int h = pyramid[i].rows;
featDimsProd[i] = w*h;
tempStorageSize += w*h;
}
tempStorageSize *= numPartFilters;
convValues.resize(tempStorageSize);
pcaConvValues.resize(tempStorageSize);
dtValues.resize(tempStorageSize);
pcaDtValues.resize(tempStorageSize);
fill(convValues.begin(), convValues.end(), -numeric_limits<double>::infinity());
fill(pcaConvValues.begin(), pcaConvValues.end(), -numeric_limits<double>::infinity());
fill(dtValues.begin(), dtValues.end(), -numeric_limits<double>::infinity());
fill(pcaDtValues.begin(), pcaDtValues.end(), -numeric_limits<double>::infinity());
// each pyramid (convolution and distance transform) is stored
// in a 1D array. Since pyramid levels have different sizes,
// we build an array of offset values in order to index by
// level. The last offset is the total length of the pyramid
// storage array.
convLevelOffset.resize(nlevels + 1);
dtLevelOffset.resize(nlevels + 1);
convLevelOffset[0] = 0;
dtLevelOffset[0] = 0;
for (int i = 1; i < nlevels + 1; i++)
{
convLevelOffset[i] = convLevelOffset[i-1] + numPartFilters*featDimsProd[i-1];
dtLevelOffset[i] = dtLevelOffset[i-1] + numDefParams*featDimsProd[i-1];
}
// cache of precomputed deformation costs
defCostCacheX.resize(numDefParams);
defCostCacheY.resize(numDefParams);
for (int i = 0; i < numDefParams; i++)
{
vector< double > def = model.defs[i];
CV_Assert((int) def.size() >= 4);
defCostCacheX[i].resize(2*halfWindowSize + 1);
defCostCacheY[i].resize(2*halfWindowSize + 1);
for (int j = 0; j < 2*halfWindowSize + 1; j++)
{
int delta = j - halfWindowSize;
int deltaSquare = delta*delta;
defCostCacheX[i][j] = -def[0]*deltaSquare - def[1]*delta;
defCostCacheY[i][j] = -def[2]*deltaSquare - def[3]*delta;
}
}
dtArgmaxX.resize(dtLevelOffset[nlevels]);
pcaDtArgmaxX.resize(dtLevelOffset[nlevels]);
dtArgmaxY.resize(dtLevelOffset[nlevels]);
pcaDtArgmaxY.resize(dtLevelOffset[nlevels]);
}
vector< vector<double> > DPMCascade::detect(Mat &image)
{
if (image.channels() == 1)
cvtColor(image, image, COLOR_GRAY2BGR);
if (image.depth() != CV_64F)
image.convertTo(image, CV_64FC3);
// compute features
computeFeatures(image);
// pre-allocate storage
initDPMCascade();
// cascade process
vector< vector<double> > detections;
process(detections);
// non-maximum suppression
NonMaximumSuppression nms;
nms.process(detections, 0.5);
return detections;
}
void DPMCascade::computeFeatures(const Mat &im)
{
// initialize feature pyramid
PyramidParameter params;
params.padx = model.maxSizeX;
params.pady = model.maxSizeY;
params.interval = model.interval;
params.binSize = model.sBin;
feature = Feature(params);
// compute pyramid
feature.computeFeaturePyramid(im, pyramid);
// compute projected pyramid
feature.projectFeaturePyramid(model.pcaCoeff, pyramid, pcaPyramid);
}
void DPMCascade::computeLocationScores(vector< vector< double > > &locationScores)
{
vector< vector < double > > locationWeight = model.locationWeight;
CV_Assert((int)locationWeight.size() == model.numComponents);
Mat locationFeature;
int nlevels = (int) pyramid.size();
feature.computeLocationFeatures(nlevels, locationFeature);
locationScores.resize(model.numComponents);
for (int comp = 0; comp < model.numComponents; comp++)
{
locationScores[comp].resize(locationFeature.cols);
for (int level = 0; level < locationFeature.cols; level++)
{
double val = 0;
for (int k = 0; k < locationFeature.rows; k++)
val += locationWeight[comp][k]*
locationFeature.at<double>(k, level);
locationScores[comp][level] = val;
}
}
}
void DPMCascade::computeRootPCAScores(vector< vector< Mat > > &rootScores)
{
PyramidParameter params = feature.getPyramidParameters();
rootScores.resize(model.numComponents);
int nlevels = (int) pyramid.size();
int interval = params.interval;
for (int comp = 0; comp < model.numComponents; comp++)
{
rootScores[comp].resize(nlevels);
ParalComputeRootPCAScores paralTask(pcaPyramid, model.rootPCAFilters[comp],
model.pcaDim, rootScores[comp]);
parallel_for_(Range(interval, nlevels), paralTask);
}
}
ParalComputeRootPCAScores::ParalComputeRootPCAScores(
const vector< Mat > &pcaPyrad,
const Mat &f,
int dim,
vector< Mat > &sc):
pcaPyramid(pcaPyrad),
filter(f),
pcaDim(dim),
scores(sc)
{
}
void ParalComputeRootPCAScores::operator() (const Range &range) const
{
for (int level = range.start; level != range.end; level++)
{
Mat feat = pcaPyramid[level];
// compute size of output
int height = feat.rows - filter.rows + 1;
int width = (feat.cols - filter.cols) / pcaDim + 1;
Mat result = Mat::zeros(Size(width, height), CV_64F);
// convolution engine
ConvolutionEngine convEngine;
convEngine.convolve(feat, filter, pcaDim, result);
scores[level] = result;
}
}
void DPMCascade::process( vector< vector<double> > &dets)
{
PyramidParameter params = feature.getPyramidParameters();
int interval = params.interval;
int padx = params.padx;
int pady = params.pady;
vector<double> scales = params.scales;
int nlevels = (int)pyramid.size() - interval;
CV_Assert(nlevels > 0);
// keep track of the PCA scores for each PCA filter
vector< vector< double > > pcaScore(model.numComponents);
for (int comp = 0; comp < model.numComponents; comp++)
pcaScore[comp].resize(model.numParts[comp]+1);
// compute location scores
vector< vector< double > > locationScores;
computeLocationScores(locationScores);
// compute root PCA scores
vector< vector< Mat > > rootPCAScores;
computeRootPCAScores(rootPCAScores);
// process each model component and pyramid level
for (int comp = 0; comp < model.numComponents; comp++)
{
for (int plevel = 0; plevel < nlevels; plevel++)
{
// root filter pyramid level
int rlevel = plevel + interval;
double bias = model.bias[comp] + locationScores[comp][rlevel];
// get the scores of the first PCA filter
Mat rtscore = rootPCAScores[comp][rlevel];
// process each location in the current pyramid level
for (int rx = (int)ceil(padx/2.0); rx < rtscore.cols - (int)ceil(padx/2.0); rx++)
{
for (int ry = (int)ceil(pady/2.0); ry < rtscore.rows - (int)ceil(pady/2.0); ry++)
{
// get stage 0 score
double score = rtscore.at<double>(ry, rx) + bias;
// record PCA score
pcaScore[comp][0] = score - bias;
// cascade stage 1 through 2*numparts + 2
int stage = 1;
int numstages = 2*model.numParts[comp] + 2;
for(; stage < numstages; stage++)
{
double t = model.prunThreshold[comp][2*stage-1];
// check for hypothesis pruning
if (score < t)
break;
// pca == 1 if place filters
// pca == 0 if place non-pca filters
bool isPCA = (stage < model.numParts[comp] + 1 ? true : false);
// get the part index
// root parts have index -1, none-root part are indexed 0:numParts-1
int part = model.partOrder[comp][stage] - 1;// partOrder
if (part == -1)
{
// calculate the root non-pca score
// and replace the PCA score
double rscore = 0.0;
if (isPCA)
{
rscore = convolutionEngine.convolve(pcaPyramid[rlevel],
model.rootPCAFilters[comp],
model.pcaDim, rx, ry);
}
else
{
rscore = convolutionEngine.convolve(pyramid[rlevel],
model.rootFilters[comp],
model.numFeatures, rx, ry);
}
score += rscore - pcaScore[comp][0];
}
else
{
// place a non-root filter
int pId = model.pFind[comp][part];
int px = 2*rx + (int)model.anchors[pId][0];
int py = 2*ry + (int)model.anchors[pId][1];
// look up the filter and deformation model
double defThreshold =
model.prunThreshold[comp][2*stage] - score;
double ps = computePartScore(plevel, pId, px, py,
isPCA, defThreshold);
if (isPCA)
{
// record PCA filter score
pcaScore[comp][part+1] = ps;
// update the hypothesis score
score += ps;
}
else
{
// update the hypothesis score by replacing
// the PCA score
score += ps - pcaScore[comp][part+1];
} // isPCA == false
} // part != -1
} // stages
// check if the hypothesis passed all stages with a
// final score over the global threshold
if (stage == numstages && score >= model.scoreThresh)
{
vector<double> coords;
// compute and record image coordinates of the detection window
double scale = model.sBin/scales[rlevel];
double x1 = (rx-padx)*scale;
double y1 = (ry-pady)*scale;
double x2 = x1 + model.rootFilterDims[comp].width*scale - 1;
double y2 = y1 + model.rootFilterDims[comp].height*scale - 1;
coords.push_back(x1);
coords.push_back(y1);
coords.push_back(x2);
coords.push_back(y2);
// compute and record image coordinates of the part filters
scale = model.sBin/scales[plevel];
int featWidth = pyramid[plevel].cols/feature.dimHOG;
for (int p = 0; p < model.numParts[comp]; p++)
{
int pId = model.pFind[comp][p];
int probx = 2*rx + (int)model.anchors[pId][0];
int proby = 2*ry + (int)model.anchors[pId][1];
int offset = dtLevelOffset[plevel] +
pId*featDimsProd[plevel] +
(proby - pady)*featWidth +
probx - padx;
int px = dtArgmaxX[offset] + padx;
int py = dtArgmaxY[offset] + pady;
x1 = (px - 2*padx)*scale;
y1 = (py - 2*pady)*scale;
x2 = x1 + model.partFilterDims[p].width*scale - 1;
y2 = y1 + model.partFilterDims[p].height*scale - 1;
coords.push_back(x1);
coords.push_back(y1);
coords.push_back(x2);
coords.push_back(y2);
}
// record component number and score
coords.push_back(comp + 1);
coords.push_back(score);
dets.push_back(coords);
}
} // ry
} // rx
} // for each pyramid level
} // for each component
}
double DPMCascade::computePartScore(int plevel, int pId, int px, int py, bool isPCA, double defThreshold)
{
// remove virtual padding
PyramidParameter params = feature.getPyramidParameters();
px -= params.padx;
py -= params.pady;
// check if already computed
int levelOffset = dtLevelOffset[plevel];
int locationOffset = pId*featDimsProd[plevel]
+ py*pyramid[plevel].cols/feature.dimHOG
+ px;
int dtBaseOffset = levelOffset + locationOffset;
double val;
if (isPCA)
val = pcaDtValues[dtBaseOffset];
else
val = dtValues[dtBaseOffset];
if (val > -numeric_limits<double>::infinity())
return val;
// Nope, define the bounds of the convolution and
// distance transform region
int xstart = px - halfWindowSize;
xstart = (xstart < 0 ? 0 : xstart);
int xend = px + halfWindowSize;
int ystart = py - halfWindowSize;
ystart = (ystart < 0 ? 0 : ystart);
int yend = py + halfWindowSize;
int featWidth = pyramid[plevel].cols/feature.dimHOG;
int featHeight = pyramid[plevel].rows;
int filterWidth = model.partFilters[pId].cols/feature.dimHOG;
int filterHeight = model.partFilters[pId].rows;
xend = (filterWidth + xend > featWidth)
? featWidth - filterWidth
: xend;
yend = (filterHeight + yend > featHeight)
? featHeight - filterHeight
: yend;
// do convolution and distance transform in region
// [xstar, xend, ystart, yend]
levelOffset = convLevelOffset[plevel];
locationOffset = pId*featDimsProd[plevel];
int convBaseOffset = levelOffset + locationOffset;
for (int y = ystart; y <= yend; y++)
{
int loc = convBaseOffset + y*featWidth + xstart - 1;
for (int x = xstart; x <= xend; x++)
{
loc++;
// skip if already computed
if (isPCA)
{
if (pcaConvValues[loc] > -numeric_limits<double>::infinity())
continue;
}
else if(convValues[loc] > -numeric_limits<double>::infinity())
continue;
// check for deformation pruning
double defCost = defCostCacheX[pId][px - x + halfWindowSize]
+ defCostCacheY[pId][py - y + halfWindowSize];
if (defCost < defThreshold)
continue;
if (isPCA)
{
pcaConvValues[loc] = convolutionEngine.convolve
(pcaPyramid[plevel], model.partPCAFilters[pId],
model.pcaDim, x, y);
}
else
{
convValues[loc] = convolutionEngine.convolve
(pyramid[plevel], model.partFilters[pId],
model.numFeatures, x, y);
}
} // y
} // x
// do distance transform over the region.
// the region is small enought that brut force DT
// is the fastest method
double max = -numeric_limits<double>::infinity();
int xargmax = 0;
int yargmax = 0;
for (int y = ystart; y <= yend; y++)
{
int loc = convBaseOffset + y*featWidth + xstart - 1;
for (int x = xstart; x <= xend; x++)
{
loc++;
double v;
if (isPCA)
v = pcaConvValues[loc];
else
v = convValues[loc];
v += defCostCacheX[pId][px - x + halfWindowSize]
+ defCostCacheY[pId][py - y + halfWindowSize];
if (v > max)
{
max = v;
xargmax = x;
yargmax = y;
} // if v
} // for x
} // for y
// record max and argmax for DT
if (isPCA)
{
pcaDtArgmaxX[dtBaseOffset] = xargmax;
pcaDtArgmaxY[dtBaseOffset] = yargmax;
pcaDtValues[dtBaseOffset] = max;
}
else
{
dtArgmaxX[dtBaseOffset] = xargmax;
dtArgmaxY[dtBaseOffset] = yargmax;
dtValues[dtBaseOffset] = max;
}
return max;
}
} // namespace dpm
} // namespace cv
modules/dpm/src/dpm_cascade.hpp
+156
View File
@@ -0,0 +1,156 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2015, Itseez Inc, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Itseez Inc or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __DPM_CASCADE__
#define __DPM_CASCADE__
#include "dpm_model.hpp"
#include "dpm_feature.hpp"
#include "dpm_convolution.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/core.hpp"
#include <string>
#include <vector>
namespace cv
{
namespace dpm
{
/** @brief This class is the main process of DPM cascade
*/
class DPMCascade
{
private:
// pyramid level offset for covolution
std::vector< int > convLevelOffset;
// pyramid level offset for distance transform
std::vector< int > dtLevelOffset;
// convolution values
std::vector< double > convValues;
std::vector< double > pcaConvValues;
// distance transform values
std::vector< double > dtValues;
std::vector< double > pcaDtValues;
// distance transform argmax, x dimension
std::vector< int > dtArgmaxX;
std::vector< int > pcaDtArgmaxX;
// distance transform argmax, y dimension
std::vector< int > dtArgmaxY;
std::vector< int > pcaDtArgmaxY;
// half-width of distance transform window
static const int halfWindowSize = 4;
// the amount of temporary storage of cascade
int tempStorageSize;
// precomputed deformation costs
std::vector< std::vector< double > > defCostCacheX;
std::vector< std::vector< double > > defCostCacheY;
// DPM cascade model
CascadeModel model;
// feature process
Feature feature;
// feature pyramid
std::vector< Mat > pyramid;
// projected (PCA) pyramid;
std::vector< Mat > pcaPyramid;
// number of positions in each pyramid level
std::vector< int > featDimsProd;
// convolution engine
ConvolutionEngine convolutionEngine;
public:
// constructor
DPMCascade () {}
// destructor
virtual ~DPMCascade () {}
// load cascade mode and initialize cascade
void loadCascadeModel(const std::string &modelPath);
// compute feature pyramid and projected feature pyramid
void computeFeatures(const Mat &im);
// compute root PCA scores
void computeRootPCAScores(std::vector< std::vector< Mat > > &rootScores);
// lookup or compute the score of a part at a location
double computePartScore(int plevel, int pId, int px, int py, bool isPCA, double defThreshold);
// compute location scores
void computeLocationScores(std::vector< std::vector< double > > &locctionScores);
// initialization pre-allocate storage
void initDPMCascade();
// cascade process
void process(std::vector< std::vector<double> > &detections);
// detect object from image
std::vector< std::vector<double> > detect(Mat &image);
};
/** @brief This class convolves root PCA feature pyramid
* and root PCA filters in parallel using Intel Threading
* Building Blocks (TBB)
*/
class ParalComputeRootPCAScores : public ParallelLoopBody
{
public:
// constructor
ParalComputeRootPCAScores(const std::vector< Mat > &pcaPyramid, const Mat &filter,\
int dim, std::vector< Mat > &scores);
// parallel loop body
void operator() (const Range &range) const CV_OVERRIDE;
ParalComputeRootPCAScores(const ParalComputeRootPCAScores &pComp);
private:
const std::vector< Mat > &pcaPyramid;
const Mat &filter;
int pcaDim;
std::vector< Mat > &scores;
};
} // namespace dpm
} // namespace cv
#endif // __DPM_CASCADE_
modules/dpm/src/dpm_cascade_detector.cpp
+178
View File
@@ -0,0 +1,178 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2015, Itseez Inc, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Itseez Inc or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "precomp.hpp"
#include "dpm_cascade.hpp"
using namespace std;
namespace cv
{
namespace dpm
{
class DPMDetectorImpl CV_FINAL : public DPMDetector
{
public:
DPMDetectorImpl( const vector<string>& filenames, const vector<string>& classNames=vector<string>() );
~DPMDetectorImpl() CV_OVERRIDE;
bool isEmpty() const CV_OVERRIDE;
void detect(Mat &image, CV_OUT vector<ObjectDetection>& objects) CV_OVERRIDE;
const vector<string>& getClassNames() const CV_OVERRIDE;
size_t getClassCount() const CV_OVERRIDE;
string extractModelName( const string& filename );
private:
vector< Ptr<DPMCascade> > detectors;
vector<string> classNames;
};
Ptr<DPMDetector> DPMDetector::create(vector<string> const &filenames,
vector<string> const &classNames)
{
return makePtr<DPMDetectorImpl>(filenames, classNames);
}
DPMDetectorImpl::ObjectDetection::ObjectDetection()
: score(0.f), classID(-1) {}
DPMDetectorImpl::ObjectDetection::ObjectDetection( const Rect& _rect, float _score, int _classID )
: rect(_rect), score(_score), classID(_classID) {}
DPMDetectorImpl::DPMDetectorImpl( const vector<string>& filenames,
const vector<string>& _classNames )
{
for( size_t i = 0; i < filenames.size(); i++ )
{
const string filename = filenames[i];
if( filename.length() < 5 || filename.substr(filename.length()-4, 4) != ".xml" )
continue;
Ptr<DPMCascade> detector = makePtr<DPMCascade>();
// initialization
detector->loadCascadeModel( filename.c_str() );
if( detector )
{
detectors.push_back( detector );
if( _classNames.empty() )
{
classNames.push_back( extractModelName(filename));
}
else
classNames.push_back( _classNames[i] );
}
}
}
DPMDetectorImpl::~DPMDetectorImpl()
{
}
bool DPMDetectorImpl::isEmpty() const
{
return detectors.empty();
}
const vector<string>& DPMDetectorImpl::getClassNames() const
{
return classNames;
}
size_t DPMDetectorImpl::getClassCount() const
{
return classNames.size();
}
string DPMDetectorImpl::extractModelName( const string& filename )
{
size_t startPos = filename.rfind('/');
if( startPos == string::npos )
startPos = filename.rfind('\\');
if( startPos == string::npos )
startPos = 0;
else
startPos++;
const int extentionSize = 4; //.xml
int substrLength = (int)(filename.size() - startPos - extentionSize);
return filename.substr(startPos, substrLength);
}
void DPMDetectorImpl::detect( Mat &image,
vector<ObjectDetection> &objectDetections)
{
objectDetections.clear();
for( size_t classID = 0; classID < detectors.size(); classID++ )
{
// detect objects
vector< vector<double> > detections;
detections = detectors[classID]->detect(image);
for (unsigned int i = 0; i < detections.size(); i++)
{
ObjectDetection ds = ObjectDetection();
int s = (int)detections[i].size() - 1;
ds.score = (float)detections[i][s];
int x1 = (int)detections[i][0];
int y1 = (int)detections[i][1];
int w = (int)detections[i][2] - x1 + 1;
int h = (int)detections[i][3] - y1 + 1;
ds.rect = Rect(x1, y1, w, h);
ds.classID = (int)classID;
objectDetections.push_back(ds);
}
}
}
} // namespace cv
}
modules/dpm/src/dpm_convolution.cpp
+91
View File
@@ -0,0 +1,91 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2015, Itseez Inc, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Itseez Inc or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "dpm_convolution.hpp"
namespace cv
{
namespace dpm
{
double ConvolutionEngine::convolve(const Mat &feat, const Mat &filter,
int dimHOG, int x, int y)
{
double val = 0;
for (int yp = 0; yp < filter.rows; yp++)
{
const double *pfeat = (double*)feat.ptr(y + yp) + x * dimHOG;
const double *pfilter = (double*)filter.ptr(yp);
for (int xp = 0; xp < filter.cols; xp++)
{
val += pfeat[xp] * pfilter[xp];
}
}
return val;
}
void ConvolutionEngine::convolve(const Mat &feat, const Mat &filter,
int dimHOG, Mat &result)
{
for (int y = 0; y < result.rows; y++)
{
double *presult = (double*)result.ptr(y);
for (int x = 0; x < result.cols; x++)
{
double val = 0;
for (int yp = 0; yp < filter.rows; yp++)
{
const double *pfeat = (double*)feat.ptr(y + yp) + x * dimHOG;
const double *pfilter = (double*)filter.ptr(yp);
for (int xp = 0; xp < filter.cols; xp++)
{
val += pfeat[xp] * pfilter[xp];
}
} // yp
presult[x] = val;
} // x
} // y
}
} // namespace cv
} // namespace dpm
modules/dpm/src/dpm_convolution.hpp
+74
View File
@@ -0,0 +1,74 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2015, Itseez Inc, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Itseez Inc or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __DPM_CONVOLUTION__
#define __DPM_CONVOLUTION__
#include "opencv2/core.hpp"
#include <vector>
namespace cv
{
namespace dpm
{
/** @brief This class contains DPM model parameters
*/
class ConvolutionEngine
{
public:
// constructor
ConvolutionEngine() {}
// destructor
~ConvolutionEngine() {}
// compute convolution value at a fixed location
double convolve(const Mat &feat, const Mat &filter,
int dimHOG, int x, int y);
// compute convolution of a feature map and multiple filters
// sum the filter convolution values into results
void convolve(const Mat &feat, const Mat &filter,
int dimHOG, Mat &result);
};
} // namespace dpm
} // namespace cv
#endif //__DPM_CONVOLUTION__
modules/dpm/src/dpm_feature.cpp
+411
View File
@@ -0,0 +1,411 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2015, Itseez Inc, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Itseez Inc or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "dpm_feature.hpp"
using namespace std;
namespace cv
{
namespace dpm
{
Feature::Feature()
{
}
Feature::Feature (PyramidParameter p):params(p)
{
}
void Feature::computeFeaturePyramid(const Mat &imageM, vector< Mat > &pyramid)
{
ParalComputePyramid paralTask(imageM, pyramid, params);
paralTask.initialize();
parallel_for_(Range(0, params.interval), paralTask);
}
ParalComputePyramid::ParalComputePyramid(const Mat &inputImage, \
vector< Mat > &outputPyramid,\
PyramidParameter &p):
imageM(inputImage), pyramid(outputPyramid), params(p)
{
}
void ParalComputePyramid::initialize()
{
CV_Assert(params.interval > 0);
// scale factor between two levels
params.sfactor = pow(2.0, 1.0/params.interval);
imSize = imageM.size();
params.maxScale = 1 + (int)floor(log(min(imSize.width, imSize.height)/(float)(params.binSize*5.0))/log(params.sfactor));
if (params.maxScale < params.interval)
{
CV_Error(cv::Error::StsBadArg, "The image is too small to create a pyramid");
return;
}
pyramid.resize(params.maxScale + params.interval);
params.scales.resize(params.maxScale + params.interval);
}
void ParalComputePyramid::operator() (const Range &range) const
{
for (int i = range.start; i != range.end; i++)
{
const double scale = (double)(1.0f/pow(params.sfactor, i));
Mat imScaled;
resize(imageM, imScaled, imSize * scale);
params.scales[i] = 2*scale;
// First octave at twice the image resolution
Feature::computeHOG32D(imScaled, pyramid[i],
params.binSize/2, params.padx + 1, params.pady + 1);
// Second octave at the original resolution
if (i + params.interval <= params.maxScale)
Feature::computeHOG32D(imScaled, pyramid[i+params.interval],
params.binSize, params.padx + 1, params.pady + 1);
params.scales[i+params.interval] = scale;
// Remaining octaves
for ( int j = i + params.interval; j < params.maxScale; j += params.interval)
{
Mat imScaled2;
Size_<double> imScaledSize = imScaled.size();
resize(imScaled, imScaled2, imScaledSize*0.5);
imScaled = imScaled2;
Feature::computeHOG32D(imScaled2, pyramid[j+params.interval],
params.binSize, params.padx + 1, params.pady + 1);
params.scales[j+params.interval] = params.scales[j]*0.5;
}
}
}
void Feature::computeHOG32D(const Mat &imageM, Mat &featM, const int sbin, const int pad_x, const int pad_y)
{
CV_Assert(pad_x >= 0);
CV_Assert(pad_y >= 0);
CV_Assert(imageM.channels() == 3);
CV_Assert(imageM.depth() == CV_64F);
// epsilon to avoid division by zero
const double eps = 0.0001;
// number of orientations
const int numOrient = 18;
// unit vectors to compute gradient orientation
const double uu[9] = {1.000, 0.9397, 0.7660, 0.5000, 0.1736, -0.1736, -0.5000, -0.7660, -0.9397};
const double vv[9] = {0.000, 0.3420, 0.6428, 0.8660, 0.9848, 0.9848, 0.8660, 0.6428, 0.3420};
// image size
const Size imageSize = imageM.size();
// block size
int bW = cvRound((double)imageSize.width/(double)sbin);
int bH = cvRound((double)imageSize.height/(double)sbin);
const Size blockSize(bW, bH);
// size of HOG features
int oW = max(blockSize.width-2, 0) + 2*pad_x;
int oH = max(blockSize.height-2, 0) + 2*pad_y;
Size outSize = Size(oW, oH);
// size of visible
const Size visible = blockSize*sbin;
// initialize historgram, norm, output feature matrices
Mat histM = Mat::zeros(Size(blockSize.width*numOrient, blockSize.height), CV_64F);
Mat normM = Mat::zeros(Size(blockSize.width, blockSize.height), CV_64F);
featM = Mat::zeros(Size(outSize.width*dimHOG, outSize.height), CV_64F);
// get the stride of each matrix
const size_t imStride = imageM.step1();
const size_t histStride = histM.step1();
const size_t normStride = normM.step1();
const size_t featStride = featM.step1();
// calculate the zero offset
const double* im = imageM.ptr<double>(0);
double* const hist = histM.ptr<double>(0);
double* const norm = normM.ptr<double>(0);
double* const feat = featM.ptr<double>(0);
for (int y = 1; y < visible.height - 1; y++)
{
for (int x = 1; x < visible.width - 1; x++)
{
// OpenCV uses an interleaved format: BGR-BGR-BGR
const double* s = im + 3*min(x, imageM.cols-2) + min(y, imageM.rows-2)*imStride;
// blue image channel
double dyb = *(s+imStride) - *(s-imStride);
double dxb = *(s+3) - *(s-3);
double vb = dxb*dxb + dyb*dyb;
// green image channel
s += 1;
double dyg = *(s+imStride) - *(s-imStride);
double dxg = *(s+3) - *(s-3);
double vg = dxg*dxg + dyg*dyg;
// red image channel
s += 1;
double dy = *(s+imStride) - *(s-imStride);
double dx = *(s+3) - *(s-3);
double v = dx*dx + dy*dy;
// pick the channel with the strongest gradient
if (vg > v) { v = vg; dx = dxg; dy = dyg; }
if (vb > v) { v = vb; dx = dxb; dy = dyb; }
// snap to one of the 18 orientations
double best_dot = 0;
int best_o = 0;
for (int o = 0; o < (int)numOrient/2; o++)
{
double dot = uu[o]*dx + vv[o]*dy;
if (dot > best_dot)
{
best_dot = dot;
best_o = o;
}
else if (-dot > best_dot)
{
best_dot = -dot;
best_o = o + (int)(numOrient/2);
}
}
// add to 4 historgrams around pixel using bilinear interpolation
double yp = ((double)y+0.5)/(double)sbin - 0.5;
double xp = ((double)x+0.5)/(double)sbin - 0.5;
int iyp = (int)floor(yp);
int ixp = (int)floor(xp);
double vy0 = yp - iyp;
double vx0 = xp - ixp;
double vy1 = 1.0 - vy0;
double vx1 = 1.0 - vx0;
v = sqrt(v);
// fill the value into the 4 neighborhood cells
if (iyp >= 0 && ixp >= 0)
*(hist + iyp*histStride + ixp*numOrient + best_o) += vy1*vx1*v;
if (iyp >= 0 && ixp+1 < blockSize.width)
*(hist + iyp*histStride + (ixp+1)*numOrient + best_o) += vx0*vy1*v;
if (iyp+1 < blockSize.height && ixp >= 0)
*(hist + (iyp+1)*histStride + ixp*numOrient + best_o) += vy0*vx1*v;
if (iyp+1 < blockSize.height && ixp+1 < blockSize.width)
*(hist + (iyp+1)*histStride + (ixp+1)*numOrient + best_o) += vy0*vx0*v;
} // for y
} // for x
// compute the energy in each block by summing over orientation
for (int y = 0; y < blockSize.height; y++)
{
const double* src = hist + y*histStride;
double* dst = norm + y*normStride;
double const* const dst_end = dst + blockSize.width;
// for each cell
while (dst < dst_end)
{
*dst = 0;
for (int o = 0; o < (int)(numOrient/2); o++)
{
*dst += (*src + *(src + numOrient/2))*
(*src + *(src + numOrient/2));
src++;
}
dst++;
src += numOrient/2;
}
}
// compute the features
for (int y = pad_y; y < outSize.height - pad_y; y++)
{
for (int x = pad_x; x < outSize.width - pad_x; x++)
{
double* dst = feat + y*featStride + x*dimHOG;
double* p, n1, n2, n3, n4;
const double* src;
p = norm + (y - pad_y + 1)*normStride + (x - pad_x + 1);
n1 = 1.0f / sqrt(*p + *(p + 1) + *(p + normStride) + *(p + normStride + 1) + eps);
p = norm + (y - pad_y)*normStride + (x - pad_x + 1);
n2 = 1.0f / sqrt(*p + *(p + 1) + *(p + normStride) + *(p + normStride + 1) + eps);
p = norm + (y- pad_y + 1)*normStride + x - pad_x;
n3 = 1.0f / sqrt(*p + *(p + 1) + *(p + normStride) + *(p + normStride + 1) + eps);
p = norm + (y - pad_y)*normStride + x - pad_x;
n4 = 1.0f / sqrt(*p + *(p + 1) + *(p + normStride) + *(p + normStride + 1) + eps);
double t1 = 0.0, t2 = 0.0, t3 = 0.0, t4 = 0.0;
// contrast-sesitive features
src = hist + (y - pad_y + 1)*histStride + (x - pad_x + 1)*numOrient;
for (int o = 0; o < numOrient; o++)
{
double val = *src;
double h1 = min(val*n1, 0.2);
double h2 = min(val*n2, 0.2);
double h3 = min(val*n3, 0.2);
double h4 = min(val*n4, 0.2);
*(dst++) = 0.5 * (h1 + h2 + h3 + h4);
src++;
t1 += h1;
t2 += h2;
t3 += h3;
t4 += h4;
}
// contrast-insensitive features
src = hist + (y - pad_y + 1)*histStride + (x - pad_x + 1)*numOrient;
for (int o = 0; o < numOrient/2; o++)
{
double sum = *src + *(src + numOrient/2);
double h1 = min(sum * n1, 0.2);
double h2 = min(sum * n2, 0.2);
double h3 = min(sum * n3, 0.2);
double h4 = min(sum * n4, 0.2);
*(dst++) = 0.5 * (h1 + h2 + h3 + h4);
src++;
}
// texture features
*(dst++) = 0.2357 * t1;
*(dst++) = 0.2357 * t2;
*(dst++) = 0.2357 * t3;
*(dst++) = 0.2357 * t4;
// truncation feature
*dst = 0;
}// for x
}// for y
// Truncation features
for (int m = 0; m < featM.rows; m++)
{
for (int n = 0; n < featM.cols; n += dimHOG)
{
if (m > pad_y - 1 && m < featM.rows - pad_y && n > pad_x*dimHOG - 1 && n < featM.cols - pad_x*dimHOG)
continue;
featM.at<double>(m, n + dimHOG - 1) = 1;
} // for x
}// for y
}
void Feature::projectFeaturePyramid(const Mat &pcaCoeff, const std::vector< Mat > &pyramid, std::vector< Mat > &projPyramid)
{
CV_Assert(dimHOG == pcaCoeff.rows);
dimPCA = pcaCoeff.cols;
projPyramid.resize(pyramid.size());
// loop for each level of the pyramid
for (unsigned int i = 0; i < pyramid.size(); i++)
{
Mat orgM = pyramid[i];
// note that the features are stored in 32-32-32
int width = orgM.cols/dimHOG;
int height = orgM.rows;
// initialize the project feature matrix
Mat projM = Mat::zeros(height, width*dimPCA, CV_64F);
//get the pointer of the matrix
double* const featOrg = orgM.ptr<double>(0);
double* const featProj = projM.ptr<double>(0);
// get the stride of each matrix
const size_t orgStride = orgM.step1();
const size_t projStride = projM.step1();
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
double* proj = featProj + y*projStride + x*dimPCA;
// for each pca dimension
for (int c = 0; c < dimPCA; c++)
{
double* org = featOrg + y*orgStride + x*dimHOG;
// dot product 32d HOG feature with the coefficient vector
for (int r = 0; r < dimHOG; r++)
{
*proj += *org * pcaCoeff.at<double>(r, c);
org++;
}
proj++;
}
} // for x
} // for y
projPyramid[i] = projM;
} // for each level of the pyramid
}
void Feature::computeLocationFeatures(const int numLevels, Mat &locFeature)
{
locFeature = Mat::zeros(Size(numLevels, 3), CV_64F);
int b = 0;
int e = min(numLevels, params.interval);
for (int x = b; x < e; x++)
locFeature.at<double>(0, x) = 1;
b = e;
e = min(numLevels, 2*e);
for (int x = b; x < e; x++)
locFeature.at<double>(1, x) = 1;
b = e;
e = min(numLevels, 3*e);
for (int x = b; x < e; x++)
locFeature.at<double>(2, x) = 1;
}
} // namespace dpm
} // namespace cv
modules/dpm/src/dpm_feature.hpp
+170
View File
@@ -0,0 +1,170 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2015, Itseez Inc, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Itseez Inc or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __DPM_FEATURE__
#define __DPM_FEATURE__
#include "opencv2/core.hpp"
#include "opencv2/imgproc.hpp"
#include <string>
#include <vector>
namespace cv
{
namespace dpm
{
// parameters of the feature pyramid
class PyramidParameter
{
public:
// number of levels per octave in feature pyramid
int interval;
// HOG cell size
int binSize;
// horizontal padding (in cells)
int padx;
// vertical padding (in cells)
int pady;
// scale factor
double sfactor;
// maximum number of scales in the pyramid
int maxScale;
// scale of each level
std::vector< double > scales;
public:
PyramidParameter()
{
// default parameters
interval = 10;
binSize = 8;
padx = 0;
pady = 0;
sfactor = 1.0;
maxScale = 0;
}
~PyramidParameter() {}
};
/** @brief This class contains DPM model parameters
*/
class Feature
{
public:
// dimension of the HOG features in a sigle cell
static const int dimHOG = 32;
// top dimPCA PCA eigenvectors
int dimPCA;
// set pyramid parameter
void setPyramidParameters(PyramidParameter val)
{
params = val;
}
// returns pyramid parameters
PyramidParameter getPyramidParameters()
{
return params;
}
// constructor
Feature ();
// constructor with parameters
Feature (PyramidParameter p);
// destrcutor
~Feature () {}
// compute feature pyramid
void computeFeaturePyramid(const Mat &imageM, std::vector< Mat > &pyramid);
// project the feature pyramid with PCA coefficient matrix
void projectFeaturePyramid(const Mat &pcaCoeff, const std::vector< Mat > &pyramid, std::vector< Mat > &projPyramid);
// compute 32 dimension HOG as described in
// "Object Detection with Discriminatively Trained Part-based Models"
// by Felzenszwalb, Girshick, McAllester and Ramanan, PAMI 2010
static void computeHOG32D(const Mat &imageM, Mat &featM, const int sbin, const int padx, const int pady);
// compute location features
void computeLocationFeatures(const int numLevels, Mat &locFeature);
private:
PyramidParameter params;
};
/** @brief This class computes feature pyramid in parallel
* using Intel Threading Building Blocks (TBB)
*/
class ParalComputePyramid : public ParallelLoopBody
{
public:
// constructor
ParalComputePyramid(const Mat &inputImage, \
std::vector< Mat > &outputPyramid,\
PyramidParameter &p);
// initializate parameters
void initialize();
// parallel loop body
void operator() (const Range &range) const CV_OVERRIDE;
private:
// image to compute feature pyramid
const Mat &imageM;
// image size
Size_<double> imSize;
// output feature pyramid
std::vector< Mat > &pyramid;
// pyramid parameters
PyramidParameter &params;
};
} // namespace dpm
} // namespace cv
#endif // __DPM_FEATURE_
modules/dpm/src/dpm_model.cpp
+207
View File
@@ -0,0 +1,207 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2015, Itseez Inc, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Itseez Inc or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "dpm_model.hpp"
namespace cv
{
namespace dpm
{
void CascadeModel::initModel()
{
CV_Assert(numComponents == (int)rootFilters.size());
// map: pFind[component][part] => part filter index
pFind.resize(numComponents);
int np = (int) partFilters.size();
rootFilterDims.resize(numComponents);
partFilterDims.resize(np);
int w, h; // width and height of the filter
int pIndex = 0; // part index
for (int comp = 0; comp < numComponents; comp++)
{
w = rootFilters[comp].cols/numFeatures;
h = rootFilters[comp].rows;
rootFilterDims[comp] = Size(w, h);
pFind[comp].resize(numParts[comp]);
for (int part = 0; part < numParts[comp]; part++)
{
w = partFilters[pIndex].cols/numFeatures;
h = partFilters[pIndex].rows;
partFilterDims[pIndex] = Size(w, h);
pFind[comp][part] = pIndex;
pIndex++;
}
}
CV_Assert(pIndex == np);
CV_Assert(pIndex == (int)anchors.size());
CV_Assert(pIndex == (int)defs.size());
}
bool CascadeModel::serialize(const std::string &filename) const
{
// open the storage container for writing
FileStorage fs;
fs.open(filename, FileStorage::WRITE);
// write the primitives
fs << "SBin" << sBin;
fs << "Interval" << interval;
fs << "MaxSizeX" << maxSizeX;
fs << "MaxSizeY" << maxSizeY;
fs << "NumComponents" << numComponents;
fs << "NumFeatures" << numFeatures;
fs << "PCADim" << pcaDim;
fs << "ScoreThreshold" << scoreThresh;
fs << "PCAcoeff" << pcaCoeff;
fs << "Bias" << bias;
// write the filters
fs << "RootFilters" << rootFilters;
fs << "RootPCAFilters" << rootPCAFilters;
fs << "PartFilters" << partFilters;
fs << "PartPCAFilters" << partPCAFilters;
// write the pruning threshold
fs << "PrunThreshold" << "[";
for (unsigned int i = 0; i < prunThreshold.size(); i++)
fs << prunThreshold[i];
fs << "]";
// write anchor points
fs << "Anchor" << "[";
for (unsigned int i = 0; i < anchors.size(); i++)
fs << anchors[i];
fs << "]";
// write deformation
fs << "Deformation" << "[";
for (unsigned int i = 0; i < defs.size(); i++)
fs << defs[i];
fs << "]";
// write number of parts
fs << "NumParts" << numParts;
// write part order
fs << "PartOrder" << "[";
for (unsigned int i = 0; i < partOrder.size(); i++)
fs << partOrder[i];
fs << "]";
// write location weight
fs << "LocationWeight" << "[";
for (unsigned int i = 0; i < locationWeight.size(); i++)
fs << locationWeight[i];
fs << "]";
fs.release();
return true;
}
bool CascadeModel::deserialize(const std::string &filename)
{
FileStorage fs;
bool is_ok = fs.open(filename, FileStorage::READ);
if (!is_ok) return false;
fs["SBin"] >> sBin;
fs["Interval"] >> interval;
fs["MaxSizeX"] >> maxSizeX;
fs["MaxSizeY"] >> maxSizeY;
fs["NumComponents"] >> numComponents;
fs["NumFeatures"] >> numFeatures;
fs["PCADim"] >> pcaDim;
fs["ScoreThreshold"] >> scoreThresh;
fs["PCAcoeff"] >> pcaCoeff;
fs["Bias"] >> bias;
fs["RootFilters"] >> rootFilters;
fs["RootPCAFilters"] >> rootPCAFilters;
fs["PartFilters"] >> partFilters;
fs["PartPCAFilters"] >> partPCAFilters;
// read pruning threshold
FileNode nodePrun = fs["PrunThreshold"];
prunThreshold.resize(nodePrun.size());
for (unsigned int i = 0; i < prunThreshold.size(); i++)
nodePrun[i] >> prunThreshold[i];
// read anchor points
FileNode nodeAnchor = fs["Anchor"];
anchors.resize(nodeAnchor.size());
for (unsigned int i = 0; i < anchors.size(); i++)
nodeAnchor[i] >> anchors[i];
// read deformation
FileNode nodeDef = fs["Deformation"];
defs.resize(nodeDef.size());
for (unsigned int i = 0; i < nodeDef.size(); i++)
nodeDef[i] >> defs[i];
// read number of parts in each component
fs["NumParts"] >> numParts;
// read part order
FileNode nodeOrder = fs["PartOrder"];
partOrder.resize(nodeOrder.size());
for (unsigned int i = 0; i < nodeOrder.size(); i++)
nodeOrder[i] >> partOrder[i];
// read location weight
FileNode nodeLoc = fs["LocationWeight"];
locationWeight.resize(nodeLoc.size());
for (unsigned int i = 0; i < locationWeight.size(); i++)
nodeLoc[i] >> locationWeight[i];
// close the file store
fs.release();
return true;
}
}
}
modules/dpm/src/dpm_model.hpp
+143
View File
@@ -0,0 +1,143 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2015, Itseez Inc, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Itseez Inc or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __DPM_MODEL__
#define __DPM_MODEL__
#include "opencv2/core.hpp"
#include <string>
#include <vector>
namespace cv
{
namespace dpm
{
/** @brief This class contains DPM model parameters
*/
class Model
{
public:
// size of HOG feature cell (e.g., 8 pixels)
int sBin;
// number of levels per octave in feature pyramid
int interval;
// maximum width of the detection window
int maxSizeX;
// maximum height of the detection window
int maxSizeY;
// dimension of HOG features
int numFeatures;
// number of components in the model
int numComponents;
// number of parts per component
std::vector<int> numParts;
// size of root filters
std::vector< Size > rootFilterDims;
// size of part filters
std::vector< Size > partFilterDims;
// root filters
std::vector< Mat > rootFilters;
// part filters
std::vector< Mat > partFilters;
// global detecion threshold
float scoreThresh;
// component indexed array of part orderings
std::vector< std::vector<int> > partOrder;
// component indexed offset (a.k.a. bias) values
std::vector<float> bias;
// location/scale weight
std::vector< std::vector< double > > locationWeight;
// idea relative positions for each deformation model
std::vector< std::vector< double > > anchors;
// array of deformation models
std::vector< std::vector< double > > defs;
// map: pFind[component][part] => part filter index
std::vector< std::vector<int> > pFind;
public:
Model () {}
virtual ~Model () {}
// get number of part filters
int getNumPartFilters()
{
return (int) partFilters.size();
}
// get number of deformation parameters
int getNumDefParams()
{
return (int) defs.size();
}
virtual void initModel() {};
virtual bool serialize(const std::string &filename) const = 0;
virtual bool deserialize(const std::string &filename) = 0;
};
class CascadeModel : public Model
{
public:
// PCA coefficient matrix
Mat pcaCoeff;
// number of dimensions used for the PCA projection
int pcaDim;
// component indexed arrays of pruning threshold
std::vector< std::vector< double > > prunThreshold;
// root pca filters
std::vector< Mat > rootPCAFilters;
// part PCA filters
std::vector< Mat > partPCAFilters;
public:
CascadeModel() {}
~CascadeModel() CV_OVERRIDE {}
void initModel() CV_OVERRIDE;
bool serialize(const std::string &filename) const CV_OVERRIDE;
bool deserialize(const std::string &filename) CV_OVERRIDE;
};
} // namespace lsvm
} // namespace cv
#endif // __DPM_MODEL_
modules/dpm/src/dpm_nms.cpp
+153
View File
@@ -0,0 +1,153 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2015, Itseez Inc, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Itseez Inc or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "dpm_nms.hpp"
#include <algorithm>
using namespace std;
namespace cv
{
namespace dpm
{
void NonMaximumSuppression::sort(const vector< double > x, vector< int > &indices)
{
for (unsigned int i = 0; i < x.size(); i++)
{
for (unsigned int j = i + 1; j < x.size(); j++)
{
if (x[indices[j]] < x[indices[i]])
{
int tmp = indices[i];
indices[i] = indices[j];
indices[j] = tmp;
}
}
}
}
void NonMaximumSuppression::process(vector< vector< double > > &detections, double overlapThreshold)
{
int numBoxes = (int) detections.size();
if (numBoxes <= 0)
return;
vector< double > area(numBoxes);
vector< double > score(numBoxes);
vector< int > indices(numBoxes);
for (int i = 0; i < numBoxes; i++)
{
indices[i] = i;
int s = (int)detections[i].size();
double x1 = detections[i][0];
double y1 = detections[i][1];
double x2 = detections[i][2];
double y2 = detections[i][3];
double sc = detections[i][s-1];
score[i] = sc;
area[i] = (x2 - x1 + 1) * ( y2 - y1 + 1);
}
// sort boxes by score
sort(score, indices);
vector< int > pick;
vector< int > suppress;
while (indices.size() > 0)
{
int last = (int) indices.size() - 1;
int i = indices[last];
pick.push_back(i);
suppress.clear();
suppress.push_back(last);
for (int k = 0; k <= last - 1; k++)
{
int j = indices[k];
double xx1 = max(detections[i][0], detections[j][0]);
double yy1 = max(detections[i][1], detections[j][1]);
double xx2 = min(detections[i][2], detections[j][2]);
double yy2 = min(detections[i][3], detections[j][3]);
double w = xx2 - xx1 + 1;
double h = yy2 - yy1 + 1;
if (w > 0 && h > 0)
{
// compute overlap
double o = w*h / area[j];
if (o > overlapThreshold)
suppress.push_back(k);
}
} // k
// remove suppressed indices
vector< int > newIndices;
for (unsigned int n = 0; n < indices.size(); n++)
{
bool isSuppressed = false;
for (unsigned int r = 0; r < suppress.size(); r++)
{
if (n == (unsigned int)suppress[r])
{
isSuppressed = true;
break;
}
}
if (!isSuppressed)
newIndices.push_back(indices[n]);
}
indices = newIndices;
} // while
vector< vector< double > > newDetections(pick.size());
for (unsigned int i = 0; i < pick.size(); i++)
newDetections[i] = detections[pick[i]];
detections = newDetections;
}
} // dpm
} // cv
modules/dpm/src/dpm_nms.hpp
+66
View File
@@ -0,0 +1,66 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2015, Itseez Inc, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Itseez Inc or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __DPM_NMS__
#define __DPM_NMS__
#include <vector>
namespace cv
{
namespace dpm
{
/** @brief Non-maximum suppression
* Greedily select high-scoring detections and skip
* detections that are significantly covered by a
* previously selected detection.
*/
class NonMaximumSuppression
{
public:
NonMaximumSuppression() {}
~NonMaximumSuppression() {}
void sort(const std::vector< double > x, std::vector< int > &indices);
void process(std::vector< std::vector< double > > &detections, double overlapThreshold);
};
} // dpm
} // cv
#endif // __DPM_NMS__
modules/dpm/src/precomp.hpp
+55
View File
@@ -0,0 +1,55 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2015, Itseez Inc, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Itseez Inc or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_PRECOMP_H__
#define __OPENCV_PRECOMP_H__
#ifdef HAVE_CVCONFIG_H
#include "cvconfig.h"
#endif
#include "opencv2/dpm.hpp"
#ifdef HAVE_TEGRA_OPTIMIZATION
#include "opencv2/objdetect/objdetect_tegra.hpp"
#endif
#endif