vendor: OpenCV 5.0.0 snapshot at 755e50675d97db9b7d449d8bd6b09888646f6c6e
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import cv2 as cv
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import numpy as np
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def rotation(theta):
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tx, ty, tz = theta
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Rx = np.array([[1, 0, 0], [0, np.cos(tx), -np.sin(tx)], [0, np.sin(tx), np.cos(tx)]])
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Ry = np.array([[np.cos(ty), 0, -np.sin(ty)], [0, 1, 0], [np.sin(ty), 0, np.cos(ty)]])
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Rz = np.array([[np.cos(tz), -np.sin(tz), 0], [np.sin(tz), np.cos(tz), 0], [0, 0, 1]])
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return np.dot(Rx, np.dot(Ry, Rz))
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width = 20
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height = 10
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max_deg = np.pi / 12
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cloud, rotated_cloud = [None]*3, [None]*3
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retval, residual, pose = [None]*3, [None]*3, [None]*3
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noise = np.random.normal(0.0, 0.1, height * width * 3).reshape((-1, 3))
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noise2 = np.random.normal(0.0, 1.0, height * width)
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x, y = np.meshgrid(
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range(-width//2, width//2),
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range(-height//2, height//2),
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sparse=False, indexing='xy'
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)
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z = np.zeros((height, width))
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cloud[0] = np.dstack((x, y, z)).reshape((-1, 3)).astype(np.float32)
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cloud[1] = noise.astype(np.float32) + cloud[0]
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cloud[2] = cloud[1]
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cloud[2][:, 2] += noise2.astype(np.float32)
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R = rotation([
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0, #np.random.uniform(-max_deg, max_deg),
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np.random.uniform(-max_deg, max_deg),
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0, #np.random.uniform(-max_deg, max_deg)
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])
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t = np.zeros((3, 1))
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Rt = np.vstack((
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np.hstack((R, t)),
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np.array([0, 0, 0, 1])
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)).astype(np.float32)
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icp = cv.ppf_match_3d_ICP(100)
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I = np.eye(4)
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print("Unaligned error:\t%.6f" % np.linalg.norm(I - Rt))
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for i in range(3):
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rotated_cloud[i] = np.matmul(Rt[0:3,0:3], cloud[i].T).T + Rt[:3,3].T
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retval[i], residual[i], pose[i] = icp.registerModelToScene(rotated_cloud[i], cloud[i])
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print("ICP error:\t\t%.6f" % np.linalg.norm(I - np.matmul(pose[0], Rt)))
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@@ -0,0 +1,159 @@
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2014, OpenCV Foundation, all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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// Author: Tolga Birdal <tbirdal AT gmail.com>
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#include "opencv2/surface_matching.hpp"
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#include <iostream>
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#include "opencv2/surface_matching/ppf_helpers.hpp"
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#include "opencv2/core/utility.hpp"
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using namespace std;
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using namespace cv;
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using namespace ppf_match_3d;
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static void help(const string& errorMessage)
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{
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cout << "Program init error : "<< errorMessage << endl;
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cout << "\nUsage : ppf_matching [input model file] [input scene file]"<< endl;
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cout << "\nPlease start again with new parameters"<< endl;
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}
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int main(int argc, char** argv)
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{
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// welcome message
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cout << "****************************************************" << endl;
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cout << "* Surface Matching demonstration : demonstrates the use of surface matching"
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" using point pair features." << endl;
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cout << "* The sample loads a model and a scene, where the model lies in a different"
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" pose than the training.\n* It then trains the model and searches for it in the"
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" input scene. The detected poses are further refined by ICP\n* and printed to the "
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" standard output." << endl;
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cout << "****************************************************" << endl;
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if (argc < 3)
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{
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help("Not enough input arguments");
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exit(1);
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}
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#if (defined __x86_64__ || defined _M_X64)
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cout << "Running on 64 bits" << endl;
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#else
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cout << "Running on 32 bits" << endl;
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#endif
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#ifdef _OPENMP
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cout << "Running with OpenMP" << endl;
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#else
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cout << "Running without OpenMP and without TBB" << endl;
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#endif
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string modelFileName = (string)argv[1];
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string sceneFileName = (string)argv[2];
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Mat pc = loadPLYSimple(modelFileName.c_str(), 1);
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// Now train the model
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cout << "Training..." << endl;
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int64 tick1 = cv::getTickCount();
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ppf_match_3d::PPF3DDetector detector(0.025, 0.05);
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detector.trainModel(pc);
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int64 tick2 = cv::getTickCount();
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cout << endl << "Training complete in "
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<< (double)(tick2-tick1)/ cv::getTickFrequency()
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<< " sec" << endl << "Loading model..." << endl;
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// Read the scene
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Mat pcTest = loadPLYSimple(sceneFileName.c_str(), 1);
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// Match the model to the scene and get the pose
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cout << endl << "Starting matching..." << endl;
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vector<Pose3DPtr> results;
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tick1 = cv::getTickCount();
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detector.match(pcTest, results, 1.0/40.0, 0.05);
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tick2 = cv::getTickCount();
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cout << endl << "PPF Elapsed Time " <<
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(tick2-tick1)/cv::getTickFrequency() << " sec" << endl;
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//check results size from match call above
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size_t results_size = results.size();
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cout << "Number of matching poses: " << results_size;
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if (results_size == 0) {
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cout << endl << "No matching poses found. Exiting." << endl;
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exit(0);
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}
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// Get only first N results - but adjust to results size if num of results are less than that specified by N
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size_t N = 2;
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if (results_size < N) {
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cout << endl << "Reducing matching poses to be reported (as specified in code): "
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<< N << " to the number of matches found: " << results_size << endl;
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N = results_size;
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}
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vector<Pose3DPtr> resultsSub(results.begin(),results.begin()+N);
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// Create an instance of ICP
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ICP icp(100, 0.005f, 2.5f, 8);
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int64 t1 = cv::getTickCount();
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// Register for all selected poses
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cout << endl << "Performing ICP on " << N << " poses..." << endl;
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icp.registerModelToScene(pc, pcTest, resultsSub);
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int64 t2 = cv::getTickCount();
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cout << endl << "ICP Elapsed Time " <<
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(t2-t1)/cv::getTickFrequency() << " sec" << endl;
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cout << "Poses: " << endl;
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// debug first five poses
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for (size_t i=0; i<resultsSub.size(); i++)
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{
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Pose3DPtr result = resultsSub[i];
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cout << "Pose Result " << i << endl;
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result->printPose();
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if (i==0)
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{
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Mat pct = transformPCPose(pc, result->pose);
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writePLY(pct, "para6700PCTrans.ply");
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}
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}
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return 0;
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}
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import cv2 as cv
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N = 2
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modelname = "parasaurolophus_6700"
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scenename = "rs1_normals"
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detector = cv.ppf_match_3d_PPF3DDetector(0.025, 0.05)
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print('Loading model...')
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pc = cv.ppf_match_3d.loadPLYSimple("data/%s.ply" % modelname, 1)
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print('Training...')
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detector.trainModel(pc)
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print('Loading scene...')
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pcTest = cv.ppf_match_3d.loadPLYSimple("data/%s.ply" % scenename, 1)
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print('Matching...')
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results = detector.match(pcTest, 1.0/40.0, 0.05)
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print('Performing ICP...')
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icp = cv.ppf_match_3d_ICP(100)
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_, results = icp.registerModelToScene(pc, pcTest, results[:N])
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print("Poses: ")
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for i, result in enumerate(results):
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#result.printPose()
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print("\n-- Pose to Model Index %d: NumVotes = %d, Residual = %f\n%s\n" % (result.modelIndex, result.numVotes, result.residual, result.pose))
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if i == 0:
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pct = cv.ppf_match_3d.transformPCPose(pc, result.pose)
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cv.ppf_match_3d.writePLY(pct, "%sPCTrans.ply" % modelname)
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@@ -0,0 +1,78 @@
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2014, OpenCV Foundation, all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
|
||||
// In no event shall the Intel Corporation or contributors be liable for any direct,
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||||
// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
|
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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#include <iostream>
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#include "opencv2/surface_matching.hpp"
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#include "opencv2/surface_matching/ppf_helpers.hpp"
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using namespace std;
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static void help(const string& errorMessage)
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{
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cout << "Program init error : " << errorMessage << endl;
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cout << "\nUsage : ppf_normal_computation [input model file] [output model file]" << endl;
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cout << "\nPlease start again with new parameters" << endl;
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}
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int main(int argc, char** argv)
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{
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if (argc < 3)
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{
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help("Not enough input arguments");
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exit(1);
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}
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string modelFileName = (string)argv[1];
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string outputFileName = (string)argv[2];
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cv::Mat points, pointsAndNormals;
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cout << "Loading points\n";
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cv::ppf_match_3d::loadPLYSimple(modelFileName.c_str(), 1).copyTo(points);
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cout << "Computing normals\n";
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cv::Vec3d viewpoint(0, 0, 0);
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cv::ppf_match_3d::computeNormalsPC3d(points, pointsAndNormals, 6, false, viewpoint);
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std::cout << "Writing points\n";
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cv::ppf_match_3d::writePLY(pointsAndNormals, outputFileName.c_str());
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//the following function can also be used for debugging purposes
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//cv::ppf_match_3d::writePLYVisibleNormals(pointsAndNormals, outputFileName.c_str());
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std::cout << "Done\n";
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return 0;
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}
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