vendor: OpenCV 5.0.0 snapshot at 755e50675d97db9b7d449d8bd6b09888646f6c6e

modules/cnn_3dobj/tutorials/model_analysis/model_analysis.markdown

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+Training Model Analysis {#tutorial_model_analysis}
+=============
+
+Goal
+----
+
+In this tutorial you will learn how to
+
+-   Extract feature from particular image.
+-   Have a meaningful comparation on the extracted feature.
+
+Code
+----
+
+@include cnn_3dobj/samples/model_analysis.cpp
+
+Explanation
+-----------
+
+Here is the general structure of the program:
+
+-   Sample which is most closest in pose to reference image and also the same class.
+    @code{.cpp}
+    ref_img.push_back(ref_img1);
+    @endcode
+
+-   Sample which is less closest in pose to reference image and also the same class.
+    @code{.cpp}
+    ref_img.push_back(ref_img2);
+    @endcode
+
+-   Sample which is very close in pose to reference image but not the same class.
+    @code{.cpp}
+    ref_img.push_back(ref_img3);
+    @endcode
+
+-   Initialize a net work with Device.
+    @code{.cpp}
+    cv::cnn_3dobj::descriptorExtractor descriptor(device, dev_id);
+    @endcode
+-   Load net with the caffe trained net work parameter and structure.
+    @code{.cpp}
+    if (strcmp(mean_file.c_str(), "no") == 0)
+        descriptor.loadNet(network_forIMG, caffemodel);
+    else
+        descriptor.loadNet(network_forIMG, caffemodel, mean_file);
+    @endcode
+
+-   Have comparations on the distance between reference image and 3 other images
+    distance between closest sample and reference image should be smallest and
+    distance between sample in another class and reference image should be largest.
+    @code{.cpp}
+    if (matches[0] < matches[1] && matches[0] < matches[2])
+        pose_pass = true;
+    if (matches[1] < matches[2])
+        class_pass = true;
+    @endcode
+Results
+-------