committed by
Alexander Alekhin
parent
5e2bcc9149
commit
f9c514b391
@@ -58,7 +58,7 @@ foreach(sample_filename ${cpp_samples})
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target_compile_definitions(${tgt} PRIVATE HAVE_OPENGL)
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endif()
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if(sample_filename MATCHES "simd_")
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# disabled intentionally - demonstation purposes only
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# disabled intentionally - demonstration purposes only
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#target_include_directories(${tgt} PRIVATE "${CMAKE_CURRENT_LIST_DIR}")
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#target_compile_definitions(${tgt} PRIVATE OPENCV_SIMD_CONFIG_HEADER=opencv_simd_config_custom.hpp)
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#target_compile_definitions(${tgt} PRIVATE OPENCV_SIMD_CONFIG_INCLUDE_DIR=1)
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@@ -12,7 +12,7 @@ static void help()
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"It draws a random set of points in an image and then delaunay triangulates them.\n"
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"Usage: \n"
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"./delaunay \n"
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"\nThis program builds the traingulation interactively, you may stop this process by\n"
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"\nThis program builds the triangulation interactively, you may stop this process by\n"
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"hitting any key.\n";
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}
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@@ -157,7 +157,7 @@ int main()
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cout << responses.t() << endl;
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cout << "accuracy: " << calculateAccuracyPercent(labels_test, responses) << "%" << endl;
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// save the classfier
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// save the classifier
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const String saveFilename = "NewLR_Trained.xml";
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cout << "saving the classifier to " << saveFilename << endl;
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lr1->save(saveFilename);
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@@ -167,7 +167,7 @@ int main()
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Ptr<LogisticRegression> lr2 = StatModel::load<LogisticRegression>(saveFilename);
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// predict using loaded classifier
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cout << "predicting the dataset using the loaded classfier...";
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cout << "predicting the dataset using the loaded classifier...";
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Mat responses2;
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lr2->predict(data_test, responses2);
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cout << "done!" << endl;
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+1
-1
@@ -10,7 +10,7 @@
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* This program demonstrates how to use OpenCV PCA with a
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* specified amount of variance to retain. The effect
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* is illustrated further by using a trackbar to
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* change the value for retained varaince.
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* change the value for retained variance.
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*
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* The program takes as input a text file with each line
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* begin the full path to an image. PCA will be performed
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@@ -36,7 +36,7 @@ public:
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void load(const std::string &path);
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private:
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/** The current number of correspondecnes */
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/** The current number of correspondences */
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int n_correspondences_;
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/** The list of 2D points on the model surface */
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std::vector<cv::KeyPoint> list_keypoints_;
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@@ -17,7 +17,7 @@ static void help()
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" CAP_OPENNI_POINT_CLOUD_MAP - XYZ in meters (CV_32FC3)\n"
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" CAP_OPENNI_DISPARITY_MAP - disparity in pixels (CV_8UC1)\n"
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" CAP_OPENNI_DISPARITY_MAP_32F - disparity in pixels (CV_32FC1)\n"
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" CAP_OPENNI_VALID_DEPTH_MASK - mask of valid pixels (not ocluded, not shaded etc.) (CV_8UC1)\n"
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" CAP_OPENNI_VALID_DEPTH_MASK - mask of valid pixels (not occluded, not shaded etc.) (CV_8UC1)\n"
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"2.) Data given from RGB image generator\n"
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" CAP_OPENNI_BGR_IMAGE - color image (CV_8UC3)\n"
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" CAP_OPENNI_GRAY_IMAGE - gray image (CV_8UC1)\n"
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@@ -3,7 +3,7 @@
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// This will loop through frames of video either from input media file
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// or camera device and do processing of these data in OpenCL and then
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// in OpenCV. In OpenCL it does inversion of pixels in left half of frame and
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// in OpenCV it does bluring in the right half of frame.
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// in OpenCV it does blurring in the right half of frame.
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*/
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#include <cstdio>
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#include <cstdlib>
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@@ -15,7 +15,7 @@ Usage:
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Use sliders to adjust PSF paramitiers.
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Keys:
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SPACE - switch btw linear/cirular PSF
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SPACE - switch btw linear/circular PSF
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ESC - exit
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Examples:
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@@ -17,6 +17,6 @@ using namespace SDKSample;
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Platform::Array<Scenario>^ MainPage::scenariosInner = ref new Platform::Array<Scenario>
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{
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// The format here is the following:
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// { "Description for the sample", "Fully quaified name for the class that implements the scenario" }
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// { "Description for the sample", "Fully qualified name for the class that implements the scenario" }
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{ "Enumerate cameras and add a video effect", "SDKSample.MediaCapture.AdvancedCapture" },
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};
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