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https://github.com/opencv/opencv_contrib.git
synced 2025-10-21 06:11:09 +08:00
Added MO-TLD NN Classifier optimization on GPU
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@@ -120,11 +120,7 @@ int main()
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//From TLD dataset
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selectObject = true;
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Rect2d boundingBox1 = tld::tld_InitDataset(TEST_VIDEO_INDEX, "D:/opencv/VOT 2015", 1);
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Rect2d boundingBox2;
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boundingBox2.x = 470;
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boundingBox2.y = 500;
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boundingBox2.width = 50;
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boundingBox2.height = 100;
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Rect2d boundingBox2(470, 490, 50, 120);
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frame = tld::tld_getNextDatasetFrame();
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frame.copyTo(image);
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@@ -133,13 +129,13 @@ int main()
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#ifdef RECORD_VIDEO_FLG
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String outputFilename = "test.avi";
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VideoWriter outputVideo;
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outputVideo.open(outputFilename, -1, 30, Size(image.cols, image.rows));
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outputVideo.open(outputFilename, -1, 15, Size(image.cols, image.rows));
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if (!outputVideo.isOpened())
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{
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std::cout << "!!! Output video could not be opened" << std::endl;
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getchar();
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return;
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return 0;
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}
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#endif
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@@ -184,17 +180,17 @@ int main()
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{
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//initializes the tracker
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mt.addTarget(frame, boundingBox1, tracker_algorithm_name);
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rectangle(image, boundingBox1, mt.colors[0], 2, 1);
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rectangle(frame, boundingBox1, mt.colors[0], 2, 1);
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mt.addTarget(frame, boundingBox2, tracker_algorithm_name);
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rectangle(image, boundingBox2, mt.colors[1], 2, 1);
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rectangle(frame, boundingBox2, mt.colors[1], 2, 1);
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initialized = true;
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}
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else
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{
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//updates the tracker
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if (mt.update_opt(frame))
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if (mt.update(frame))
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{
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for (int i = 0; i < mt.targetNum; i++)
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rectangle(frame, mt.boundingBoxes[i], mt.colors[i], 2, 1);
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@@ -204,7 +200,7 @@ int main()
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imshow("Tracking API", frame);
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#ifdef RECORD_VIDEO_FLG
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outputVideo << image;
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outputVideo << frame;
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#endif
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