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e3884a9ea8
video: fix vittrack in the case where crop size grows until out-of-memory when the input is black #25771 Fixes https://github.com/opencv/opencv/issues/25760 ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake
184 lines
5.8 KiB
C++
184 lines
5.8 KiB
C++
// VitTracker
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// model: https://github.com/opencv/opencv_zoo/tree/main/models/object_tracking_vittrack
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#include <iostream>
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#include <cmath>
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#include <opencv2/dnn.hpp>
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#include <opencv2/imgproc.hpp>
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#include <opencv2/highgui.hpp>
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#include <opencv2/video.hpp>
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using namespace cv;
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using namespace cv::dnn;
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const char *keys =
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"{ help h | | Print help message }"
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"{ input i | | Full path to input video folder, the specific camera index. (empty for camera 0) }"
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"{ net | vitTracker.onnx | Path to onnx model of vitTracker.onnx}"
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"{ tracking_score_threshold t | 0.3 | Tracking score threshold. If a bbox of score >= 0.3, it is considered as found }"
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"{ backend | 0 | Choose one of computation backends: "
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"0: automatically (by default), "
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"1: Halide language (http://halide-lang.org/), "
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"2: Intel's Deep Learning Inference Engine (https://software.intel.com/openvino-toolkit), "
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"3: OpenCV implementation, "
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"4: VKCOM, "
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"5: CUDA },"
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"{ target | 0 | Choose one of target computation devices: "
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"0: CPU target (by default), "
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"1: OpenCL, "
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"2: OpenCL fp16 (half-float precision), "
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"3: VPU, "
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"4: Vulkan, "
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"6: CUDA, "
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"7: CUDA fp16 (half-float preprocess) }"
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;
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static
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int run(int argc, char** argv)
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{
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// Parse command line arguments.
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CommandLineParser parser(argc, argv, keys);
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if (parser.has("help"))
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{
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parser.printMessage();
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return 0;
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}
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std::string inputName = parser.get<String>("input");
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std::string net = parser.get<String>("net");
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int backend = parser.get<int>("backend");
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int target = parser.get<int>("target");
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float tracking_score_threshold = parser.get<float>("tracking_score_threshold");
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Ptr<TrackerVit> tracker;
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try
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{
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TrackerVit::Params params;
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params.net = samples::findFile(net);
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params.backend = backend;
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params.target = target;
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params.tracking_score_threshold = tracking_score_threshold;
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tracker = TrackerVit::create(params);
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}
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catch (const cv::Exception& ee)
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{
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std::cerr << "Exception: " << ee.what() << std::endl;
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std::cout << "Can't load the network by using the following files:" << std::endl;
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std::cout << "net : " << net << std::endl;
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return 2;
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}
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const std::string winName = "vitTracker";
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namedWindow(winName, WINDOW_AUTOSIZE);
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// Open a video file or an image file or a camera stream.
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VideoCapture cap;
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if (inputName.empty() || (isdigit(inputName[0]) && inputName.size() == 1))
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{
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int c = inputName.empty() ? 0 : inputName[0] - '0';
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std::cout << "Trying to open camera #" << c << " ..." << std::endl;
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if (!cap.open(c))
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{
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std::cout << "Capture from camera #" << c << " didn't work. Specify -i=<video> parameter to read from video file" << std::endl;
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return 2;
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}
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}
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else if (inputName.size())
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{
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inputName = samples::findFileOrKeep(inputName);
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if (!cap.open(inputName))
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{
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std::cout << "Could not open: " << inputName << std::endl;
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return 2;
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}
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}
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// Read the first image.
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Mat image;
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cap >> image;
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if (image.empty())
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{
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std::cerr << "Can't capture frame!" << std::endl;
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return 2;
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}
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Mat image_select = image.clone();
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putText(image_select, "Select initial bounding box you want to track.", Point(0, 15), FONT_HERSHEY_SIMPLEX, 0.5, Scalar(0, 255, 0));
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putText(image_select, "And Press the ENTER key.", Point(0, 35), FONT_HERSHEY_SIMPLEX, 0.5, Scalar(0, 255, 0));
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Rect selectRect = selectROI(winName, image_select);
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std::cout << "ROI=" << selectRect << std::endl;
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if (selectRect.empty())
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{
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std::cerr << "Invalid ROI!" << std::endl;
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return 2;
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}
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tracker->init(image, selectRect);
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TickMeter tickMeter;
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for (int count = 0; ; ++count)
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{
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cap >> image;
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if (image.empty())
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{
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std::cerr << "Can't capture frame " << count << ". End of video stream?" << std::endl;
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break;
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}
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Rect rect;
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tickMeter.start();
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bool ok = tracker->update(image, rect);
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tickMeter.stop();
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float score = tracker->getTrackingScore();
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std::cout << "frame " << count;
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if (ok) {
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std::cout << ": predicted score=" << score <<
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"\trect=" << rect <<
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"\ttime=" << tickMeter.getTimeMilli() << "ms" << std::endl;
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rectangle(image, rect, Scalar(0, 255, 0), 2);
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std::string timeLabel = format("Inference time: %.2f ms", tickMeter.getTimeMilli());
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std::string scoreLabel = format("Score: %f", score);
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putText(image, timeLabel, Point(0, 15), FONT_HERSHEY_SIMPLEX, 0.5, Scalar(0, 255, 0));
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putText(image, scoreLabel, Point(0, 35), FONT_HERSHEY_SIMPLEX, 0.5, Scalar(0, 255, 0));
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} else {
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std::cout << ": target lost" << std::endl;
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putText(image, "Target lost", Point(0, 15), FONT_HERSHEY_SIMPLEX, 0.5, Scalar(0, 0, 255));
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}
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imshow(winName, image);
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tickMeter.reset();
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int c = waitKey(1);
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if (c == 27 /*ESC*/ || c == 'q' || c == 'Q')
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break;
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}
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std::cout << "Exit" << std::endl;
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return 0;
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}
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int main(int argc, char **argv)
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{
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try
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{
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return run(argc, argv);
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}
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catch (const std::exception& e)
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{
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std::cerr << "FATAL: C++ exception: " << e.what() << std::endl;
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return 1;
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}
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}
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