718c41634f
1.项目后端整体迁移至PaddleOCR-NCNN算法，已通过基本的兼容性测试 2.工程改为使用CMake组织，后续为了更好地兼容第三方库，不再提供QMake工程 3.重整权利声明文件，重整代码工程，确保最小化侵权风险 Log: 切换后端至PaddleOCR-NCNN，切换工程为CMake Change-Id: I4d5d2c5d37505a4a24b389b1a4c5d12f17bfa38c
130 lines
3.9 KiB
C++
130 lines
3.9 KiB
C++
// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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#include "test_precomp.hpp"
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//#define DEBUG_TEST
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#ifdef DEBUG_TEST
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#include <opencv2/highgui.hpp>
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#endif
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namespace opencv_test { namespace {
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//using namespace cv::tracking;
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#define TESTSET_NAMES testing::Values("david", "dudek", "faceocc2")
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const string TRACKING_DIR = "tracking";
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const string FOLDER_IMG = "data";
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const string FOLDER_OMIT_INIT = "initOmit";
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#include "test_trackers.impl.hpp"
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//[TESTDATA]
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PARAM_TEST_CASE(DistanceAndOverlap, string)
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{
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string dataset;
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virtual void SetUp()
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{
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dataset = GET_PARAM(0);
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}
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};
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TEST_P(DistanceAndOverlap, MIL)
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{
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TrackerTest<Tracker, Rect> test(TrackerMIL::create(), dataset, 30, .65f, NoTransform);
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test.run();
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}
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TEST_P(DistanceAndOverlap, Shifted_Data_MIL)
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{
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TrackerTest<Tracker, Rect> test(TrackerMIL::create(), dataset, 30, .6f, CenterShiftLeft);
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test.run();
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}
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/***************************************************************************************/
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//Tests with scaled initial window
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TEST_P(DistanceAndOverlap, Scaled_Data_MIL)
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{
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TrackerTest<Tracker, Rect> test(TrackerMIL::create(), dataset, 30, .7f, Scale_1_1);
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test.run();
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}
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TEST_P(DistanceAndOverlap, GOTURN)
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{
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std::string model = cvtest::findDataFile("dnn/gsoc2016-goturn/goturn.prototxt");
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std::string weights = cvtest::findDataFile("dnn/gsoc2016-goturn/goturn.caffemodel", false);
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cv::TrackerGOTURN::Params params;
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params.modelTxt = model;
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params.modelBin = weights;
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TrackerTest<Tracker, Rect> test(TrackerGOTURN::create(params), dataset, 35, .35f, NoTransform);
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test.run();
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}
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INSTANTIATE_TEST_CASE_P(Tracking, DistanceAndOverlap, TESTSET_NAMES);
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TEST(GOTURN, memory_usage)
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{
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cv::Rect roi(145, 70, 85, 85);
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std::string model = cvtest::findDataFile("dnn/gsoc2016-goturn/goturn.prototxt");
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std::string weights = cvtest::findDataFile("dnn/gsoc2016-goturn/goturn.caffemodel", false);
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cv::TrackerGOTURN::Params params;
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params.modelTxt = model;
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params.modelBin = weights;
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cv::Ptr<Tracker> tracker = TrackerGOTURN::create(params);
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string inputVideo = cvtest::findDataFile("tracking/david/data/david.webm");
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cv::VideoCapture video(inputVideo);
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ASSERT_TRUE(video.isOpened()) << inputVideo;
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cv::Mat frame;
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video >> frame;
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ASSERT_FALSE(frame.empty()) << inputVideo;
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tracker->init(frame, roi);
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string ground_truth_bb;
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for (int nframes = 0; nframes < 15; ++nframes)
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{
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std::cout << "Frame: " << nframes << std::endl;
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video >> frame;
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bool res = tracker->update(frame, roi);
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ASSERT_TRUE(res);
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std::cout << "Predicted ROI: " << roi << std::endl;
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}
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}
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TEST(DaSiamRPN, memory_usage)
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{
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cv::Rect roi(145, 70, 85, 85);
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std::string model = cvtest::findDataFile("dnn/onnx/models/dasiamrpn_model.onnx", false);
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std::string kernel_r1 = cvtest::findDataFile("dnn/onnx/models/dasiamrpn_kernel_r1.onnx", false);
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std::string kernel_cls1 = cvtest::findDataFile("dnn/onnx/models/dasiamrpn_kernel_cls1.onnx", false);
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cv::TrackerDaSiamRPN::Params params;
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params.model = model;
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params.kernel_r1 = kernel_r1;
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params.kernel_cls1 = kernel_cls1;
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cv::Ptr<Tracker> tracker = TrackerDaSiamRPN::create(params);
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string inputVideo = cvtest::findDataFile("tracking/david/data/david.webm");
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cv::VideoCapture video(inputVideo);
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ASSERT_TRUE(video.isOpened()) << inputVideo;
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cv::Mat frame;
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video >> frame;
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ASSERT_FALSE(frame.empty()) << inputVideo;
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tracker->init(frame, roi);
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string ground_truth_bb;
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for (int nframes = 0; nframes < 15; ++nframes)
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{
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std::cout << "Frame: " << nframes << std::endl;
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video >> frame;
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bool res = tracker->update(frame, roi);
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ASSERT_TRUE(res);
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std::cout << "Predicted ROI: " << roi << std::endl;
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}
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}
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}} // namespace opencv_test::
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