190 lines
7.6 KiB
C
190 lines
7.6 KiB
C
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#pragma once
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#pragma once
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/// <summary>
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/// https://www.cnblogs.com/guojin-blogs/p/18284497
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/// wget https://github.com/jameslahm/yolov10/releases/download/v1.0/yolov10s.pt
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// yolo export model = yolov10s.pt format = onnx opset = 13 simplify
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/// </summary>
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#include "opencv2/opencv.hpp"
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#include <openvino/op/transpose.hpp>
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#include <openvino/core/node.hpp>
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#include <opencv2/dnn.hpp>
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#include <opencv2/imgproc.hpp>
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#include <models/detection_model_ssd.h>
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namespace Yolov10OV {
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struct DetResult {
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cv::Rect bbox;
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float conf;
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int lable;
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DetResult(cv::Rect bbox, float conf, int lable) :bbox(bbox), conf(conf), lable(lable) {}
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};
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void pre_process(cv::Mat* img, int length, float* factor, std::vector<float>& data) {
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cv::Mat mat;
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int rh = img->rows;
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int rw = img->cols;
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int rc = img->channels();
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cv::cvtColor(*img, mat, cv::COLOR_BGR2RGB);
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int max_image_length = rw > rh ? rw : rh;
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cv::Mat max_image = cv::Mat::zeros(max_image_length, max_image_length, CV_8UC3);
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max_image = max_image * 255;
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cv::Rect roi(0, 0, rw, rh);
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mat.copyTo(cv::Mat(max_image, roi));
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cv::Mat resize_img;
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cv::resize(max_image, resize_img, cv::Size(length, length), 0.0f, 0.0f, cv::INTER_LINEAR);
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*factor = (float)((float)max_image_length / (float)length);
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resize_img.convertTo(resize_img, CV_32FC3, 1 / 255.0);
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rh = resize_img.rows;
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rw = resize_img.cols;
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rc = resize_img.channels();
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for (int i = 0; i < rc; ++i) {
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cv::extractChannel(resize_img, cv::Mat(rh, rw, CV_32FC1, data.data() + i * rh * rw), i);
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}
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}
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std::vector<DetResult> post_process(float* result, float factor, int outputLength) {
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std::vector<cv::Rect> position_boxes;
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std::vector <int> class_ids;
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std::vector <float> confidences;
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// Preprocessing output results
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for (int i = 0; i < outputLength; i++)
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{
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int s = 6 * i;
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if ((float)result[s + 4] > 0.2)
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{
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float cx = result[s + 0];
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float cy = result[s + 1];
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float dx = result[s + 2];
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float dy = result[s + 3];
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int x = (int)((cx)*factor);
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int y = (int)((cy)*factor);
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int width = (int)((dx - cx) * factor);
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int height = (int)((dy - cy) * factor);
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cv::Rect box(x, y, width, height);
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position_boxes.push_back(box);
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class_ids.push_back((int)result[s + 5]);
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confidences.push_back((float)result[s + 4]);
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}
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}
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std::vector<DetResult> re;
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for (int i = 0; i < position_boxes.size(); i++)
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{
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DetResult det(position_boxes[i], confidences[i], class_ids[i]);
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re.push_back(det);
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}
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return re;
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}
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void draw_bbox(cv::Mat& img, std::vector<DetResult>& res) {
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for (size_t j = 0; j < res.size(); j++) {
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cv::rectangle(img, res[j].bbox, cv::Scalar(255, 0, 255), 2);
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cv::putText(img, std::to_string(res[j].lable) + "-" + std::to_string(res[j].conf),
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cv::Point(res[j].bbox.x, res[j].bbox.y - 1), cv::FONT_HERSHEY_PLAIN,
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1.2, cv::Scalar(0, 0, 255), 2);
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}
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}
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void yolov10_infer_without_process() {
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std::string videoPath = "E:\\Text_dataset\\car_test.mov";
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std::string model_path = "E:\\Text_Model\\yolov10s_openvino_model\\yolov10s.xml";
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ov::Core core;
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auto model = core.read_model(model_path);
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auto compiled_model = core.compile_model(model, "CPU");
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ov::InferRequest request = compiled_model.create_infer_request();
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cv::VideoCapture capture(videoPath);
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if (!capture.isOpened()) {
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std::cerr << "ERROR: " << std::endl;
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return;
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}
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float factor = 0;
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request.get_input_tensor().set_shape(std::vector<size_t>{1, 3, 640, 640});
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std::vector<float> inputData(640 * 640 * 3);
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std::chrono::time_point<std::chrono::steady_clock> t_beg;
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std::chrono::time_point<std::chrono::steady_clock> t_end;
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while (true)
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{
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cv::Mat frame;
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if (!capture.read(frame)) {
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break;
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}
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t_beg = std::chrono::high_resolution_clock::now();
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pre_process(&frame, 640, &factor, inputData);
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memcpy(request.get_input_tensor().data<float>(), inputData.data(), 640 * 640 * 3);
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request.infer();
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float* output_data = request.get_output_tensor().data<float>();
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std::vector<DetResult> result = post_process(output_data, factor, 300);
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t_end = std::chrono::high_resolution_clock::now();
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cv::putText(frame, "FPS: " + std::to_string(1000.0 / std::chrono::duration<float, std::milli>(t_end - t_beg).count())
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+ ", Time: " + std::to_string(std::chrono::duration<float, std::milli>(t_end - t_beg).count()) + "ms",
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cv::Point(20, 40), 1, 2, cv::Scalar(255, 0, 255), 2);
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draw_bbox(frame, result);
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imshow("Frame", frame);
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cv::waitKey(1); //30
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}
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cv::destroyAllWindows();
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return;
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}
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void yolov10_infer_ansy_without_process() {
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std::string videoPath = "E:\\Text_dataset\\car_test.mov";
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std::string model_path = "E:\\Text_Model\\yolov10s_openvino_model\\yolov10s.xml";
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ov::Core core;
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auto model = core.read_model(model_path);
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auto compiled_model = core.compile_model(model, "CPU");
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std::vector<ov::InferRequest>requests = { compiled_model.create_infer_request(), compiled_model.create_infer_request() };
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cv::VideoCapture capture(videoPath);
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if (!capture.isOpened()) {
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std::cerr << "ERROR:" << std::endl;
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return;
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}
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float factor = 0;
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requests[0].get_input_tensor().set_shape(std::vector<size_t>{1, 3, 640, 640});
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requests[1].get_input_tensor().set_shape(std::vector<size_t>{1, 3, 640, 640});
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cv::Mat frame;
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capture.read(frame);
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std::vector<float> inputData(640 * 640 * 3);
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pre_process(&frame, 640, &factor, inputData);
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memcpy(requests[0].get_input_tensor().data<float>(), inputData.data(), 640 * 640 * 3);
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requests[0].start_async();
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std::chrono::time_point<std::chrono::steady_clock> t_beg;
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std::chrono::time_point<std::chrono::steady_clock> t_end;
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while (true)
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{
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cv::Mat next_frame;
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if (!capture.read(next_frame)) {
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break;
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}
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t_beg = std::chrono::high_resolution_clock::now();
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pre_process(&next_frame, 640, &factor, inputData);
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memcpy(requests[1].get_input_tensor().data<float>(), inputData.data(), 640 * 640 * 3);
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requests[1].start_async();
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requests[0].wait();
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float* output_data = requests[0].get_output_tensor().data<float>();
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std::vector<DetResult> result = post_process(output_data, factor, 300);
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t_end = std::chrono::high_resolution_clock::now();
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draw_bbox(frame, result);
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cv::putText(frame, "FPS: " + std::to_string(1000.0 / std::chrono::duration<float, std::milli>(t_end - t_beg).count())
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+ ", Time: " + std::to_string(std::chrono::duration<float, std::milli>(t_end - t_beg).count()) + "ms",
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cv::Point(20, 40), 1, 2, cv::Scalar(255, 0, 255), 2);
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imshow("Frame", frame);
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cv::waitKey(1); //30
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frame = next_frame;
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std::swap(requests[0], requests[1]);
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}
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cv::destroyAllWindows();
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return;
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}
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}
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