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98 lines
3.1 KiB
98 lines
3.1 KiB
#include <iostream>
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#include "inference.h"
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#include <filesystem>
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#include <fstream>
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void file_iterator(DCSP_CORE *&p) {
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std::filesystem::path current_path = std::filesystem::current_path();
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std::filesystem::path imgs_path = current_path / "images";
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for (auto &i: std::filesystem::directory_iterator(imgs_path)) {
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if (i.path().extension() == ".jpg" || i.path().extension() == ".png" || i.path().extension() == ".jpeg") {
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std::string img_path = i.path().string();
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cv::Mat img = cv::imread(img_path);
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std::vector<DCSP_RESULT> res;
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p->RunSession(img, res);
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for (auto &re: res) {
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cv::RNG rng(cv::getTickCount());
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cv::Scalar color(rng.uniform(0, 256), rng.uniform(0, 256), rng.uniform(0, 256));
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cv::rectangle(img, re.box, color, 3);
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std::string label = p->classes[re.classId] + " " + std::to_string(re.confidence);
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cv::putText(
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img,
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label,
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cv::Point(re.box.x, re.box.y - 5),
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cv::FONT_HERSHEY_SIMPLEX,
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0.75,
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color,
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2
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);
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}
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std::cout << "Press any key to exit" << std::endl;
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cv::imshow("Result of Detection", img);
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cv::waitKey(0);
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cv::destroyAllWindows();
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}
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}
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}
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int read_coco_yaml(DCSP_CORE *&p) {
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// Open the YAML file
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std::ifstream file("coco.yaml");
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if (!file.is_open()) {
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std::cerr << "Failed to open file" << std::endl;
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return 1;
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}
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// Read the file line by line
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std::string line;
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std::vector<std::string> lines;
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while (std::getline(file, line)) {
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lines.push_back(line);
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}
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// Find the start and end of the names section
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std::size_t start = 0;
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std::size_t end = 0;
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for (std::size_t i = 0; i < lines.size(); i++) {
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if (lines[i].find("names:") != std::string::npos) {
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start = i + 1;
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} else if (start > 0 && lines[i].find(':') == std::string::npos) {
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end = i;
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break;
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}
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}
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// Extract the names
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std::vector<std::string> names;
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for (std::size_t i = start; i < end; i++) {
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std::stringstream ss(lines[i]);
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std::string name;
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std::getline(ss, name, ':'); // Extract the number before the delimiter
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std::getline(ss, name); // Extract the string after the delimiter
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names.push_back(name);
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}
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p->classes = names;
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return 0;
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}
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int main() {
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DCSP_CORE *yoloDetector = new DCSP_CORE;
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std::string model_path = "yolov8n.onnx";
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read_coco_yaml(yoloDetector);
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#ifdef USE_CUDA
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// GPU FP32 inference
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DCSP_INIT_PARAM params{ model_path, YOLO_ORIGIN_V8, {640, 640}, 0.1, 0.5, true };
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// GPU FP16 inference
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// DCSP_INIT_PARAM params{ model_path, YOLO_ORIGIN_V8_HALF, {640, 640}, 0.1, 0.5, true };
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#else
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// CPU inference
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DCSP_INIT_PARAM params{model_path, YOLO_ORIGIN_V8, {640, 640}, 0.1, 0.5, false};
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#endif
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yoloDetector->CreateSession(params);
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file_iterator(yoloDetector);
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}
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