70 lines
2.1 KiB
C++
70 lines
2.1 KiB
C++
#include "mmdeploy/detector.hpp"
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#include <opencv2/imgcodecs/imgcodecs.hpp>
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#include <opencv2/imgproc/imgproc.hpp>
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#include <string>
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int main(int argc, char* argv[]) {
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if (argc != 4) {
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fprintf(stderr, "usage:\n object_detection device_name model_path image_path\n");
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return 1;
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}
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auto device_name = argv[1];
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auto model_path = argv[2];
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auto image_path = argv[3];
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cv::Mat img = cv::imread(image_path);
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if (!img.data) {
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fprintf(stderr, "failed to load image: %s\n", image_path);
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return 1;
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}
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mmdeploy::Model model(model_path);
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mmdeploy::Detector detector(model, mmdeploy::Device{device_name, 0});
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auto dets = detector.Apply(img);
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fprintf(stdout, "bbox_count=%d\n", (int)dets.size());
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for (int i = 0; i < dets.size(); ++i) {
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const auto& box = dets[i].bbox;
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const auto& mask = dets[i].mask;
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fprintf(stdout, "box %d, left=%.2f, top=%.2f, right=%.2f, bottom=%.2f, label=%d, score=%.4f\n",
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i, box.left, box.top, box.right, box.bottom, dets[i].label_id, dets[i].score);
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// skip detections with invalid bbox size (bbox height or width < 1)
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if ((box.right - box.left) < 1 || (box.bottom - box.top) < 1) {
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continue;
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}
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// skip detections less than specified score threshold
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if (dets[i].score < 0.3) {
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continue;
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}
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// generate mask overlay if model exports masks
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if (mask != nullptr) {
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fprintf(stdout, "mask %d, height=%d, width=%d\n", i, mask->height, mask->width);
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cv::Mat imgMask(mask->height, mask->width, CV_8UC1, &mask->data[0]);
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auto x0 = std::max(std::floor(box.left) - 1, 0.f);
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auto y0 = std::max(std::floor(box.top) - 1, 0.f);
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cv::Rect roi((int)x0, (int)y0, mask->width, mask->height);
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// split the RGB channels, overlay mask to a specific color channel
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cv::Mat ch[3];
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split(img, ch);
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int col = 0; // int col = i % 3;
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cv::bitwise_or(imgMask, ch[col](roi), ch[col](roi));
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merge(ch, 3, img);
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}
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cv::rectangle(img, cv::Point{(int)box.left, (int)box.top},
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cv::Point{(int)box.right, (int)box.bottom}, cv::Scalar{0, 255, 0});
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}
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cv::imwrite("output_detection.png", img);
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return 0;
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}
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