// Copyright (c) OpenMMLab. All rights reserved. #include <iostream> #include "mmdeploy/detector.hpp" #include "mmdeploy/pose_detector.hpp" #include "opencv2/imgcodecs/imgcodecs.hpp" #include "utils/argparse.h" #include "utils/visualize.h" DEFINE_ARG_string(det_model, "Object detection model path"); DEFINE_ARG_string(pose_model, "Pose estimation model path"); DEFINE_ARG_string(image, "Input image path"); DEFINE_string(device, "cpu", R"(Device name, e.g. "cpu", "cuda")"); DEFINE_string(output, "det_pose_output.jpg", "Output image path"); DEFINE_string(skeleton, "coco", R"(Path to skeleton data or name of predefined skeletons: "coco")"); DEFINE_int32(det_label, 0, "Detection label use for pose estimation"); DEFINE_double(det_thr, .5, "Detection score threshold"); DEFINE_double(det_min_bbox_size, -1, "Detection minimum bbox size"); DEFINE_double(pose_thr, 0, "Pose key-point threshold"); int main(int argc, char* argv[]) { if (!utils::ParseArguments(argc, argv)) { return -1; } cv::Mat img = cv::imread(ARGS_image); if (img.empty()) { fprintf(stderr, "failed to load image: %s\n", ARGS_image.c_str()); return -1; } mmdeploy::Device device{FLAGS_device}; // create object detector mmdeploy::Detector detector(mmdeploy::Model(ARGS_det_model), device); // create pose detector mmdeploy::PoseDetector pose(mmdeploy::Model(ARGS_pose_model), device); // apply the detector, the result is an array-like class holding references to // `mmdeploy_detection_t`, will be released automatically on destruction mmdeploy::Detector::Result dets = detector.Apply(img); // filter detections and extract bboxes for pose model std::vector<mmdeploy_rect_t> bboxes; for (const mmdeploy_detection_t& det : dets) { if (det.label_id == FLAGS_det_label && det.score > FLAGS_det_thr) { bboxes.push_back(det.bbox); } } // apply pose detector, if no bboxes are provided, full image will be used; the result is an // array-like class holding references to `mmdeploy_pose_detection_t`, will be released // automatically on destruction mmdeploy::PoseDetector::Result poses = pose.Apply(img, bboxes); assert(bboxes.size() == poses.size()); // visualize results utils::Visualize v; v.set_skeleton(utils::Skeleton::get(FLAGS_skeleton)); auto sess = v.get_session(img); for (size_t i = 0; i < bboxes.size(); ++i) { sess.add_bbox(bboxes[i], -1, -1); sess.add_pose(poses[i].point, poses[i].score, poses[i].length, FLAGS_pose_thr); } if (!FLAGS_output.empty()) { cv::imwrite(FLAGS_output, sess.get()); } return 0; }