69 lines
3.1 KiB
C++
69 lines
3.1 KiB
C++
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#ifdef VP_WITH_TRT
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#include "vp_trt_yolov8_detector.h"
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namespace vp_nodes {
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vp_trt_yolov8_detector::vp_trt_yolov8_detector(std::string node_name,
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std::string model_path,
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std::string labels_path):
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vp_primary_infer_node(node_name, "", "", labels_path) {
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yolov8_detector = std::make_shared<trt_yolov8::trt_yolov8_detector>(model_path);
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this->initialized();
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}
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vp_trt_yolov8_detector::~vp_trt_yolov8_detector() {
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deinitialized();
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}
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// please refer to vp_infer_node::run_infer_combinations
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void vp_trt_yolov8_detector::run_infer_combinations(const std::vector<std::shared_ptr<vp_objects::vp_frame_meta>>& frame_meta_with_batch) {
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assert(frame_meta_with_batch.size() == 1);
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std::vector<cv::Mat> mats_to_infer;
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// start
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auto start_time = std::chrono::system_clock::now();
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// prepare data, as same as base class
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vp_primary_infer_node::prepare(frame_meta_with_batch, mats_to_infer);
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auto prepare_time = std::chrono::duration_cast<std::chrono::milliseconds>(std::chrono::system_clock::now() - start_time);
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start_time = std::chrono::system_clock::now();
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std::vector<std::vector<Detection>> detections;
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yolov8_detector->detect(mats_to_infer, detections);
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assert(detections.size() == 1);
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auto& detection_list = detections[0];
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auto& frame_meta = frame_meta_with_batch[0];
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for (int i = 0; i < detection_list.size(); i++) {
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auto& objbox = detection_list[i];
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// objbox.bbox: center_x center_y width height
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auto rect = get_rect(frame_meta->frame, objbox.bbox); // convert to: x, y, width,height
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// check value range
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int x = std::max(rect.x, 0);
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int y = std::max(rect.y, 0);
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int width = std::min(rect.width, frame_meta->frame.cols - x);
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int height = std::min(rect.height, frame_meta->frame.rows - y);
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if (width <= 0 || height <= 0) {
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continue;
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}
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auto label = labels.size() == 0 ? "" : labels[objbox.class_id];
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auto target = std::make_shared<vp_objects::vp_frame_target>(x, y, width, height,
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objbox.class_id, objbox.conf, frame_meta->frame_index, frame_meta->channel_index, label);
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// create target and update back into frame meta
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frame_meta->targets.push_back(target);
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}
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auto infer_time = std::chrono::duration_cast<std::chrono::milliseconds>(std::chrono::system_clock::now() - start_time);
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// can not calculate preprocess time and postprocess time, set 0 by default.
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vp_infer_node::infer_combinations_time_cost(mats_to_infer.size(), prepare_time.count(), 0, infer_time.count(), 0);
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}
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void vp_trt_yolov8_detector::postprocess(const std::vector<cv::Mat>& raw_outputs, const std::vector<std::shared_ptr<vp_objects::vp_frame_meta>>& frame_meta_with_batch) {
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}
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}
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#endif |