triple-Mu
commented
6 months ago The model learned with multi-class(3) is performed normally with the yolov8 cli Predict command. I confirmed through debugging that only one class objects was detected when using the example here.
*. you recommed. You should modify pose postprocess. Default is only one class so that the score is only for person. But if enable multiclass you should use argmax and max to find the highest score and label. => Where should I fix it?
*. I check it.
YOLOv8-TensorRT\csrc\pose\normal\include\yolov8-pose.hpp .... void YOLOv8_pose::postprocess(std::vector& objs, float score_thres, float iou_thres, int topk) { ... auto kps_ptr = row_ptr + 5;
// classnum = 3 auto maxSPtr = std::max_element(kps_ptr, kps_ptr + 3); // auto maxSPtr = std::max_element(kps_ptr+2, kps_ptr + 3); // auto maxSPtr = std::max_element(kps_ptr+3, kps_ptr + 3);
float score = *scores_ptr; if(score > score_thres) { label = maxSPtr - scores_ptr;// Not Detect label cout << func << ";label=" << label << endl; .....
int cnt = 0; /* #ifdef BATCHED_NMS cv::dnn::NMSBoxesBatched(bboxes, scores, labels, score_thresd, iou_thres, indices); #else cv::dnn::NMSBoxes(bboxes, scores, score_thres, iou_thres, indices); #endif
for(auto& i : indices) */ // 8 object Detect, but almost same position and size. for(int i = 0; i < bboxes.size(); i++) { if(cnt >= topk) break; Object obj; obj.rect = bboxes[i]; obj.prob = scores[i]; obj.label = labels[i]; obj.kps = kpss[i]; objs.push_back(obj); cnt += 1; } } ....
Sure you should find the top label by scores_ptr. And make the Object.label to this label. And do postprocess and draw label on image.
faithmaker
The model learned with multi-class(3) is performed normally with the yolov8 cli Predict command. I confirmed through debugging that only one class objects was detected when using the example here.
*. you recommed. You should modify pose postprocess. Default is only one class so that the score is only for person. But if enable multiclass you should use argmax and max to find the highest score and label. => Where should I fix it?
*. I check it.
YOLOv8-TensorRT\csrc\pose\normal\include\yolov8-pose.hpp .... void YOLOv8_pose::postprocess(std::vector
// classnum = 3 auto maxSPtr = std::max_element(kps_ptr, kps_ptr + 3); // auto maxSPtr = std::max_element(kps_ptr+2, kps_ptr + 3); // auto maxSPtr = std::max_element(kps_ptr+3, kps_ptr + 3);
// Not Detect label cout << func << ";label=" << label << endl; .....
int cnt = 0; /*
ifdef BATCHED_NMS
cv::dnn::NMSBoxesBatched(bboxes, scores, labels, score_thresd, iou_thres, indices);
else
cv::dnn::NMSBoxes(bboxes, scores, score_thres, iou_thres, indices);
endif
for(auto& i : indices) */ // 8 object Detect, but almost same position and size. for(int i = 0; i < bboxes.size(); i++) { if(cnt >= topk) break; Object obj; obj.rect = bboxes[i]; obj.prob = scores[i]; obj.label = labels[i]; obj.kps = kpss[i]; objs.push_back(obj); cnt += 1; } } ....