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Fix YOLOv8 C++ ONNXRuntime transpose op (#15779)

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Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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memorylorry 2024-08-25 07:05:52 +08:00 • committed by GitHub
parent e2b04dc853
commit dc15242cbd
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1 changed files with 5 additions and 5 deletions
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10
examples/YOLOv8-ONNXRuntime-CPP/inference.cpp
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@ -221,8 +221,8 @@ char* YOLO_V8::TensorProcess(clock_t& starttime_1, cv::Mat& iImg, N& blob, std::
case YOLO_DETECT_V8: case YOLO_DETECT_V8:
case YOLO_DETECT_V8_HALF: case YOLO_DETECT_V8_HALF:
{ {
int strideNum = outputNodeDims[1];//8400 int signalResultNum = outputNodeDims[1];//84
int signalResultNum = outputNodeDims[2];//84 int strideNum = outputNodeDims[2];//8400
std::vector<int> class_ids; std::vector<int> class_ids;
std::vector<float> confidences; std::vector<float> confidences;
std::vector<cv::Rect> boxes; std::vector<cv::Rect> boxes;
@ -230,18 +230,18 @@ char* YOLO_V8::TensorProcess(clock_t& starttime_1, cv::Mat& iImg, N& blob, std::
if (modelType == YOLO_DETECT_V8) if (modelType == YOLO_DETECT_V8)
{ {
// FP32 // FP32
rawData = cv::Mat(strideNum, signalResultNum, CV_32F, output); rawData = cv::Mat(signalResultNum, strideNum, CV_32F, output);
} }
else else
{ {
// FP16 // FP16
rawData = cv::Mat(strideNum, signalResultNum, CV_16F, output); rawData = cv::Mat(signalResultNum, strideNum, CV_16F, output);
rawData.convertTo(rawData, CV_32F); rawData.convertTo(rawData, CV_32F);
} }
//Note: //Note:
//ultralytics add transpose operator to the output of yolov8 model.which make yolov8/v5/v7 has same shape //ultralytics add transpose operator to the output of yolov8 model.which make yolov8/v5/v7 has same shape
//https://github.com/ultralytics/assets/releases/download/v8.2.0/yolov8n.pt //https://github.com/ultralytics/assets/releases/download/v8.2.0/yolov8n.pt
//rowData = rowData.t(); rawData = rawData.t();
float* data = (float*)rawData.data; float* data = (float*)rawData.data;