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Update yolov8_seg_onnx.cpp #31

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13 changes: 7 additions & 6 deletions yolov8_seg_onnx.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -163,6 +163,7 @@ bool Yolov8SegOnnx::ReadModel(const std::string& modelPath, bool isCuda, int cud
catch (const std::exception&) {
return false;
}
return true;

}

Expand Down Expand Up @@ -240,9 +241,9 @@ bool Yolov8SegOnnx::OnnxBatchDetect(std::vector<cv::Mat>& srcImgs, std::vector<s
all_data += one_output_length;
float* pdata = (float*)output0.data;
int rows = output0.rows;
std::vector<int> class_ids;//���id����
std::vector<float> confidences;//���ÿ��id��Ӧ���Ŷ�����
std::vector<cv::Rect> boxes;//ÿ��id���ο�
std::vector<int> class_ids;//结果id数组
std::vector<float> confidences;//结果每个id对应置信度数组
std::vector<cv::Rect> boxes;//每个id矩形框
std::vector<vector<float>> picked_proposals; //output0[:,:, 5 + _className.size():net_width]===> for mask
for (int r = 0; r < rows; ++r) { //stride
cv::Mat scores(1, _className.size(), CV_32F, pdata + 4);
Expand All @@ -264,7 +265,7 @@ bool Yolov8SegOnnx::OnnxBatchDetect(std::vector<cv::Mat>& srcImgs, std::vector<s
confidences.push_back(max_class_socre);
boxes.push_back(Rect(left, top, int(w + 0.5), int(h + 0.5)));
}
pdata += net_width;//��һ��
pdata += net_width;//下一行
}

vector<int> nms_result;
Expand Down Expand Up @@ -294,7 +295,7 @@ bool Yolov8SegOnnx::OnnxBatchDetect(std::vector<cv::Mat>& srcImgs, std::vector<s
}

//******************** ****************
// �ϰ汾�ķ�������������ڿ�����ע�͵IJ���֮��һֱ����������ʹ�������
// 老版本的方案，如果上面在开启我注释的部分之后还一直报错，建议使用这个。
// If the GetMask2() still reports errors , it is recommended to use GetMask().
//Mat mask_proposals;
//for (int i = 0; i < temp_mask_proposals.size(); ++i) {
Expand All @@ -310,4 +311,4 @@ bool Yolov8SegOnnx::OnnxBatchDetect(std::vector<cv::Mat>& srcImgs, std::vector<s
return true;
else
return false;
}
}