Comments (3)
@lyb36524
If the code is running in the TX2 device, please modify the code(
Line 150 in a0de42f
//-------------------------------------------------------------------------------------------------------------
void yolo::YOLO::copy(const std::vectorcv::Mat& imgsBatch)
{
#if 0
cv::Mat img_fp32 = cv::Mat::zeros(imgsBatch[0].size(), CV_32FC3); // todo
cudaHostRegister(img_fp32.data, img_fp32.elemSize() * img_fp32.total(), cudaHostRegisterPortable);
float* pi = m_input_src_device;
for (size_t i = 0; i < imgsBatch.size(); i++)
{
imgsBatch[i].convertTo(img_fp32, CV_32FC3);
checkRuntime(cudaMemcpy(pi, img_fp32.data, sizeof(float) * 3 * m_param.src_h * m_param.src_w, cudaMemcpyHostToDevice));
pi += 3 * m_param.src_h * m_param.src_w;
}
cudaHostUnregister(img_fp32.data);
#endif
#if 1 // for Nvidia TX2
cv::Mat img_fp32 = cv::Mat::zeros(imgsBatch[0].size(), CV_32FC3); // todo
float* pi = m_input_src_device;
for (size_t i = 0; i < imgsBatch.size(); i++)
{
std::vector img_vec = std::vector(imgsBatch[i].reshape(1, 1));
imgsBatch[i].convertTo(img_fp32, CV_32FC3);
checkRuntime(cudaMemcpy(pi, img_fp32.data, sizeof(float) * 3 * m_param.src_h * m_param.src_w, cudaMemcpyHostToDevice));
pi += 3 * m_param.src_h * m_param.src_w;
}
#endif
}
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from tensorrt-alpha.
This part of the code has been modified to be compatible with TX2.
Line 178 in 72cdd9d
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