CMakeFiles/ORB_SLAM2.dir/src/InstanceDetect.cc.o:在函数‘PSROIPool_backward(at::Tensor const&, at::Tensor const&, at::Tensor const&, float, int, int, int, int, int, int)’中: InstanceDetect.cc:(.text+0x1430): `PSRO
1Mat frame = cv::imread("1.png", IMREAD_COLOR);2cvtColor(frame, frame, CV_BGR2RGB);//转换色彩通道3frame.convertTo(frame, CV_32FC3,1.0f/255.0f);4auto tensor_image =torch::from_blob(frame.data, {frame.rows, frame.cols, frame.channels()});5//换chw;6tensor_image = tensor_image...
// Create a vector of inputs. std::vector<torch::jit::IValue> inputs; inputs.push_back(tensor_image); 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 可以看到,其实语法都是跟python里面类似的。 运行forward函数,得到CenterNet最终输出。 auto outputs = module.forward(inputs)....
libtorch 报错与解决 1.error: conversion from ‘at::TensorAccessor<float, 2ul, at::DefaultPtrTraits, long int>’ to non-scalar type ‘at::Tensor’ requested torch::Tensor result_data = result_.accessor<float,2>();// torch::Tensor result_data = result_.cpu().accessor<float,2>(); 定...
"read src image ok" << endl; cout << "module forward" << endl; auto output = module.forward({ srcTensor, bgrTensor }).toTensor(); cout << "module forward over" << endl; Tensor mask = output.permute({ 0, 2, 3, 1 }).detach().index({ 0, "...", 0 }); mask.mul_(255...
RuntimeError: forward(__torch__.models.transformer.Transformer self, Tensor src, Tensor mask, Tensor query_embed, Tensor pos_embed) -> ((Tensor, Tensor)): Expected a value of type 'Tensor (inferred)' for argument 'mask' but instead found type 'Optional[Tensor]'. Inferred 'mask' to be...
// Create a vector of inputs. std::vectorinputs; inputs.push_back(torch::ones({1, 3, 224, 224})); // Execute the model and turn its output into a tensor. at::Tensor output = module.forward(inputs).toTensor(); std::cout << output.slice(/*dim=*/1, /*start=*/0, /*end...
OK, 切换到物体检测模型,https://pytorch.org/docs/master/torchvision/models.html#object-detection-instance-segmentation-and-person-keypoint-detection,试了一下pre_trained faster rcnn,巨慢,我印象里detectron2里面的maskrcnn也没有这么慢啊,咋回事,那个就5,6秒,重启了一次,好像速度变正常了。
startp, endp是int形的,转成tensor,再在forward里面解析出int endp = endp.cpu().numpy()[0] 解决方案如上,在此记录一下! https://github.com/xi11xi19/CenterNet2TorchScript/issues/5 4 libtorch 运行时间问题 一般情况下,我们用c++或者opencv自带的函数统计函数运行时间 ...
Or when I move mask tensor to CPU. But it works, I am not sure, if it a good approach to have a mask tensor on CPU and other tensors are store at GPU? (my second questions) To Reproduce I create a small demo program, with the issue. main.cu #include <thrust/execution_policy....