Copy // 置信度过滤 torch::Tensor conf_mask = scores > conf_threshold; if (conf_mask.sum().item<int>() == 0) { return std::vector<size_t>(); } std::cout << "原来框数量: " << scores.numel() << std::endl; // 只保留高置信度的
COMMAND ${CMAKE_COMMAND} -E copy_if_different ${TORCH_DLLS} $<TARGET_FILE_DIR:example-app>) endif (MSVC) example-test.cpp内容如下: #include <torch/torch.h> #include <iostream> int main() { torch::Tensor tensor = torch::rand({2, 3}); std::cout << tensor << std::endl; } ...
as this link: said, I tried to copy all the DLLs in LibTorch to the directory of my executable, but it's invalid. cc @peterjc123 @mszhanyi @skyline75489 @nbcsm
labelImg,标注完是json格式,自己完成json文件 -> mask图片功能 U2-Net主要测试多组数据集: 训练数据集:在DUTS-TR上训练的网络,它是DUTS数据集的一部分。DUTS-TR包含共10553张图片。目前,它是最大的用于显著目标检测的常用训练数据集。训练之前,做了平翻转来扩充这个数据集,也就是21106张图像。 评估数据集:六个...
cout << "mask4 = " << mask4 << std::endl;*/41torch::Tensor mask5 = torch::tensor({ {1}, {0}, {1} }, torch::kBool);42std::cout <<"mask5 ="<< mask5 << std::endl; std::cout <<std::endl;43std::cout <<"mask5.size() ="<< mask5.sizes() << std::endl; ...
🐛 Bug Hi, I use CPP torch fronted API with thrust library (but independent). When I call torch function mask_select on tensor which is a store at GPU and mask which is store on GPU too (result is store on GPU), I get an error. terminate ...
(tmp_model,backbone_tensor)backbone_jit.save(os.path.join(args.output_path,'backbone.pth'))#rpn#convconv_in_channels=model.rpn.head.conv.weight.shape[1]conv_tensor=torch.zeros(2,conv_in_channels,10,10)conv_jit=torch.jit.trace(model.rpn.head.conv,conv_tensor)conv_jit.save(os.path.join...
I am not sure what's that since the variableimgis a type of torch.Tensor... so it should be fine? Copy link Contributor zhiqwangcommentedDec 26, 2020 Hi@femust, I think that you can refer to the unittest as below: detr/test_all.py ...
这个新的实现使得两者符合了c++11的标准,具体来说是取消了Copy-On-Write。那么,这样子虽然符合了c++11的标注,旧版不就无法兼容了吗。为了避免上述混乱,对于旧版而言,GCC5.1添加了__cxx11命名空间,GCC5.1或者说c++11规范下的string和list,实际上是std::__cxx11::string和std::__cxx11::list,所以我们一般的...