首先附上github链接，里面其实有比较详细的安装教程了，不过完全照做会有些小坑
GitHub - visionml/pytracking: Visual tracking library based on PyTorch.
1. Create and activate a conda environment

conda create --name pytracking python=3.7 conda activate pytracking

2. Install PyTorch
Install PyTorch with cuda10.

文章图片

由于我使用的是RTX3060不支持cuda10，正好试一下cuda11的支持情况，在pytorch官网找命令
Start Locally | PyTorch

pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html

（注意，我使用pip安装下面会遇到坑，建议直接使用conda安装）

conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch

Note:

• It is possible to use any PyTorch supported version of CUDA (not necessarily v10).
• For more details about PyTorch installation, see Previous PyTorch Versions | PyTorch.

3. Install matplotlib, pandas, tqdm, opencv, scikit-image, visdom, tikzplotlib, gdown, and tensorboad

conda install matplotlib pandas tqdm pip install opencv-python visdom tb-nightly scikit-image tikzplotlib gdown

Install the coco and lvis toolkits

conda install cython pip install pycocotools pip install lvis

Install ninja-build for Precise ROI pooling
To compile the Precise ROI pooling module (https://github.com/vacancy/PreciseRoIPooling), you may additionally have to install ninja-build.

sudo apt-get install ninja-build

In case of issues, we refer to https://github.com/vacancy/PreciseRoIPooling.
Install spatial-correlation-sampler (only required for KYS tracker)

pip install spatial-correlation-sampler

【单目标追踪|pytracking框架 服务器端配置采坑（ubuntu18.04+cuda11.3）】In case of issues, we refer to https://github.com/ClementPinard/Pytorch-Correlation-extension.
Install jpeg4py
In order to use jpeg4py for loading the images instead of OpenCV's imread(), install jpeg4py in the following way,

sudo apt-get install libturbojpeg pip install jpeg4py

Note: The first step (sudo apt-get install libturbojpeg) can be optionally ignored, in which case OpenCV's imread() will be used to read the images. However the second step is a must.
In case of issues, we refer to https://github.com/ajkxyz/jpeg4py.
4. Setup the environment
Create the default environment setting files.

# Environment settings for pytracking. Saved at pytracking/evaluation/local.py python -c "from pytracking.evaluation.environment import create_default_local_file; create_default_local_file()"# Environment settings for ltr. Saved at ltr/admin/local.py python -c "from ltr.admin.environment import create_default_local_file; create_default_local_file()"

You can modify these files to set the paths to datasets, results paths etc.
这两部会创建用于配置路径的两个local.py，等下会提到
5. Download the pre-trained networks
You can download the pre-trained networks from the google drive folder. The networks shoud be saved in the directory set by "network_path" in "pytracking/evaluation/local.py". By default, it is set to pytracking/networks. You can also download the networks using the gdown python package.

# Download the default network for DiMP-50 and DiMP-18 gdown https://drive.google.com/uc\?id\=1qgachgqks2UGjKx-GdO1qylBDdB1f9KN -O pytracking/networks/dimp50.pth gdown https://drive.google.com/uc\?id\=1MAjrRJDCbL0DSjUKFyDkUuYS1-cYBNjk -O pytracking/networks/dimp18.pth# Download the default network for ATOM gdown https://drive.google.com/uc\?id\=1VNyr-Ds0khjM0zaq6lU-xfY74-iWxBvU -O pytracking/networks/atom_default.pth# Download the default network for ECO gdown https://drive.google.com/uc\?id\=1aWC4waLv_te-BULoy0k-n_zS-ONms21S -O pytracking/networks/resnet18_vggmconv1.pth

考虑到梯子问题，也可以自己下好，放到对应目录即可（对应位置同样可以查看local.py文件）
6.补全一些文件
我这边直接使用git的命令会缺失一些文件
github的issues里面有解决办法

git clone https://github.com/visionml/pytracking.git cd pytracking

git submodule update --init

如果仍然报错，就需要挂梯子，或者手动下载，再加入目录里面
主要是这里的文件
7. 下载数据集并配置数据集位置

8.运行报错

Evaluating1 trackers on1 sequences Tracker: atom default None ,Sequence: Soccer Setting up a new session... ../pytracking/features/featurebase.py:78: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor'). return TensorList([im_sz // s for s in self.stride()]) ../pytracking/features/preprocessing.py:109: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor'). tl = posl - (szl - 1) // 2 ../pytracking/features/preprocessing.py:110: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor'). br = posl + szl//2 + 1 /home/admin312/anaconda3/envs/pytracking/lib/python3.7/site-packages/torch/nn/functional.py:3635: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details. "See the documentation of nn.Upsample for details.".format(mode) Using /home/admin312/.cache/torch_extensions/py37_cu113 as PyTorch extensions root... Detected CUDA files, patching ldflags Emitting ninja build file /home/admin312/.cache/torch_extensions/py37_cu113/_prroi_pooling/build.ninja... Building extension module _prroi_pooling... Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N) [1/3] :/usr/local/cuda-11.3/bin/nvcc-DTORCH_EXTENSION_NAME=_prroi_pooling -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -isystem /home/admin312/anaconda3/envs/pytracking/lib/python3.7/site-packages/torch/include -isystem /home/admin312/anaconda3/envs/pytracking/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -isystem /home/admin312/anaconda3/envs/pytracking/lib/python3.7/site-packages/torch/include/TH -isystem /home/admin312/anaconda3/envs/pytracking/lib/python3.7/site-packages/torch/include/THC -isystem :/usr/local/cuda-11.3/include -isystem /home/admin312/anaconda3/envs/pytracking/include/python3.7m -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_86,code=compute_86 -gencode=arch=compute_86,code=sm_86 --compiler-options '-fPIC' -std=c++14 -c /home/admin312/lzm_project/pytracking/pytracking/ltr/external/PreciseRoIPooling/pytorch/prroi_pool/src/prroi_pooling_gpu_impl.cu -o prroi_pooling_gpu_impl.cuda.o FAILED: prroi_pooling_gpu_impl.cuda.o :/usr/local/cuda-11.3/bin/nvcc-DTORCH_EXTENSION_NAME=_prroi_pooling -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -isystem /home/admin312/anaconda3/envs/pytracking/lib/python3.7/site-packages/torch/include -isystem /home/admin312/anaconda3/envs/pytracking/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -isystem /home/admin312/anaconda3/envs/pytracking/lib/python3.7/site-packages/torch/include/TH -isystem /home/admin312/anaconda3/envs/pytracking/lib/python3.7/site-packages/torch/include/THC -isystem :/usr/local/cuda-11.3/include -isystem /home/admin312/anaconda3/envs/pytracking/include/python3.7m -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_86,code=compute_86 -gencode=arch=compute_86,code=sm_86 --compiler-options '-fPIC' -std=c++14 -c /home/admin312/lzm_project/pytracking/pytracking/ltr/external/PreciseRoIPooling/pytorch/prroi_pool/src/prroi_pooling_gpu_impl.cu -o prroi_pooling_gpu_impl.cuda.o /bin/sh: 1: :/usr/local/cuda-11.3/bin/nvcc: not found [2/3] c++ -MMD -MF prroi_pooling_gpu.o.d -DTORCH_EXTENSION_NAME=_prroi_pooling -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -isystem /home/admin312/anaconda3/envs/pytracking/lib/python3.7/site-packages/torch/include -isystem /home/admin312/anaconda3/envs/pytracking/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -isystem /home/admin312/anaconda3/envs/pytracking/lib/python3.7/site-packages/torch/include/TH -isystem /home/admin312/anaconda3/envs/pytracking/lib/python3.7/site-packages/torch/include/THC -isystem :/usr/local/cuda-11.3/include -isystem /home/admin312/anaconda3/envs/pytracking/include/python3.7m -D_GLIBCXX_USE_CXX11_ABI=0 -fPIC -std=c++14 -c /home/admin312/lzm_project/pytracking/pytracking/ltr/external/PreciseRoIPooling/pytorch/prroi_pool/src/prroi_pooling_gpu.c -o prroi_pooling_gpu.o FAILED: prroi_pooling_gpu.o c++ -MMD -MF prroi_pooling_gpu.o.d -DTORCH_EXTENSION_NAME=_prroi_pooling -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -isystem /home/admin312/anaconda3/envs/pytracking/lib/python3.7/site-packages/torch/include -isystem /home/admin312/anaconda3/envs/pytracking/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -isystem /home/admin312/anaconda3/envs/pytracking/lib/python3.7/site-packages/torch/include/TH -isystem /home/admin312/anaconda3/envs/pytracking/lib/python3.7/site-packages/torch/include/THC -isystem :/usr/local/cuda-11.3/include -isystem /home/admin312/anaconda3/envs/pytracking/include/python3.7m -D_GLIBCXX_USE_CXX11_ABI=0 -fPIC -std=c++14 -c /home/admin312/lzm_project/pytracking/pytracking/ltr/external/PreciseRoIPooling/pytorch/prroi_pool/src/prroi_pooling_gpu.c -o prroi_pooling_gpu.o In file included from /home/admin312/lzm_project/pytracking/pytracking/ltr/external/PreciseRoIPooling/pytorch/prroi_pool/src/prroi_pooling_gpu.c:15:0: /home/admin312/anaconda3/envs/pytracking/lib/python3.7/site-packages/torch/include/ATen/cuda/CUDAContext.h:5:10: fatal error: cuda_runtime_api.h: 没有那个文件或目录 #include ^~~~~~~~~~~~~~~~~~~~ compilation terminated. ninja: build stopped: subcommand failed. Traceback (most recent call last): File "/home/admin312/anaconda3/envs/pytracking/lib/python3.7/site-packages/torch/utils/cpp_extension.py", line 1723, in _run_ninja_build env=env) File "/home/admin312/anaconda3/envs/pytracking/lib/python3.7/subprocess.py", line 512, in run output=stdout, stderr=stderr) subprocess.CalledProcessError: Command '['ninja', '-v']' returned non-zero exit status 1.The above exception was the direct cause of the following exception:Traceback (most recent call last): File "run_tracker.py", line 65, in main() File "run_tracker.py", line 61, in main args.threads, {'use_visdom': args.use_visdom, 'server': args.visdom_server, 'port': args.visdom_port}) File "run_tracker.py", line 37, in run_tracker run_dataset(dataset, trackers, debug, threads, visdom_info=visdom_info) File "../pytracking/evaluation/running.py", line 199, in run_dataset run_sequence(seq, tracker_info, debug=debug, visdom_info=visdom_info) File "../pytracking/evaluation/running.py", line 148, in run_sequence output = tracker.run_sequence(seq, debug=debug, visdom_info=visdom_info) File "../pytracking/evaluation/tracker.py", line 148, in run_sequence output = self._track_sequence(tracker, seq, init_info) File "../pytracking/evaluation/tracker.py", line 186, in _track_sequence out = tracker.initialize(image, init_info) File "../pytracking/tracker/atom/atom.py", line 115, in initialize self.init_iou_net() File "../pytracking/tracker/atom/atom.py", line 694, in init_iou_net target_feat = self.iou_predictor.get_modulation(iou_backbone_features, target_boxes) File "../ltr/models/bbreg/atom_iou_net.py", line 157, in get_modulation roi3r = self.prroi_pool3r(c3_r, roi1) File "/home/admin312/anaconda3/envs/pytracking/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl return forward_call(*input, **kwargs) File "../ltr/external/PreciseRoIPooling/pytorch/prroi_pool/prroi_pool.py", line 28, in forward return prroi_pool2d(features, rois, self.pooled_height, self.pooled_width, self.spatial_scale) File "../ltr/external/PreciseRoIPooling/pytorch/prroi_pool/functional.py", line 44, in forward _prroi_pooling = _import_prroi_pooling() File "../ltr/external/PreciseRoIPooling/pytorch/prroi_pool/functional.py", line 33, in _import_prroi_pooling verbose=True File "/home/admin312/anaconda3/envs/pytracking/lib/python3.7/site-packages/torch/utils/cpp_extension.py", line 1136, in load keep_intermediates=keep_intermediates) File "/home/admin312/anaconda3/envs/pytracking/lib/python3.7/site-packages/torch/utils/cpp_extension.py", line 1347, in _jit_compile is_standalone=is_standalone) File "/home/admin312/anaconda3/envs/pytracking/lib/python3.7/site-packages/torch/utils/cpp_extension.py", line 1452, in _write_ninja_file_and_build_library error_prefix=f"Error building extension '{name}'") File "/home/admin312/anaconda3/envs/pytracking/lib/python3.7/site-packages/torch/utils/cpp_extension.py", line 1733, in _run_ninja_build raise RuntimeError(message) from e RuntimeError: Error building extension '_prroi_pooling'

抓重点来看就是cuda的问题，cuda11真的万恶之源
我当时使用的是最新的cuda11.5，于是参照下面这篇帖子卸载重装了cuda11.4（因为之前11.3不行，pytorch1.10又只支持11.3以上）

9.torch需要降级
重装之后编译正常，但torch报错

文章图片

由于这些是torch1.7中的写法，1.8以后不复存在，且网上搜了一通找不到替代品，在pytorch官网查了一下，1.7以上不不止rfft，1.7一下不支持cuda11，妙啊，夹缝中求生存
于是conda卸载重装pytorch1.7，cuda则安装cuda11.0与cuda11.4并存，这个教程很多了


10.然后cuda11.0没办法编译PreciseRolPooling
就是那个compute_86 的错误，之前指github issues里看到过这个错误，更到11.3版本后可解，很好，很好



好吧我暂时放弃了，过几天冷静了看看能不能手动改torch.rfft或者绕过去


参考链接
pytracking系列跟踪算法的配置（LWL, KYS, PrDiMP, DiMP and ATOM Trackers）（Ubuntu版本）_博博有个大大大的Dream-CSDN博客_pytracking训练

(5条消息) [Object Tracking][环境配置流程][Ubuntu16.04]ATOM【CVPR2019】pytracking_llzxz9628的博客-CSDN博客
Ubuntu之cuda11.4安装_月生的静心苑-CSDN博客

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