一.maskrcnn配置环境
1.前提:
虚拟环境anaconda+pytorch1.0 nightly(就是最新版,但是2024年的最新版pytorch已经不适配了,我这里用的是1.7.0)
1.1anaconda下载安装 链接:
是我们导师给的链接
pycharm、anaconda、pytorch安装以及环境配置（超详细教程）_pycharm配置anaconda运行环境-CSDN博客
1.2maskrcnn官网链接:
facebookresearch/maskrcnn-benchmark：PyTorch 中实例分割和对象检测算法的快速模块化参考实现。 (github.com)
1.3pytorch1.7.0 CUDA版本为11.0，CUDNN版本为8.9.2
1.安装多个cuda的教程我看的这个:https://blog.csdn.net/weixin_39450145/article/details/125630585?spm=1001.2014.3001.5506
2.cuda11.0 cuDNN的安装我看的这个:
Windows10系统pytorch、cuda11.0、cuDNN安装_cudnn11-CSDN博客
注:1.这步主要安装对应的cuda环境,不要安装pytorch
2.只有NVIDIA的显卡能安装cuda
3.cuda最高能安装到什么版本要看自己的显卡
在终端输入:nvidia-smi可以看到
2.按照官网一步一步配置环境
1.Requirements:
- PyTorch 1.0 from a nightly release. It will not work with 1.0 nor 1.0.1. Installation instructions can be found in Start Locally | PyTorch
- torchvision from master
- cocoapi
- yacs
- matplotlib
- GCC >= 4.9
- OpenCV
- CUDA >= 9.0
2.Install
2.1创建虚拟环境
conda create --name maskrcnn_benchmark python==3.7 -y
conda activate maskrcnn_benchmark2.2 为新python安装正确的pip和依赖项
conda install ipython pip
2.3安装依赖（opencv建议安装低版本）：
pip install ninja yacs cython matplotlib tqdm -i https://pypi.tuna.tsinghua.edu.cn/simple
pip install opencv-python==3.4.10.35 -i https://pypi.tuna.tsinghua.edu.cn/simple2.4安装Pytorch(这里建议安装1.7.0版本)
conda install pytorch==1.7.0 torchvision==0.8.0 torchaudio==0.7.0 cudatoolkit=11.0 -c pytorch2.5正式安装（官方步骤）：
首先保证你下载了vs2019,因为这个项目只支持2015-2019的版本!!!!!!!!!!!!!!!!!很重要因为这一步不对我后续报超级多错
下载vs2019链接:Visual Studio 2019 下载安装_vs2019下载-CSDN博客
我也建议咱们在下一个Microsoft Visual C++ Build Tools14.0(但是报错后先下载了vstools14.0 和我原有的visual stdio2022运行的,到最后一步vs版本还是不对,我又下的vs2019,所以Tools14.0我不确定是否必须下载,感兴趣的可以先不下14.0看看报不报错)
2.5.1pycocotools,cityscapesScripts
export INSTALL_DIR=$PWD
# install pycocotools
cd $INSTALL_DIR
git clone https://github.com/cocodataset/cocoapi.git
cd cocoapi/PythonAPI
python setup.py build_ext install
# install cityscapesScripts
cd $INSTALL_DIR
git clone https://github.com/mcordts/cityscapesScripts.git
cd cityscapesScripts/
python setup.py build_ext install需要注意的以及可能会出现的报错:
1.这里要用到git下载项目,我用的下载教程:
Git下载安装及环境配置，解决安装包下载慢问题（详细版）-CSDN博客
git安装详细过程及常见错误解决过程_安装git网络问题-CSDN博客
2.Microsoft Visual C++ 14.0 is required. Get it with "Build Tools for Visual Studio": https://visualstudio.microsoft.com/downloads/ Tools"
error: Microsoft Visual C++ 14.0 is required. Get it with "Build Tools for Visual Studio": https://visualstudio.microsoft.com/downloads/ Tools":
因为我没安装Visual Studio，就出了这个错
解决方法（不用下Visual Studio，下一个Microsoft Visual C++ Build Tools安装就行）
安装方法：visual c++ build tools的安装与使用
我下载的是这个链接的vs14.0:maskrcnn-benchmark win10安装报错及解决方案_attrs==21.2.0-CSDN博客
下载 visualcppbuildtools_full.exe. 目前从网上找到的不是无法安装就是损坏，可从百度网盘下载。
链接：百度网盘 请输入提取码
提取码：1234
解压后直接点击安装即可安装后要配置变量，就跟这个链接一步一步做就行
3.Error checking compiler version for cl: [WinError 2] 系统找不到指定的文件.warnings.warn('Error checking compiler version for {}: {}'.format(compiler, error)) 代表找不到cl.exe这个文件->配置环境变量就行
如果报这个错可以看这个链接:小白跑deep snake（巨详细）_thcnumerics.cuh(196): error : more than one operat-CSDN博客
E:\Python\Lib\site-packages\torch\utils\cpp_extension.py:189: UserWarning: Error checking compiler version for cl: [WinError 2] 系统找不到指定的文件。
warnings.warn('Error checking compiler version for {}: {}'.format(compiler, error))
这是我所有配置的环境变量可以借鉴一下.
4.''Your compiler (cl 19.00.24210) may be ABI-incompatible with PyTorch!
Please use a compiler that is ABI-compatible with GCC 4.9 and above.
See https://gcc.gnu.org/onlinedocs/libstdc++/manual/abi.html.''
E:\Python\lib\site-packages\torch(utils\cpp_extension.py:191: UserWarning:
!! WARNING !!
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
Your compiler (cl 19.00.24210) may be ABI-incompatible with PyTorch!
Please use a compiler that is ABI-compatible with GCC 4.9 and above.
See https://gcc.gnu.org/onlinedocs/libstdc++/manual/abi.html.
See https://gist.github.com/goldsborough/d466f43e8ffc948ff92de7486c5216d6
for instructions on how to install GCC 4.9 or higher.
编译器cl跟PyTorch不兼容,不用管,只是个WARING 我们主要解决ERROR就行
2.5.2安装apex：
建议用git克隆完整的apex包，然后再退回老版本的apex
cd $INSTALL_DIR
git clone https://github.com/NVIDIA/apex.git #git克隆，不要用网页下载压缩包
cd apex
git checkout f3a960f80244cf9e80558ab30f7f7e8cbf03c0a0 # 回退到老版本
python setup.py install --cuda_ext --cpp_ext2.5.3安装maskrcnn：
cd $INSTALL_DIR
git clone https://github.com/facebookresearch/maskrcnn-benchmark.git
cd maskrcnn-benchmark
# 添加路径
cuda_dir="maskrcnn_benchmark/csrc/cuda"
perl -i -pe 's/AT_CHECK/TORCH_CHECK/' $cuda_dir/deform_pool_cuda.cu $cuda_dir/deform_conv_cuda.cu
# You can then run the regular setup command
# 编译
python setup.py build develop2.6其余我遇到的报错:
1.编译错误：error: identifier “AT_CHECK“ is undefined
编译错误：error: identifier “AT_CHECK“ is undefined_atcheck torchcheck-CSDN博客
2.计算机丢失mspdb60.dll6,VC++6.0提示找不到mspdb60.dll之解决办法
计算机丢失mspdb60.dll6,VC++6.0提示找不到mspdb60.dll之解决办法-CSDN博客
3.error: command ‘C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\bin\nvcc.exe’ failed with exit status 1
maskrcnn-benchmark win10安装报错及解决方案_attrs==21.2.0-CSDN博客
4.windows环境下cuda报错：nvcc fatal : Unsupported gpu architecture ‘compute_86‘ !!!!!!!!!找了很久的一个错
windows环境下cuda报错：nvcc fatal : Unsupported gpu architecture ‘compute_86‘_peft cuda 报错-CSDN博客
5.“subprocess.CalledProcessError: Command ‘[‘ninja‘, ‘-v‘]‘ returned non-zero exit status 1”解决方法
6.讲解cl: 命令行 error D8021 :无效的数值参数“/Wno-cpp” 和 cl: 命令行 error D8021 :无效的数值参数“/Wno-unused-function”
3.总体环境+版本pip list +conda list
(maskrcnn_benchmark) C:\Users\86189>pip list
Package Version Editable project location
------------------- ----------- -------------------------------
aiohttp 3.8.6
aiosignal 1.3.1
apex 0.1
appdirs 1.4.4
async-timeout 4.0.3
asyncio 3.4.3
asynctest 0.13.0
attrs 23.2.0
Automat 22.10.0
backcall 0.2.0
beautifulsoup4 4.12.3
bs4 0.0.2
certifi 2024.2.2
cffi 1.15.1
charset-normalizer 3.3.2
cityscapesScripts 2.2.3
colorama 0.4.6
coloredlogs 15.0.1
constantly 15.1.0
cryptography 42.0.8
cssselect 1.2.0
curl-cffi 0.5.10
cycler 0.11.0
Cython 3.0.10
decorator 4.4.2
dnspython 2.3.0
exceptiongroup 1.2.1
filelock 3.12.2
flit_core 3.6.0
fonttools 4.38.0
frozenlist 1.3.3
gevent 22.10.2
greenlet 3.0.3
h11 0.14.0
humanfriendly 10.0
hyperlink 21.0.0
idna 3.7
imageio 2.31.2
imageio-ffmpeg 0.4.9
importlib-metadata 6.7.0
incremental 22.10.0
ipython 7.31.1
itemadapter 0.8.0
itemloaders 1.1.0
jedi 0.18.1
jmespath 1.0.1
jsonpath 0.82.2
kiwisolver 1.4.5
lxml 5.2.2
lxml-stubs 0.5.1
maskrcnn-benchmark 0.1 e:\pytorch__\maskrcnn-benchmark
matplotlib 3.5.3
matplotlib-inline 0.1.6
mkl-fft 1.3.1
mkl-random 1.2.2
mkl-service 2.4.0
moviepy 1.0.3
multidict 6.0.5
ninja 1.11.1.1
numpy 1.21.6
opencv-python 3.4.10.35
outcome 1.3.0.post0
packaging 24.0
parsel 1.8.1
parso 0.8.3
pickleshare 0.7.5
Pillow 9.5.0
pip 24.0
proglog 0.1.10
prompt-toolkit 3.0.36
Protego 0.3.0
py 1.11.0
pyasn1 0.5.1
pyasn1-modules 0.3.0
pycocotools 2.0
pycparser 2.21
PyDispatcher 2.0.7
PyExecJS 1.5.1
Pygments 2.11.2
pymongo 4.7.2
pyOpenSSL 24.1.0
pyparsing 3.1.2
pyquaternion 0.9.9
pyquery 2.0.0
pyreadline 2.1
PySocks 1.7.1
python-dateutil 2.9.0.post0
PyYAML 6.0.1
queuelib 1.6.2
requests 2.31.0
requests-file 2.1.0
retry 0.9.2
retrying 1.3.4
Scrapy 2.9.0
selenium 4.11.2
service-identity 21.1.0
setuptools 59.6.0
six 1.16.0
sniffio 1.3.1
sortedcontainers 2.4.0
soupsieve 2.4.1
tldextract 4.0.0
torch 1.7.0
torchaudio 0.7.0
torchvision 0.8.0
tqdm 4.66.4
traitlets 5.7.1
trio 0.22.2
trio-websocket 0.11.1
Twisted 22.10.0
twisted-iocpsupport 1.0.4
typing 3.10.0.0
typing_extensions 4.7.1
urllib3 2.0.7
w3lib 2.1.2
wcwidth 0.2.5
wheel 0.38.4
wincertstore 0.2
wsproto 1.2.0
yacs 0.1.8
yarl 1.9.4
zipp 3.15.0
zope.event 5.0
zope.interface 6.4.post2(maskrcnn_benchmark) C:\Users\86189>conda list
# packages in environment at E:\Python37\anaconda3\envs\maskrcnn_benchmark:
#
# Name Version Build Channel
apex 0.1 pypi_0 pypi
appdirs 1.4.4 pypi_0 pypi
backcall 0.2.0 pyhd3eb1b0_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
blas 1.0 mkl https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
certifi 2022.12.7 py37haa95532_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
cityscapesscripts 2.2.3 pypi_0 pypi
colorama 0.4.6 py37haa95532_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
coloredlogs 15.0.1 pypi_0 pypi
cudatoolkit 11.0.221 h74a9793_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
cycler 0.11.0 pypi_0 pypi
cython 3.0.10 pypi_0 pypi
decorator 5.1.1 pyhd3eb1b0_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
flit-core 3.6.0 pyhd3eb1b0_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
freetype 2.12.1 ha860e81_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
giflib 5.2.1 h8cc25b3_3 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
humanfriendly 10.0 pypi_0 pypi
intel-openmp 2021.4.0 haa95532_3556 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
ipython 7.31.1 py37haa95532_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
jedi 0.18.1 py37haa95532_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
jpeg 9e h2bbff1b_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
kiwisolver 1.4.5 pypi_0 pypi
lerc 3.0 hd77b12b_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
libdeflate 1.17 h2bbff1b_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
libpng 1.6.39 h8cc25b3_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
libtiff 4.5.1 hd77b12b_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
libuv 1.44.2 h2bbff1b_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
libwebp 1.2.4 hbc33d0d_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
libwebp-base 1.2.4 h2bbff1b_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
lz4-c 1.9.4 h2bbff1b_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
maskrcnn-benchmark 0.1 dev_0 <develop>
matplotlib 3.5.3 pypi_0 pypi
matplotlib-inline 0.1.6 py37haa95532_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
mkl 2021.4.0 haa95532_640 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
mkl-service 2.4.0 py37h2bbff1b_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
mkl_fft 1.3.1 py37h277e83a_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
mkl_random 1.2.2 py37hf11a4ad_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
ninja 1.11.1.1 pypi_0 pypi
ninja-base 1.10.2 h6d14046_5 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
numpy 1.21.5 py37h7a0a035_3 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
numpy-base 1.21.5 py37hca35cd5_3 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
opencv-python 3.4.10.35 pypi_0 pypi
parso 0.8.3 pyhd3eb1b0_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
pickleshare 0.7.5 pyhd3eb1b0_1003 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
pillow 9.4.0 py37hd77b12b_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
pip 22.3.1 py37haa95532_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
prompt-toolkit 3.0.36 py37haa95532_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
pycocotools 2.0 pypi_0 pypi
pygments 2.11.2 pyhd3eb1b0_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
pyparsing 3.1.2 pypi_0 pypi
pyquaternion 0.9.9 pypi_0 pypi
python 3.7.0 hea74fb7_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
python-dateutil 2.9.0.post0 pypi_0 pypi
pytorch 1.7.0 py3.7_cuda110_cudnn8_0 pytorch
pyyaml 6.0.1 pypi_0 pypi
setuptools 59.6.0 pypi_0 pypi
six 1.16.0 pyhd3eb1b0_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
tk 8.6.14 h0416ee5_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
torchaudio 0.7.0 py37 pytorch
torchvision 0.8.0 py37_cu110 pytorch
traitlets 5.7.1 py37haa95532_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
typing 3.10.0.0 pypi_0 pypi
typing_extensions 4.4.0 py37haa95532_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
vc 14.2 h2eaa2aa_4 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
vs2015_runtime 14.29.30133 h43f2093_4 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
wcwidth 0.2.5 pyhd3eb1b0_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
wheel 0.38.4 py37haa95532_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
wincertstore 0.2 py37haa95532_2 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
xz 5.4.6 h8cc25b3_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
yacs 0.1.8 pypi_0 pypi
zlib 1.2.13 h8cc25b3_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
zstd 1.5.5 hd43e919_2 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
二.maskrcnn小demo运行
我用的pycharm,直接打开项目maskrcnn_benchmark,环境要设置成刚配置的虚拟环境
Readme里面有一个实时摄像头的小demo可以运行试试
Webcam and Jupyter notebook demo
We provide a simple webcam demo that illustrates how you can use
maskrcnn_benchmarkfor inference:cd demo
点小绿箭头然后等待下载一个包就可以运行了
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