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ubuntu20.04 conda环境配置Mask2former记录

news 2025/7/8 13:08:13

建议先看完再按照步骤安装

代码地址：GitHub - facebookresearch/Mask2Former: Code release for "Masked-attention Mask Transformer for Universal Image Segmentation"

一、配置环境

1、创建虚拟环境

conda create -n mask2former python=3.8conda activate mask2former

2、安装pytorch

在pytorch官网，找到对应版本pytorch

# CUDA 11.3
conda install pytorch==1.9.1 torchvision==0.10.1 torchaudio==0.9.1 cudatoolkit=11.3 -c pytorch -c conda-forge

通过这个命令安装的pytorch在后续使用时出现了问题（后面会讲到），于是后来我换了安装命令，解决了问题，建议直接用下面的命令安装：

# CUDA 11.3 pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cu113

3、安装opencv-python

pip install -U opencv-python

4、安装detectorn2

如果这些语句下载不下来就直接去网址下载

# under your working directory 
git clone git@github.com:facebookresearch/detectron2.git 
cd detectron2 pip install -e . 
pip install git+https://github.com/cocodataset/panopticapi.git 
pip install git+https://github.com/mcordts/cityscapesScripts.git

5、安装mask2former

cd .. 
git clone git@github.com:facebookresearch/Mask2Former.git 
cd Mask2Former 
pip install -r requirements.txt 
cd mask2former/modeling/pixel_decoder/ops 
sh make.sh

二、准备数据集

ADE20K数据集

数据集文件夹内容如下

ADEChallengeData2016/ images/ annotations/ objectInfo150.txt # 1、下载 instance annotation annotations_instance/ # 2、下面内容由 prepare_ade20k_sem_seg.py 生成 annotations_detectron2/ # 3、下面内容由 prepare_ade20k_pan_seg.py 生成 ade20k_panoptic_{train,val}.json ade20k_panoptic_{train,val}/ # 4、下面内容由 prepare_ade20k_ins_seg.py 生成 ade20k_instance_{train,val}.json

根据以上步骤依次生成数据集所需文件，另外由于我把数据集放在了项目文件夹外，所以在各种py文件中需要修改路径

下载 instance annotation 可以从 MIT Scene Parsing Benchmark，也可以用命令下载

wget http://sceneparsing.csail.mit.edu/data/ChallengeData2017/annotations_instance.tar

然后，运行将语义和实例注释组合为全景注释。

python-datasets/prepare_ade20k_pan_seg.py

并运行提取实例annota

python datasets/prepare_ade20k_ins_seg.py

三、训练

多gpu训练：

python train_net.py --num-gpus 2 --config-file configs/ade20k/panoptic-segmentation/maskformer2_R50_bs16_160k.yaml

以ADE20K数据集为例：

数据集路径在/home/dell/liyan/Mask2Former-main/mask2former/data/datasets/相对应的文件中，最后两行可以设置数据集路径

后续将更新训练的细节和遇到的问题

四、安装遇到问题

1、执行 sh make.sh 后出现问题：

No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda-11.3' Traceback (most recent call last): File "setup.py", line 76, in <module> ext_modules=get_extensions(), File "setup.py", line 54, in get_extensions raise NotImplementedError('No CUDA runtime is found. Please set FORCE_CUDA=1 or test it by running torch.cuda.is_available().')

在 .bashrc 文件中添加

export FORCE_CUDA="1"

然后运行 sh make.sh 后出现

No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda-11.3' running build running build_py running build_ext building 'MultiScaleDeformableAttention' extension Traceback (most recent call last): File "setup.py", line 69, in <module> setup( File "/home/abc/anaconda3/envs/mask2former/lib/python3.8/site-packages/setuptools/__init__.py", line 103, in setup return distutils.core.setup(**attrs) File "/home/abc/anaconda3/envs/mask2former/lib/python3.8/site-packages/setuptools/_distutils/core.py", line 185, in setup return run_commands(dist) File "/home/abc/anaconda3/envs/mask2former/lib/python3.8/site-packages/setuptools/_distutils/core.py", line 201, in run_commands dist.run_commands() File "/home/abc/anaconda3/envs/mask2former/lib/python3.8/site-packages/setuptools/_distutils/dist.py", line 969, in run_commands self.run_command(cmd) File "/home/abc/anaconda3/envs/mask2former/lib/python3.8/site-packages/setuptools/dist.py", line 989, in run_command super().run_command(command) File "/home/abc/anaconda3/envs/mask2former/lib/python3.8/site-packages/setuptools/_distutils/dist.py", line 988, in run_command cmd_obj.run() File "/home/abc/anaconda3/envs/mask2former/lib/python3.8/site-packages/setuptools/_distutils/command/build.py", line 131, in run self.run_command(cmd_name) File "/home/abc/anaconda3/envs/mask2former/lib/python3.8/site-packages/setuptools/_distutils/cmd.py", line 318, in run_command self.distribution.run_command(command) File "/home/abc/anaconda3/envs/mask2former/lib/python3.8/site-packages/setuptools/dist.py", line 989, in run_command super().run_command(command) File "/home/abc/anaconda3/envs/mask2former/lib/python3.8/site-packages/setuptools/_distutils/dist.py", line 988, in run_command cmd_obj.run() File "/home/abc/anaconda3/envs/mask2former/lib/python3.8/site-packages/setuptools/command/build_ext.py", line 88, in run _build_ext.run(self) File "/home/abc/anaconda3/envs/mask2former/lib/python3.8/site-packages/setuptools/_distutils/command/build_ext.py", line 345, in run self.build_extensions() File "/home/abc/anaconda3/envs/mask2former/lib/python3.8/site-packages/torch/utils/cpp_extension.py", line 709, in build_extensions build_ext.build_extensions(self) File "/home/abc/anaconda3/envs/mask2former/lib/python3.8/site-packages/setuptools/_distutils/command/build_ext.py", line 467, in build_extensions self._build_extensions_serial() File "/home/abc/anaconda3/envs/mask2former/lib/python3.8/site-packages/setuptools/_distutils/command/build_ext.py", line 493, in _build_extensions_serial self.build_extension(ext) File "/home/abc/anaconda3/envs/mask2former/lib/python3.8/site-packages/setuptools/command/build_ext.py", line 249, in build_extension _build_ext.build_extension(self, ext) File "/home/abc/anaconda3/envs/mask2former/lib/python3.8/site-packages/Cython/Distutils/build_ext.py", line 135, in build_extension super(build_ext, self).build_extension(ext) File "/home/abc/anaconda3/envs/mask2former/lib/python3.8/site-packages/setuptools/_distutils/command/build_ext.py", line 548, in build_extension objects = self.compiler.compile( File "/home/abc/anaconda3/envs/mask2former/lib/python3.8/site-packages/torch/utils/cpp_extension.py", line 525, in unix_wrap_ninja_compile cuda_post_cflags = unix_cuda_flags(cuda_post_cflags) File "/home/abc/anaconda3/envs/mask2former/lib/python3.8/site-packages/torch/utils/cpp_extension.py", line 424, in unix_cuda_flags cflags + _get_cuda_arch_flags(cflags)) File "/home/abc/anaconda3/envs/mask2former/lib/python3.8/site-packages/torch/utils/cpp_extension.py", line 1562, in _get_cuda_arch_flags arch_list[-1] += '+PTX' IndexError: list index out of range

检查CUDA是否可用：你可以在终端中运行以下Python命令来测试CUDA在你的系统上是否可用：

import torch print(torch.cuda.is_available())

这将使用PyTorch来检查CUDA是否可用。如果返回

True，表示CUDA已在你的Python环境中安装并可用。如果返回

False，则CUDA可能未正确安装。

换了一个安装渠道：

# CUDA 11.3 pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cu113

安装成功了，那啥也显示的ture

2、运行时发现PIL库有问题

conda install pillow

解决了

3、训练时报错

AttributeError: module 'numpy' has no attribute 'typeDict'

解决：降低numpy版本到1.21后出现问题

ValueError: numpy.ndarray size changed, may indicate binary incompatibility. Expected 96 from C header, got 88 from PyObject

解决：numpy版本升高到1.22后出现错误：

ImportError: numpy.core.multiarray failed to import

conda install numpy==1.23

4、上一个问题解决后

ImportError: /home/abc/liyan/detectron2-main/detectron2/_C.cpython-38-x86_64-linux-gnu.so: undefined symbol: _ZNK2at6Tensor7reshapeEN3c108ArrayRefIlEE

解决：在detactron2-main文件夹下打开终端，进入虚拟环境，删除build文件，重新安装

rm -r build pip install -e .

5、训练时报错

FileNotFoundError: [Errno 2] No such file or directory: 'datasets/ADEChallengeData2016/ade20k_instance_train.json'

原因是数据集路径不对，修改 Mask2Former-main/mask2former/data/datasets 路径下的py文件中的路径，改成绝对路径问题解决

6、上一个问题解决后出现新问题

File "/home/abc/anaconda3/envs/mask2former/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 240, in __init__ assert prefetch_factor > 0 TypeError: '>' not supported between instances of 'NoneType' and 'int'

原因：None 和 int 不能做大小比较，通过print出prefetch_factor的值发现是None，有人说是detectron2安装和torch版本之间的错误，在detectron2的github上有人提问这个问题，他们的解决方法是安装 pytorch 2.1.0 ，但是由于我的cuda版本太低，装不了这么高版本的pytorch，然后我在detectron2-main文件夹中寻找prefetch_factor，发现/detectron2-main/detectron2/data文件夹下的build.py文件中将prefetch_factor设置成了None，于是我把prefetch_factor的值改为2，再次进行训练，这个问题消失，但是消失不代表解决，至于真的解决没有，之后有待考证。

7、上个问题解决后，出现新问题：

dim_t = self.temperature ** (2 * (dim_t // 2) / self.num_pos_feats) Could not load library libcudnn_cnn_train.so.8. Error: /home/abc/anaconda3/envs/mask2former/bin/../lib/libcudnn_ops_train.so.8: undefined symbol: _Z20traceback_iretf_implPKcRKN5cudnn16InternalStatus_tEb, version libcudnn_ops_infer.so.8 Please make sure libcudnn_cnn_train.so.8 is in your library path! 已放弃 (核心已转储)

重新建立软连接

在文件中搜索libcudnn_cnn_train.so.8结果发现在两个路径中存在，一个是anaconda虚拟环境中，一个是/usr/，然后发现，在anaconda中链接的是8.9.1，在usr中链接的是8.2.0，本机中cudnn的版本是8.2.0，所以我觉得，在anaconda环境嗯中的链接应该是链接到8.2.0版本，这两个链接修改之后不报错了，不报错不代表没有错，后续出现问题在解决。

8、

ERROR [11/03 14:48:57 d2.engine.train_loop]: Exception during training: Traceback (most recent call last): File "/home/abc/.local/lib/python3.8/site-packages/tensorboard/compat/__init__.py", line 47, in tf from tensorboard.compat import notf # pylint: disable=g-import-not-at-top ImportError: cannot import name 'notf' from 'tensorboard.compat' (/home/abc/.local/lib/python3.8/site-packages/tensorboard/compat/__init__.py)

这个错误后面还有一个别的错误，应该是缺了一个什么库，安装好了之后，这个错也消失了，所以具体解决方法不详

9、

File "/home/abc/.local/lib/python3.8/site-packages/scipy/optimize/_hungarian.py", line 93, in linear_sum_assignment raise ValueError("matrix contains invalid numeric entries") ValueError: matrix contains invalid numeric entries

待更新