文章目录

  • 一、下载Mask_RCNN的源码：
  • 二、创建环境
    • 2.1 Anaconda创建一个虚拟环境
    • 2. 安装必要依赖包
      • 2.1.1 安装tensorflow
      • 2.1.2 安装pillow
      • 2.1.3 安装keras
      • 2.1.4 安装scikit-image
      • 2.1.5 安装opencv-python
      • 2.1.6 安装imgaug
      • 2.1.7 安装ipython
      • 2.1.8 安装pycocotools
      • 2.1.9 安装nb_conda
  • 三、下载数据集
    • 3.1 下载数据集和权重文件
    • 3.2 构建数据集
  • 四、网络训练
  • 五、问题解决
    • 5.1 Keras requires TensorFlow 2.2 or higher.
    • 5.2 AttributeError: 'str' object has no attribute 'decode'
    • 5.3 ModuleNotFoundError: No module named 'mrcnn'
    • 5.4 在TensorFlow中屏蔽warning的方式

一、下载Mask_RCNN的源码：

源码下载地址：Mask_RCNN

二、创建环境

2.1 Anaconda创建一个虚拟环境

bit@bit-613:~$ source activate
(base) bit@bit-613:~$
(base) bit@bit-613:~$
(base) bit@bit-613:~$ conda create -n MaskRCNN python=3.6
Solving environment: done==> WARNING: A newer version of conda exists. <==current version: 4.5.4latest version: 4.10.3Please update conda by running$ conda update -n base conda## Package Plan ##environment location: /home/bit/anaconda3/envs/MaskRCNNadded / updated specs: - python=3.6The following packages will be downloaded:package                    |            build---------------------------|-----------------python_abi-3.6             |          2_cp36m           4 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgecertifi-2021.5.30          |   py36h5fab9bb_0         141 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge------------------------------------------------------------Total:         145 KBThe following NEW packages will be INSTALLED:_libgcc_mutex:    0.1-conda_forge           https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge_openmp_mutex:    4.5-1_gnu                 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeca-certificates:  2021.5.30-ha878542_0      https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgecertifi:          2021.5.30-py36h5fab9bb_0  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeld_impl_linux-64: 2.36.1-hea4e1c9_1         https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgelibffi:           3.3-h58526e2_2            https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgelibgcc-ng:        9.3.0-h2828fa1_19         https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgelibgomp:          9.3.0-h2828fa1_19         https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgelibstdcxx-ng:     9.3.0-h6de172a_19         https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgencurses:          6.2-h58526e2_4            https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeopenssl:          1.1.1k-h7f98852_0         https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgepip:              21.1.3-pyhd8ed1ab_0       https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgepython:           3.6.13-hffdb5ce_0_cpython https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgepython_abi:       3.6-2_cp36m               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgereadline:         8.1-h46c0cb4_0            https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgesetuptools:       49.6.0-py36h5fab9bb_3     https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgesqlite:           3.36.0-h9cd32fc_0         https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgetk:               8.6.10-h21135ba_1         https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgewheel:            0.36.2-pyhd3deb0d_0       https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgexz:               5.2.5-h516909a_1          https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgezlib:             1.2.11-h516909a_1010      https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeProceed ([y]/n)? yDownloading and Extracting Packages
python_abi-3.6       |    4 KB | ####################################### | 100%
certifi-2021.5.30    |  141 KB | ####################################### | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
#
# To activate this environment, use
#
#     $ conda activate MaskRCNN
#
# To deactivate an active environment, use
#
#     $ conda deactivate(base) bit@bit-613:~$ conda activate MaskRCNN
(MaskRCNN) bit@bit-613:~$
(MaskRCNN) bit@bit-613:~$

进入项目的：

(MaskRCNN) bit@bit-613:~$ cd MaskRCNN/
(MaskRCNN) bit@bit-613:~/MaskRCNN$ ls
Mask_RCNN-master  Mask_RCNN-master.zip
(MaskRCNN) bit@bit-613:~/MaskRCNN$ cd Mask_RCNN-master/
(MaskRCNN) bit@bit-613:~/MaskRCNN/Mask_RCNN-master$ ls
assets  LICENSE      mrcnn      requirements.txt  setup.cfg
images  MANIFEST.in  README.md  samples           setup.py
(MaskRCNN) bit@bit-613:~/MaskRCNN/Mask_RCNN-master$

2. 安装必要依赖包

采用手动安装requirements中各个包：

首先配置最重要的keras和tensorflow，注意版本号.

查询Cuda版本

(MaskRCNN) bit@bit-613:~/MaskRCNN/Mask_RCNN-master$ nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2018 NVIDIA Corporation
Built on Sat_Aug_25_21:08:01_CDT_2018
Cuda compilation tools, release 10.0, V10.0.130

根据电脑中CUDA版本确定TensorFlow的版本号。

2.1.1 安装tensorflow

(MaskRCNN) bit@bit-613:~/MaskRCNN/Mask_RCNN-master$ pip install tensorflow-gpu==1.13.0
ERROR: Could not find a version that satisfies the requirement tensorflow-gpu==1.13.0 (from versions: 0.12.1, 1.0.0, 1.0.1, 1.1.0, 1.2.0, 1.2.1, 1.3.0, 1.4.0, 1.4.1, 1.5.0, 1.5.1, 1.6.0, 1.7.0, 1.7.1, 1.8.0, 1.9.0, 1.10.0, 1.10.1, 1.11.0, 1.12.0, 1.12.2, 1.12.3, 1.13.1, 1.13.2, 1.14.0, 1.15.0rc0, 1.15.0rc1, 1.15.0rc2, 1.15.0rc3, 1.15.0, 1.15.2, 1.15.3, 1.15.4, 1.15.5, 2.0.0a0, 2.0.0b0, 2.0.0b1, 2.0.0rc0, 2.0.0rc1, 2.0.0rc2, 2.0.0, 2.0.1, 2.0.2, 2.0.3, 2.0.4, 2.1.0rc0, 2.1.0rc1, 2.1.0rc2, 2.1.0, 2.1.1, 2.1.2, 2.1.3, 2.1.4, 2.2.0rc0, 2.2.0rc1, 2.2.0rc2, 2.2.0rc3, 2.2.0rc4, 2.2.0, 2.2.1, 2.2.2, 2.2.3, 2.3.0rc0, 2.3.0rc1, 2.3.0rc2, 2.3.0, 2.3.1, 2.3.2, 2.3.3, 2.4.0rc0, 2.4.0rc1, 2.4.0rc2, 2.4.0rc3, 2.4.0rc4, 2.4.0, 2.4.1, 2.4.2, 2.5.0rc0, 2.5.0rc1, 2.5.0rc2, 2.5.0rc3, 2.5.0, 2.6.0rc0, 2.6.0rc1)
ERROR: No matching distribution found for tensorflow-gpu==1.13.0
(MaskRCNN) bit@bit-613:~/MaskRCNN/Mask_RCNN-master$ pip install tensorflow-gpu==1.13.1
Collecting tensorflow-gpu==1.13.1Using cached tensorflow_gpu-1.13.1-cp36-cp36m-manylinux1_x86_64.whl (345.2 MB)
Requirement already satisfied: termcolor>=1.1.0 in /home/bit/.local/lib/python3.6/site-packages (from tensorflow-gpu==1.13.1) (1.1.0)
Collecting tensorboard<1.14.0,>=1.13.0Using cached tensorboard-1.13.1-py3-none-any.whl (3.2 MB)
Requirement already satisfied: absl-py>=0.1.6 in /home/bit/.local/lib/python3.6/site-packages (from tensorflow-gpu==1.13.1) (0.12.0)
Collecting keras-applications>=1.0.6Using cached Keras_Applications-1.0.8-py3-none-any.whl (50 kB)
Collecting grpcio>=1.8.6Downloading grpcio-1.38.1-cp36-cp36m-manylinux2014_x86_64.whl (4.2 MB)|████████████████████████████████| 4.2 MB 839 kB/s
Collecting tensorflow-estimator<1.14.0rc0,>=1.13.0Using cached tensorflow_estimator-1.13.0-py2.py3-none-any.whl (367 kB)
Collecting gast>=0.2.0Downloading gast-0.5.0-py3-none-any.whl (10 kB)
Collecting six>=1.10.0Using cached six-1.16.0-py2.py3-none-any.whl (11 kB)
Collecting astor>=0.6.0Using cached astor-0.8.1-py2.py3-none-any.whl (27 kB)
Requirement already satisfied: wheel>=0.26 in /home/bit/anaconda3/envs/MaskRCNN/lib/python3.6/site-packages (from tensorflow-gpu==1.13.1) (0.36.2)
Collecting numpy>=1.13.3Using cached numpy-1.19.5-cp36-cp36m-manylinux2010_x86_64.whl (14.8 MB)
Collecting keras-preprocessing>=1.0.5Using cached Keras_Preprocessing-1.1.2-py2.py3-none-any.whl (42 kB)
Requirement already satisfied: protobuf>=3.6.1 in /home/bit/.local/lib/python3.6/site-packages (from tensorflow-gpu==1.13.1) (3.15.6)
Collecting h5pyUsing cached h5py-3.1.0-cp36-cp36m-manylinux1_x86_64.whl (4.0 MB)
Requirement already satisfied: markdown>=2.6.8 in /home/bit/.local/lib/python3.6/site-packages (from tensorboard<1.14.0,>=1.13.0->tensorflow-gpu==1.13.1) (3.3.4)
Requirement already satisfied: werkzeug>=0.11.15 in /home/bit/.local/lib/python3.6/site-packages (from tensorboard<1.14.0,>=1.13.0->tensorflow-gpu==1.13.1) (1.0.1)
Requirement already satisfied: importlib-metadata in /home/bit/.local/lib/python3.6/site-packages (from markdown>=2.6.8->tensorboard<1.14.0,>=1.13.0->tensorflow-gpu==1.13.1) (3.7.3)
Collecting mock>=2.0.0Using cached mock-4.0.3-py3-none-any.whl (28 kB)
Collecting cached-propertyUsing cached cached_property-1.5.2-py2.py3-none-any.whl (7.6 kB)
Requirement already satisfied: typing-extensions>=3.6.4 in /home/bit/.local/lib/python3.6/site-packages (from importlib-metadata->markdown>=2.6.8->tensorboard<1.14.0,>=1.13.0->tensorflow-gpu==1.13.1) (3.7.4.3)
Requirement already satisfied: zipp>=0.5 in /home/bit/.local/lib/python3.6/site-packages (from importlib-metadata->markdown>=2.6.8->tensorboard<1.14.0,>=1.13.0->tensorflow-gpu==1.13.1) (3.4.1)
Installing collected packages: six, numpy, cached-property, mock, h5py, grpcio, tensorflow-estimator, tensorboard, keras-preprocessing, keras-applications, gast, astor, tensorflow-gpu
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
matplotlib 3.3.4 requires pillow>=6.2.0, which is not installed.
cvpods 0.1 requires Pillow>=7.1, which is not installed.
cvpods 0.1 requires torch, which is not installed.
cvpods 0.1 requires torchvision, which is not installed.
Successfully installed astor-0.8.1 cached-property-1.5.2 gast-0.5.0 grpcio-1.38.1 h5py-3.1.0 keras-applications-1.0.8 keras-preprocessing-1.1.2 mock-4.0.3 numpy-1.19.5 six-1.16.0 tensorboard-1.13.1 tensorflow-estimator-1.13.0 tensorflow-gpu-1.13.1
(MaskRCNN) bit@bit-613:~/MaskRCNN/Mask_RCNN-master$ pip list
Package                Version             Location
---------------------- ------------------- ----------------
absl-py                0.12.0
appdirs                1.4.4
astor                  0.8.1
cached-property        1.5.2
cachetools             4.2.1
certifi                2021.5.30
chardet                4.0.0
cloudpickle            1.6.0
colorama               0.4.4
cvpods                 0.1                 /home/bit/cvpods
cycler                 0.10.0
Cython                 0.29.22
easydict               1.9
future                 0.18.2
gast                   0.5.0
google-auth            1.28.0
google-auth-oauthlib   0.4.3
grpcio                 1.38.1
h5py                   3.1.0
idna                   2.10
importlib-metadata     3.7.3
Keras-Applications     1.0.8
Keras-Preprocessing    1.1.2
kiwisolver             1.3.1
Markdown               3.3.4
matplotlib             3.3.4
mock                   4.0.3
numpy                  1.19.5
oauthlib               3.1.0
pandas                 1.1.5
pip                    21.1.3
portalocker            2.2.1
protobuf               3.15.6
pyasn1                 0.4.8
pyasn1-modules         0.2.8
pycocotools            2.0.2
pydot                  1.4.2
pyparsing              2.4.7
python-dateutil        2.8.1
pytz                   2021.1
requests               2.25.1
requests-oauthlib      1.3.0
rsa                    4.7.2
scipy                  1.5.4
seaborn                0.11.1
setuptools             49.6.0.post20210108
six                    1.16.0
tabulate               0.8.9
tensorboard            1.13.1
tensorboard-plugin-wit 1.8.0
tensorflow-estimator   1.13.0
tensorflow-gpu         1.13.1
termcolor              1.1.0
tqdm                   4.59.0
typing-extensions      3.7.4.3
urllib3                1.26.4
Werkzeug               1.0.1
wheel                  0.36.2
zipp                   3.4.1

2.1.2 安装pillow

(MaskRCNN) bit@bit-613:~/MaskRCNN/Mask_RCNN-master$ pip install pillow
Collecting pillowDownloading Pillow-8.3.1-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.whl (3.0 MB)|████████████████████████████████| 3.0 MB 837 kB/s
Installing collected packages: pillow
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
cvpods 0.1 requires torch, which is not installed.
cvpods 0.1 requires torchvision, which is not installed.
Successfully installed pillow-8.3.1

2.1.3 安装keras

(MaskRCNN) bit@bit-613:~/MaskRCNN/Mask_RCNN-master$ pip  install keras
Collecting kerasDownloading Keras-2.4.3-py2.py3-none-any.whl (36 kB)
Requirement already satisfied: numpy>=1.9.1 in /home/bit/anaconda3/envs/MaskRCNN/lib/python3.6/site-packages (from keras) (1.19.5)
Requirement already satisfied: scipy>=0.14 in /home/bit/.local/lib/python3.6/site-packages (from keras) (1.5.4)
Requirement already satisfied: h5py in /home/bit/anaconda3/envs/MaskRCNN/lib/python3.6/site-packages (from keras) (3.1.0)
Collecting pyyamlDownloading PyYAML-5.4.1-cp36-cp36m-manylinux1_x86_64.whl (640 kB)|████████████████████████████████| 640 kB 956 kB/s
Requirement already satisfied: cached-property in /home/bit/anaconda3/envs/MaskRCNN/lib/python3.6/site-packages (from h5py->keras) (1.5.2)
Installing collected packages: pyyaml, keras
Successfully installed keras-2.4.3 pyyaml-5.4.1

2.1.4 安装scikit-image

(MaskRCNN) bit@bit-613:~/MaskRCNN/Mask_RCNN-master$ pip install scikit-image
Collecting scikit-imageUsing cached scikit_image-0.17.2-cp36-cp36m-manylinux1_x86_64.whl (12.4 MB)
Requirement already satisfied: numpy>=1.15.1 in /home/bit/anaconda3/envs/MaskRCNN/lib/python3.6/site-packages (from scikit-image) (1.19.5)
Requirement already satisfied: matplotlib!=3.0.0,>=2.0.0 in /home/bit/.local/lib/python3.6/site-packages (from scikit-image) (3.3.4)
Collecting PyWavelets>=1.1.1Using cached PyWavelets-1.1.1-cp36-cp36m-manylinux1_x86_64.whl (4.4 MB)
Collecting networkx>=2.0Using cached networkx-2.5.1-py3-none-any.whl (1.6 MB)
Requirement already satisfied: scipy>=1.0.1 in /home/bit/.local/lib/python3.6/site-packages (from scikit-image) (1.5.4)
Collecting tifffile>=2019.7.26Using cached tifffile-2020.9.3-py3-none-any.whl (148 kB)
Collecting imageio>=2.3.0Using cached imageio-2.9.0-py3-none-any.whl (3.3 MB)
Requirement already satisfied: pillow!=7.1.0,!=7.1.1,>=4.3.0 in /home/bit/anaconda3/envs/MaskRCNN/lib/python3.6/site-packages (from scikit-image) (8.3.1)
Requirement already satisfied: python-dateutil>=2.1 in /home/bit/.local/lib/python3.6/site-packages (from matplotlib!=3.0.0,>=2.0.0->scikit-image) (2.8.1)
Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in /home/bit/.local/lib/python3.6/site-packages (from matplotlib!=3.0.0,>=2.0.0->scikit-image) (2.4.7)
Requirement already satisfied: cycler>=0.10 in /home/bit/.local/lib/python3.6/site-packages (from matplotlib!=3.0.0,>=2.0.0->scikit-image) (0.10.0)
Requirement already satisfied: kiwisolver>=1.0.1 in /home/bit/.local/lib/python3.6/site-packages (from matplotlib!=3.0.0,>=2.0.0->scikit-image) (1.3.1)
Requirement already satisfied: six in /home/bit/anaconda3/envs/MaskRCNN/lib/python3.6/site-packages (from cycler>=0.10->matplotlib!=3.0.0,>=2.0.0->scikit-image) (1.16.0)
Collecting decorator<5,>=4.3Using cached decorator-4.4.2-py2.py3-none-any.whl (9.2 kB)
Installing collected packages: decorator, tifffile, PyWavelets, networkx, imageio, scikit-image
Successfully installed PyWavelets-1.1.1 decorator-4.4.2 imageio-2.9.0 networkx-2.5.1 scikit-image-0.17.2 tifffile-2020.9.3

2.1.5 安装opencv-python

(MaskRCNN) bit@bit-613:~/MaskRCNN/Mask_RCNN-master$ pip install opencv-python
Collecting opencv-pythonDownloading opencv_python-4.5.3.56-cp36-cp36m-manylinux2014_x86_64.whl (49.9 MB)|████████████████████████████████| 49.9 MB 59 kB/s
Requirement already satisfied: numpy>=1.13.3 in /home/bit/anaconda3/envs/MaskRCNN/lib/python3.6/site-packages (from opencv-python) (1.19.5)
Installing collected packages: opencv-python
Successfully installed opencv-python-4.5.3.56

2.1.6 安装imgaug

(MaskRCNN) bit@bit-613:~/MaskRCNN/Mask_RCNN-master$ pip install imgaug
Collecting imgaugDownloading imgaug-0.4.0-py2.py3-none-any.whl (948 kB)|████████████████████████████████| 948 kB 576 kB/s
Requirement already satisfied: imageio in /home/bit/anaconda3/envs/MaskRCNN/lib/python3.6/site-packages (from imgaug) (2.9.0)
Requirement already satisfied: numpy>=1.15 in /home/bit/anaconda3/envs/MaskRCNN/lib/python3.6/site-packages (from imgaug) (1.19.5)
Requirement already satisfied: matplotlib in /home/bit/.local/lib/python3.6/site-packages (from imgaug) (3.3.4)
Requirement already satisfied: Pillow in /home/bit/anaconda3/envs/MaskRCNN/lib/python3.6/site-packages (from imgaug) (8.3.1)
Requirement already satisfied: six in /home/bit/anaconda3/envs/MaskRCNN/lib/python3.6/site-packages (from imgaug) (1.16.0)
Requirement already satisfied: scipy in /home/bit/.local/lib/python3.6/site-packages (from imgaug) (1.5.4)
Collecting ShapelyDownloading Shapely-1.7.1-cp36-cp36m-manylinux1_x86_64.whl (1.0 MB)|████████████████████████████████| 1.0 MB 29.7 MB/s
Requirement already satisfied: opencv-python in /home/bit/anaconda3/envs/MaskRCNN/lib/python3.6/site-packages (from imgaug) (4.5.3.56)
Requirement already satisfied: scikit-image>=0.14.2 in /home/bit/anaconda3/envs/MaskRCNN/lib/python3.6/site-packages (from imgaug) (0.17.2)
Requirement already satisfied: tifffile>=2019.7.26 in /home/bit/anaconda3/envs/MaskRCNN/lib/python3.6/site-packages (from scikit-image>=0.14.2->imgaug) (2020.9.3)
Requirement already satisfied: networkx>=2.0 in /home/bit/anaconda3/envs/MaskRCNN/lib/python3.6/site-packages (from scikit-image>=0.14.2->imgaug) (2.5.1)
Requirement already satisfied: PyWavelets>=1.1.1 in /home/bit/anaconda3/envs/MaskRCNN/lib/python3.6/site-packages (from scikit-image>=0.14.2->imgaug) (1.1.1)
Requirement already satisfied: cycler>=0.10 in /home/bit/.local/lib/python3.6/site-packages (from matplotlib->imgaug) (0.10.0)
Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in /home/bit/.local/lib/python3.6/site-packages (from matplotlib->imgaug) (2.4.7)
Requirement already satisfied: kiwisolver>=1.0.1 in /home/bit/.local/lib/python3.6/site-packages (from matplotlib->imgaug) (1.3.1)
Requirement already satisfied: python-dateutil>=2.1 in /home/bit/.local/lib/python3.6/site-packages (from matplotlib->imgaug) (2.8.1)
Requirement already satisfied: decorator<5,>=4.3 in /home/bit/anaconda3/envs/MaskRCNN/lib/python3.6/site-packages (from networkx>=2.0->scikit-image>=0.14.2->imgaug) (4.4.2)
Installing collected packages: Shapely, imgaug
Successfully installed Shapely-1.7.1 imgaug-0.4.0

2.1.7 安装ipython

(MaskRCNN) bit@bit-613:~/MaskRCNN/Mask_RCNN-master$ conda install ipython
Solving environment: done==> WARNING: A newer version of conda exists. <==current version: 4.5.4latest version: 4.10.3Please update conda by running$ conda update -n base conda## Package Plan ##environment location: /home/bit/anaconda3/envs/MaskRCNNadded / updated specs: - ipythonThe following packages will be downloaded:package                    |            build---------------------------|-----------------pygments-2.9.0             |     pyhd8ed1ab_0         754 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeprompt-toolkit-3.0.19      |     pyha770c72_0         244 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgetraitlets-4.3.3            |   py36h9f0ad1d_1         133 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgebackports.functools_lru_cache-1.6.4|     pyhd8ed1ab_0           9 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgedecorator-5.0.9            |     pyhd8ed1ab_0          11 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeipython_genutils-0.2.0     |             py_1          21 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeptyprocess-0.7.0           |     pyhd3deb0d_0          16 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgepickleshare-0.7.5          |          py_1003           9 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgesix-1.16.0                 |     pyh6c4a22f_0          14 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgewcwidth-0.2.5              |     pyh9f0ad1d_2          33 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgebackcall-0.2.0             |     pyh9f0ad1d_0          13 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgejedi-0.17.2                |   py36h5fab9bb_1         957 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgebackports-1.0              |             py_2           4 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgepexpect-4.8.0              |     pyh9f0ad1d_2          47 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeparso-0.7.1                |     pyh9f0ad1d_0          70 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeipython-7.16.1             |   py36he448a4c_2         1.1 MB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge------------------------------------------------------------Total:         3.4 MBThe following NEW packages will be INSTALLED:backcall:                      0.2.0-pyh9f0ad1d_0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgebackports:                     1.0-py_2              https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgebackports.functools_lru_cache: 1.6.4-pyhd8ed1ab_0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgedecorator:                     5.0.9-pyhd8ed1ab_0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeipython:                       7.16.1-py36he448a4c_2 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeipython_genutils:              0.2.0-py_1            https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgejedi:                          0.17.2-py36h5fab9bb_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeparso:                         0.7.1-pyh9f0ad1d_0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgepexpect:                       4.8.0-pyh9f0ad1d_2    https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgepickleshare:                   0.7.5-py_1003         https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeprompt-toolkit:                3.0.19-pyha770c72_0   https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeptyprocess:                    0.7.0-pyhd3deb0d_0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgepygments:                      2.9.0-pyhd8ed1ab_0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgesix:                           1.16.0-pyh6c4a22f_0   https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgetraitlets:                     4.3.3-py36h9f0ad1d_1  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgewcwidth:                       0.2.5-pyh9f0ad1d_2    https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeProceed ([y]/n)? yDownloading and Extracting Packages
pygments-2.9.0       |  754 KB | ####################################### | 100%
prompt-toolkit-3.0.1 |  244 KB | ####################################### | 100%
traitlets-4.3.3      |  133 KB | ####################################### | 100%
backports.functools_ |    9 KB | ####################################### | 100%
decorator-5.0.9      |   11 KB | ####################################### | 100%
ipython_genutils-0.2 |   21 KB | ####################################### | 100%
ptyprocess-0.7.0     |   16 KB | ####################################### | 100%
pickleshare-0.7.5    |    9 KB | ####################################### | 100%
six-1.16.0           |   14 KB | ####################################### | 100%
wcwidth-0.2.5        |   33 KB | ####################################### | 100%
backcall-0.2.0       |   13 KB | ####################################### | 100%
jedi-0.17.2          |  957 KB | ####################################### | 100%
backports-1.0        |    4 KB | ####################################### | 100%
pexpect-4.8.0        |   47 KB | ####################################### | 100%
parso-0.7.1          |   70 KB | ####################################### | 100%
ipython-7.16.1       |  1.1 MB | ####################################### | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
(MaskRCNN) bit@bit-613:~/MaskRCNN/Mask_RCNN-master$
(MaskRCNN) bit@bit-613:~/MaskRCNN/Mask_RCNN-master$ pip list
Package                       Version             Location
----------------------------- ------------------- ----------------
absl-py                       0.12.0
appdirs                       1.4.4
astor                         0.8.1
backcall                      0.2.0
backports.functools-lru-cache 1.6.4
cached-property               1.5.2
cachetools                    4.2.1
certifi                       2021.5.30
chardet                       4.0.0
cloudpickle                   1.6.0
colorama                      0.4.4
cvpods                        0.1                 /home/bit/cvpods
cycler                        0.10.0
Cython                        0.29.22
decorator                     5.0.9
easydict                      1.9
future                        0.18.2
gast                          0.5.0
google-auth                   1.28.0
google-auth-oauthlib          0.4.3
grpcio                        1.38.1
h5py                          3.1.0
idna                          2.10
imageio                       2.9.0
imgaug                        0.4.0
importlib-metadata            3.7.3
ipython                       7.16.1
ipython-genutils              0.2.0
jedi                          0.17.2
Keras                         2.4.3
Keras-Applications            1.0.8
Keras-Preprocessing           1.1.2
kiwisolver                    1.3.1
Markdown                      3.3.4
matplotlib                    3.3.4
mock                          4.0.3
networkx                      2.5.1
numpy                         1.19.5
oauthlib                      3.1.0
opencv-python                 4.5.3.56
pandas                        1.1.5
parso                         0.7.1
pexpect                       4.8.0
pickleshare                   0.7.5
Pillow                        8.3.1
pip                           21.1.3
portalocker                   2.2.1
prompt-toolkit                3.0.19
protobuf                      3.15.6
ptyprocess                    0.7.0
pyasn1                        0.4.8
pyasn1-modules                0.2.8
pycocotools                   2.0.2
pydot                         1.4.2
Pygments                      2.9.0
pyparsing                     2.4.7
python-dateutil               2.8.1
pytz                          2021.1
PyWavelets                    1.1.1
PyYAML                        5.4.1
requests                      2.25.1
requests-oauthlib             1.3.0
rsa                           4.7.2
scikit-image                  0.17.2
scipy                         1.5.4
seaborn                       0.11.1
setuptools                    49.6.0.post20210108
Shapely                       1.7.1
six                           1.16.0
tabulate                      0.8.9
tensorboard                   1.13.1
tensorboard-plugin-wit        1.8.0
tensorflow-estimator          1.13.0
tensorflow-gpu                1.13.1
termcolor                     1.1.0
tifffile                      2020.9.3
tqdm                          4.59.0
traitlets                     4.3.3
typing-extensions             3.7.4.3
urllib3                       1.26.4
wcwidth                       0.2.5
Werkzeug                      1.0.1
wheel                         0.36.2
zipp                          3.4.1

2.1.8 安装pycocotools

pycocotools从这些存储库之一训练或测试 MS COCO 安装。它们是原始 pycocotools 的分支，修复了 Python3 和 Windows（官方存储库似乎不再活跃）。

COCO API 提供了 Matlab, Python 和 Lua 的 API 接口. 该 API 接口可以提供完整的图像标签数据的加载, parsing 和可视化。在使用coco数据集时会用到这个API，因此需要安装。

  • Linux：https : //github.com/waleedka/coco
  • Windows：https : //github.com/philferriere/cocoapi。您的路径上必须有 Visual C++ 2015 构建工具（有关其他详细信息，请参阅 repo）

下载pycocotools该项目到本地，并解压打开：

安装方式：

  • For Matlab, add coco/MatlabApi to the Matlab path (OSX/Linux binaries provided)
  • For Python, run “make” under coco/PythonAPI
  • For Lua, run “luarocks make LuaAPI/rocks/coco-scm-1.rockspec” under coco/

For Python, run “make” under coco/PythonAPI，即进入到PythonAPI，并输入make

(MaskRCNN) bit@bit-613:~/MaskRCNN/coco-master$ cd PythonAPI/
(MaskRCNN) bit@bit-613:~/MaskRCNN/coco-master/PythonAPI$ ls
Makefile  pycocoDemo.ipynb  pycocoEvalDemo.ipynb  pycocotools  setup.py
(MaskRCNN) bit@bit-613:~/MaskRCNN/coco-master/PythonAPI$ make
python setup.py build_ext --inplace
Compiling pycocotools/_mask.pyx because it changed.
[1/1] Cythonizing pycocotools/_mask.pyx
/home/bit/.local/lib/python3.6/site-packages/Cython/Compiler/Main.py:369: FutureWarning: Cython directive 'language_level' not set, using 2 for now (Py2). This will change in a later release! File: /home/bit/MaskRCNN/coco-master/PythonAPI/pycocotools/_mask.pyxtree = Parsing.p_module(s, pxd, full_module_name)
running build_ext
building 'pycocotools._mask' extension
creating build
creating build/temp.linux-x86_64-3.6
creating build/temp.linux-x86_64-3.6/pycocotools
creating build/common
gcc -pthread -B /home/bit/anaconda3/envs/MaskRCNN/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I/home/bit/anaconda3/envs/MaskRCNN/lib/python3.6/site-packages/numpy/core/include -I../common -I/home/bit/anaconda3/envs/MaskRCNN/include/python3.6m -c pycocotools/_mask.c -o build/temp.linux-x86_64-3.6/pycocotools/_mask.o -Wno-cpp -Wno-unused-function -std=c99
gcc -pthread -B /home/bit/anaconda3/envs/MaskRCNN/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I/home/bit/anaconda3/envs/MaskRCNN/lib/python3.6/site-packages/numpy/core/include -I../common -I/home/bit/anaconda3/envs/MaskRCNN/include/python3.6m -c ../common/maskApi.c -o build/temp.linux-x86_64-3.6/../common/maskApi.o -Wno-cpp -Wno-unused-function -std=c99
gcc -pthread -shared -B /home/bit/anaconda3/envs/MaskRCNN/compiler_compat -L/home/bit/anaconda3/envs/MaskRCNN/lib -Wl,-rpath=/home/bit/anaconda3/envs/MaskRCNN/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.6/pycocotools/_mask.o build/temp.linux-x86_64-3.6/../common/maskApi.o -o /home/bit/MaskRCNN/coco-master/PythonAPI/pycocotools/_mask.cpython-36m-x86_64-linux-gnu.so
rm -rf build

输入pip install pycocotools，安装成功．

(MaskRCNN) bit@bit-613:~/MaskRCNN/coco-master/PythonAPI$ pip install pycocotools
Requirement already satisfied: pycocotools in /home/bit/.local/lib/python3.6/site-packages (2.0.2)
Requirement already satisfied: cython>=0.27.3 in /home/bit/.local/lib/python3.6/site-packages (from pycocotools) (0.29.22)
Requirement already satisfied: setuptools>=18.0 in /home/bit/anaconda3/envs/MaskRCNN/lib/python3.6/site-packages (from pycocotools) (49.6.0.post20210108)
Requirement already satisfied: matplotlib>=2.1.0 in /home/bit/.local/lib/python3.6/site-packages (from pycocotools) (3.3.4)
Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in /home/bit/.local/lib/python3.6/site-packages (from matplotlib>=2.1.0->pycocotools) (2.4.7)
Requirement already satisfied: python-dateutil>=2.1 in /home/bit/.local/lib/python3.6/site-packages (from matplotlib>=2.1.0->pycocotools) (2.8.1)
Requirement already satisfied: kiwisolver>=1.0.1 in /home/bit/.local/lib/python3.6/site-packages (from matplotlib>=2.1.0->pycocotools) (1.3.1)
Requirement already satisfied: cycler>=0.10 in /home/bit/.local/lib/python3.6/site-packages (from matplotlib>=2.1.0->pycocotools) (0.10.0)
Requirement already satisfied: numpy>=1.15 in /home/bit/anaconda3/envs/MaskRCNN/lib/python3.6/site-packages (from matplotlib>=2.1.0->pycocotools) (1.19.5)
Requirement already satisfied: pillow>=6.2.0 in /home/bit/anaconda3/envs/MaskRCNN/lib/python3.6/site-packages (from matplotlib>=2.1.0->pycocotools) (8.3.1)
Requirement already satisfied: six in /home/bit/anaconda3/envs/MaskRCNN/lib/python3.6/site-packages (from cycler>=0.10->matplotlib>=2.1.0->pycocotools) (1.16.0)
(MaskRCNN) bit@bit-613:~/MaskRCNN/coco-master/PythonAPI$

查询安装的安装包，发现已经成功安装 pycocotools．

(MaskRCNN) bit@bit-613:~/MaskRCNN/coco-master/PythonAPI$ pip list
Package                       Version             Location
----------------------------- ------------------- ----------------
absl-py                       0.12.0
appdirs                       1.4.4
astor                         0.8.1
backcall                      0.2.0
backports.functools-lru-cache 1.6.4
cached-property               1.5.2
cachetools                    4.2.1
certifi                       2021.5.30
chardet                       4.0.0
cloudpickle                   1.6.0
colorama                      0.4.4
cvpods                        0.1                 /home/bit/cvpods
cycler                        0.10.0
Cython                        0.29.22
decorator                     5.0.9
easydict                      1.9
future                        0.18.2
gast                          0.5.0
google-auth                   1.28.0
google-auth-oauthlib          0.4.3
grpcio                        1.38.1
h5py                          3.1.0
idna                          2.10
imageio                       2.9.0
imgaug                        0.4.0
importlib-metadata            3.7.3
ipython                       7.16.1
ipython-genutils              0.2.0
jedi                          0.17.2
Keras                         2.4.3
Keras-Applications            1.0.8
Keras-Preprocessing           1.1.2
kiwisolver                    1.3.1
Markdown                      3.3.4
matplotlib                    3.3.4
mock                          4.0.3
networkx                      2.5.1
numpy                         1.19.5
oauthlib                      3.1.0
opencv-python                 4.5.3.56
pandas                        1.1.5
parso                         0.7.1
pexpect                       4.8.0
pickleshare                   0.7.5
Pillow                        8.3.1
pip                           21.1.3
portalocker                   2.2.1
prompt-toolkit                3.0.19
protobuf                      3.15.6
ptyprocess                    0.7.0
pyasn1                        0.4.8
pyasn1-modules                0.2.8
pycocotools                   2.0.2
pydot                         1.4.2
Pygments                      2.9.0
pyparsing                     2.4.7
python-dateutil               2.8.1
pytz                          2021.1
PyWavelets                    1.1.1
PyYAML                        5.4.1
requests                      2.25.1
requests-oauthlib             1.3.0
rsa                           4.7.2
scikit-image                  0.17.2
scipy                         1.5.4
seaborn                       0.11.1
setuptools                    49.6.0.post20210108
Shapely                       1.7.1
six                           1.16.0
tabulate                      0.8.9
tensorboard                   1.13.1
tensorboard-plugin-wit        1.8.0
tensorflow-estimator          1.13.0
tensorflow-gpu                1.13.1
termcolor                     1.1.0
tifffile                      2020.9.3
tqdm                          4.59.0
traitlets                     4.3.3
typing-extensions             3.7.4.3
urllib3                       1.26.4
wcwidth                       0.2.5
Werkzeug                      1.0.1
wheel                         0.36.2
zipp                          3.4.1

2.1.9 安装nb_conda

一般安装了anaconda会自带jupyter notebook，但是这样启动的notebook运行的是base环境，当我们创建其他虚拟环境时启动notebook是还是运行base环境。

想指定notebook的运行环境需要安装nb_conda，重新启动jupyter notebook之后，就可以在kernel中选择自己需要的虚拟环境。

(MaskRCNN) bit@bit-613:~/MaskRCNN/coco-master/PythonAPI$ conda install nb_conda
Solving environment: done==> WARNING: A newer version of conda exists. <==current version: 4.5.4latest version: 4.10.3Please update conda by running$ conda update -n base conda## Package Plan ##environment location: /home/bit/anaconda3/envs/MaskRCNNadded / updated specs: - nb_condaThe following packages will be downloaded:package                    |            build---------------------------|-----------------nb_conda-2.2.1             |   py36h5fab9bb_4          36 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeipykernel-5.5.5            |   py36hcb3619a_0         166 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgepandocfilters-1.4.2        |             py_1           9 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgenbconvert-6.0.7            |   py36h5fab9bb_3         533 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgejinja2-3.0.1               |     pyhd8ed1ab_0          99 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgepandoc-2.14.1              |       h7f98852_0        12.0 MB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgesend2trash-1.7.1           |     pyhd8ed1ab_0          17 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgetyping_extensions-3.10.0.0 |     pyha770c72_0          28 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgecffi-1.14.6                |   py36hc120d54_0         224 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeasync_generator-1.10       |             py_0          18 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgewebencodings-0.5.1         |             py_1          12 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgenbclient-0.5.3             |     pyhd8ed1ab_0          67 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgemistune-0.8.4              |py36h8f6f2f9_1004          54 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgemarkupsafe-2.0.1           |   py36h8f6f2f9_0          22 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeattrs-21.2.0               |     pyhd8ed1ab_0          44 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgetestpath-0.5.0             |     pyhd8ed1ab_0          86 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgepyzmq-22.1.0               |   py36h7068817_0         528 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeargon2-cffi-20.1.0         |   py36h8f6f2f9_2          47 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeprometheus_client-0.11.0   |     pyhd8ed1ab_0          46 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeentrypoints-0.3            |  pyhd8ed1ab_1003           8 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeimportlib-metadata-4.6.1   |   py36h5fab9bb_0          31 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgepython-dateutil-2.8.2      |     pyhd8ed1ab_0         240 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgejupyter_core-4.7.1         |   py36h5fab9bb_0          72 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgebleach-3.3.1               |     pyhd8ed1ab_0         111 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgepackaging-21.0             |     pyhd8ed1ab_0          35 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeterminado-0.10.1           |   py36h5fab9bb_0          26 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgenest-asyncio-1.5.1         |     pyhd8ed1ab_0           9 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgedefusedxml-0.7.1           |     pyhd8ed1ab_0          23 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgenbformat-5.1.3             |     pyhd8ed1ab_0          47 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgelibsodium-1.0.18           |       h36c2ea0_1         366 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgejupyterlab_pygments-0.1.2  |     pyh9f0ad1d_0           8 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgenotebook-6.3.0             |   py36h5fab9bb_0         6.3 MB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgezeromq-4.3.4               |       h9c3ff4c_0         352 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgezipp-3.5.0                 |     pyhd8ed1ab_0          12 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgepyrsistent-0.17.3          |   py36h8f6f2f9_2          89 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgetornado-6.1                |   py36h8f6f2f9_1         643 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgejsonschema-3.2.0           |     pyhd8ed1ab_3          45 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgejupyter_client-6.1.12      |     pyhd8ed1ab_0          79 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgenb_conda_kernels-2.3.1     |   py36h5fab9bb_0          27 KB  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge------------------------------------------------------------Total:        22.5 MBThe following NEW packages will be INSTALLED:argon2-cffi:         20.1.0-py36h8f6f2f9_2   https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeasync_generator:     1.10-py_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeattrs:               21.2.0-pyhd8ed1ab_0     https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgebleach:              3.3.1-pyhd8ed1ab_0      https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgecffi:                1.14.6-py36hc120d54_0   https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgedefusedxml:          0.7.1-pyhd8ed1ab_0      https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeentrypoints:         0.3-pyhd8ed1ab_1003     https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeimportlib-metadata:  4.6.1-py36h5fab9bb_0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeipykernel:           5.5.5-py36hcb3619a_0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgejinja2:              3.0.1-pyhd8ed1ab_0      https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgejsonschema:          3.2.0-pyhd8ed1ab_3      https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgejupyter_client:      6.1.12-pyhd8ed1ab_0     https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgejupyter_core:        4.7.1-py36h5fab9bb_0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgejupyterlab_pygments: 0.1.2-pyh9f0ad1d_0      https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgelibsodium:           1.0.18-h36c2ea0_1       https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgemarkupsafe:          2.0.1-py36h8f6f2f9_0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgemistune:             0.8.4-py36h8f6f2f9_1004 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgenb_conda:            2.2.1-py36h5fab9bb_4    https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgenb_conda_kernels:    2.3.1-py36h5fab9bb_0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgenbclient:            0.5.3-pyhd8ed1ab_0      https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgenbconvert:           6.0.7-py36h5fab9bb_3    https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgenbformat:            5.1.3-pyhd8ed1ab_0      https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgenest-asyncio:        1.5.1-pyhd8ed1ab_0      https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgenotebook:            6.3.0-py36h5fab9bb_0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgepackaging:           21.0-pyhd8ed1ab_0       https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgepandoc:              2.14.1-h7f98852_0       https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgepandocfilters:       1.4.2-py_1              https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeprometheus_client:   0.11.0-pyhd8ed1ab_0     https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgepycparser:           2.20-pyh9f0ad1d_2       https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgepyparsing:           2.4.7-pyh9f0ad1d_0      https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgepyrsistent:          0.17.3-py36h8f6f2f9_2   https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgepython-dateutil:     2.8.2-pyhd8ed1ab_0      https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgepyzmq:               22.1.0-py36h7068817_0   https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgesend2trash:          1.7.1-pyhd8ed1ab_0      https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeterminado:           0.10.1-py36h5fab9bb_0   https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgetestpath:            0.5.0-pyhd8ed1ab_0      https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgetornado:             6.1-py36h8f6f2f9_1      https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgetyping_extensions:   3.10.0.0-pyha770c72_0   https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgewebencodings:        0.5.1-py_1              https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgezeromq:              4.3.4-h9c3ff4c_0        https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgezipp:                3.5.0-pyhd8ed1ab_0      https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeProceed ([y]/n)? yDownloading and Extracting Packages
nb_conda-2.2.1       |   36 KB | ########################################################## | 100%
ipykernel-5.5.5      |  166 KB | ########################################################## | 100%
pandocfilters-1.4.2  |    9 KB | ########################################################## | 100%
nbconvert-6.0.7      |  533 KB | ########################################################## | 100%
jinja2-3.0.1         |   99 KB | ########################################################## | 100%
pandoc-2.14.1        | 12.0 MB | ########################################################## | 100%
send2trash-1.7.1     |   17 KB | ########################################################## | 100%
typing_extensions-3. |   28 KB | ########################################################## | 100%
cffi-1.14.6          |  224 KB | ########################################################## | 100%
async_generator-1.10 |   18 KB | ########################################################## | 100%
webencodings-0.5.1   |   12 KB | ########################################################## | 100%
nbclient-0.5.3       |   67 KB | ########################################################## | 100%
mistune-0.8.4        |   54 KB | ########################################################## | 100%
markupsafe-2.0.1     |   22 KB | ########################################################## | 100%
attrs-21.2.0         |   44 KB | ########################################################## | 100%
testpath-0.5.0       |   86 KB | ########################################################## | 100%
pyzmq-22.1.0         |  528 KB | ########################################################## | 100%
argon2-cffi-20.1.0   |   47 KB | ########################################################## | 100%
prometheus_client-0. |   46 KB | ########################################################## | 100%
entrypoints-0.3      |    8 KB | ########################################################## | 100%
importlib-metadata-4 |   31 KB | ########################################################## | 100%
python-dateutil-2.8. |  240 KB | ########################################################## | 100%
jupyter_core-4.7.1   |   72 KB | ########################################################## | 100%
bleach-3.3.1         |  111 KB | ########################################################## | 100%
packaging-21.0       |   35 KB | ########################################################## | 100%
terminado-0.10.1     |   26 KB | ########################################################## | 100%
nest-asyncio-1.5.1   |    9 KB | ########################################################## | 100%
defusedxml-0.7.1     |   23 KB | ########################################################## | 100%
nbformat-5.1.3       |   47 KB | ########################################################## | 100%
libsodium-1.0.18     |  366 KB | ########################################################## | 100%
jupyterlab_pygments- |    8 KB | ########################################################## | 100%
notebook-6.3.0       |  6.3 MB | ########################################################## | 100%
zeromq-4.3.4         |  352 KB | ########################################################## | 100%
zipp-3.5.0           |   12 KB | ########################################################## | 100%
pyrsistent-0.17.3    |   89 KB | ########################################################## | 100%
tornado-6.1          |  643 KB | ########################################################## | 100%
jsonschema-3.2.0     |   45 KB | ########################################################## | 100%
jupyter_client-6.1.1 |   79 KB | ########################################################## | 100%
nb_conda_kernels-2.3 |   27 KB | ########################################################## | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: / Enabling nb_conda_kernels...
CONDA_PREFIX: /home/bit/anaconda3/envs/MaskRCNN
Status: enabled\ + /home/bit/anaconda3/envs/MaskRCNN/bin/jupyter-nbextension enable nb_conda --py --sys-prefix
Config option `kernel_spec_manager_class` not recognized by `EnableNBExtensionApp`.
Enabling notebook extension nb_conda/main...- Validating: OK
Enabling tree extension nb_conda/tree...- Validating: OK
+ /home/bit/anaconda3/envs/MaskRCNN/bin/jupyter-serverextension enable nb_conda --py --sys-prefix
Config option `kernel_spec_manager_class` not recognized by `EnableServerExtensionApp`.
Enabling: nb_conda
- Writing config: /home/bit/anaconda3/envs/MaskRCNN/etc/jupyter- Validating...nb_conda 2.2.1 OKdone

三、下载数据集

3.1 下载数据集和权重文件

  • 下载预训练的 COCO 权重 (mask_rcnn_coco.h5)

  • 下载MS COCO数据集

  • 下载 5K minival 和 35K validation-minus-minival 子集.

3.2 构建数据集

创建数据集文件夹，并将数据集放入：

四、网络训练

五、问题解决

5.1 Keras requires TensorFlow 2.2 or higher.

 pip install keras==2.0.8

5.2 AttributeError: ‘str’ object has no attribute ‘decode’

卸载原来的h5py模块，安装2.10版本

pip install h5py==2.10 -i https://pypi.tuna.tsinghua.edu.cn/simple/

5.3 ModuleNotFoundError: No module named ‘mrcnn’

python setup.py install

5.4 在TensorFlow中屏蔽warning的方式

https://www.yht7.com/news/30396

https://www.freesion.com/article/5863338313/
https://blog.csdn.net/qq_29462849/article/details/81037343
https://blog.csdn.net/u012746060/article/details/82143285

MaskRCNN代码训练复现流程以及相关问题解决相关推荐

  1. caffe SSD 代码编译运行流程及问题解决

    caffe SSD 代码编译运行流程及问题解决 该文基于以下代码: https://github.com/weiliu89/caffe/tree/ssd down下来后,进入目录 -rw-rw-r-- ...

  2. Pointnet++复现流程及问题解决

    复现流程 1.通过github下载pointnet++的包; 2.以分类为例,在pointnet2-master目录下新建data文件夹,将modelnet40_ply_hdf5_2048数据集解压到 ...

  3. SiamFC代码配置复现 matlab版本

    原创 SiamFC代码配置复现 2019-04-29 22:18:06 ZZXin_ 阅读数 1603更多 分类专栏: 深度学习 版权声明:本文为博主原创文章,遵循 CC 4.0 BY-SA 版权协议 ...

  4. Deep-Feature-Flow文章及代码训练解析

    Deep Feature Flow for Video Recognition CVPR2017 Github地址:https://github.com/msracver/Deep-Feature-F ...

  5. Colosal-AI复现流程

    Colosal-AI复现流程 1 环境搭建 1.1 cuda环境 1.2 python环境 1.3 python package 环境 2 下载代码 3 模型训练 3.1 SFT(supervised ...

  6. U2Net、U2NetP分割模型训练---自定义dataset、训练代码训练自己的数据集

    前言 博客很久没有更新了,今天就来更新一篇博客吧,哈哈: 最近在做图像分割相关的任务,因此,写这么一篇博客来简单实现一下分割是怎么做的,内容简单,枯燥,需要耐心看,哈哈: 博客的内容相对简单,比较适合 ...

  7. python检测吸烟的算法_yolov3+tensorflow+keras实现吸烟的训练全流程及识别检测

    yolov3+tensorflow+keras实现吸烟的训练全流程及识别检测 弈休丶 2019-12-30 23:29:54 1591 收藏 19 分类专栏: 基于yolov3+tensorflow+ ...

  8. 【2020】win10java（jdk安装）环境变量配置和相关问题解决

    [2020]win10java环境变量配置和相关问题解决 写在前面的话 前置条件(阅读以下内容需要掌握的知识) 准备 常见问题一览 安装后如何配置环境变量 剩余的问题 为了测试需要准备的 1.版本不统 ...

  9. 【国家局发布】医疗器械注册流程及相关法规大全

    [国家局发布]医疗器械注册流程及相关法规大全 2018-10-06 22:17 医疗器械注册申报流程图 具体流程如下 一.注册申请资料准备 一.注册申报资料依据 <关于公布医疗器械注册申报资料要 ...

最新文章

  1. 自动取款机如何使用无卡取款_如何设计700度高温下使用的自动夹具？
  2. 对卫星网络及内容的安全防护措施
  3. java数组缓冲,java – 字节数组缓冲图像转换速度慢
  4. 最佳实践丨三种典型场景下的云上虚拟IDC（私有池）选购指南
  5. c语言mfc弹出窗口函数,CMFCDesktopAlertWnd实现桌面弹出消息框
  6. power of two java_LeetCode算法题-Power Of Two（Java实现）
  7. 【今日CS 视觉论文速览】20 Dec 2018
  8. node php环境变量配置,关于NodeJS、NPM安装配置步骤(windows版本) 以及环境变量的介绍...
  9. python数据驱动登录_python之数据驱动ddt操作（方法三）
  10. 水晶报表的使用经验和资料总结
  11. 烦了，放弃卡巴——改用小红伞
  12. 架构之美-最强卷积神经网络架构设计初想
  13. Retinanet论文解读
  14. 万万没想到，“红孩儿”竟然做了程序员，还是CTO!
  15. 【Python】用字母生成图像
  16. 图像RGB与数组关系理解
  17. 分布式文件系统KFS
  18. 企业应如何办理银行承兑汇票
  19. Gluster常见故障处理和HOWTO资源
  20. 微信小程序开发如何实现微信支付

热门文章

  1. 探秘丝涟“美梦工厂”—舒适焕新 美梦升级
  2. 沉睡者IT创业项目 - 学习如何玩直播卖零食
  3. 是心跳影响情绪，还是情绪影响心跳？
  4. 再来一个高仿开眼的短视频APP
  5. Surface 和 SurfaceHolder
  6. 每日享视频，开眼看世界
  7. LWN：利用Org mode和iCalendar来管理自己的task！
  8. 北京市两限房管理办法揭秘
  9. 快速分析多个德邦单号物流，并将信息导出EXCEL表格
  10. 回溯算法背包问题（java实现）