What is this?
This document shows you how to install Colorful Image Colorization on Windows 10 and Python 3.x (3.8.6).
Steps
Step 1. Install Python on Windows
Version 3.8 of Windows x86-64 executable installer seems better:
https://www.python.org/downloads/windows/
Step 2. Install richzhang/colorization
Clone the repository
git clone https://github.com/richzhang/colorization.git
CUDA
Download and install CUDA 10.2:
https://developer.nvidia.com/cuda-downloads
PyTorch (torch)
pip install torch===1.6.0 torchvision===0.7.0 -f https://download.pytorch.org/whl/torch_stable.html
# For more details see below
# https://stackoverflow.com/questions/56859803/modulenotfounderror-no-module-named-tools-nnwrap
Others
Please note that I chose scikit-image
instead of skimage
.
pip install wheel scikit-image matplotlib argparse
pip install ipython
Step 3. Run
cd colorization
python demo_release.py -i imgs/ansel_adams3.jpg
Congratulations!
Logs
PyTorch (torch)
Click here to see command-line logs
C:\Users\AAA>pip install torch===1.6.0 torchvision===0.7.0 -f https://download.pytorch.org/whl/torch_stable.html
Looking in links: https://download.pytorch.org/whl/torch_stable.html
Collecting torch===1.6.0
Downloading https://download.pytorch.org/whl/cu102/torch-1.6.0-cp38-cp38-win_amd64.whl (1077.4 MB)
|████████████████████████████████| 1077.4 MB 833 bytes/s
Collecting torchvision===0.7.0
Downloading https://download.pytorch.org/whl/cu102/torchvision-0.7.0-cp38-cp38-win_amd64.whl (1.1 MB)
|████████████████████████████████| 1.1 MB 6.8 MB/s
Collecting future
Downloading future-0.18.2.tar.gz (829 kB)
|████████████████████████████████| 829 kB 3.2 MB/s
Collecting numpy
Downloading numpy-1.19.2-cp38-cp38-win_amd64.whl (13.0 MB)
|████████████████████████████████| 13.0 MB 6.8 MB/s
Collecting pillow>=4.1.1
Downloading Pillow-8.0.0-cp38-cp38-win_amd64.whl (2.1 MB)
|████████████████████████████████| 2.1 MB 6.4 MB/s
Using legacy 'setup.py install' for future, since package 'wheel' is not installed.
Installing collected packages: future, numpy, torch, pillow, torchvision
Running setup.py install for future ... done
Successfully installed future-0.18.2 numpy-1.19.2 pillow-8.0.0 torch-1.6.0 torchvision-0.7.0
PIL
seems to be the name used in Python 2.x, and pillow
seems to be the name used in Python 3.x.
Others
Click here to see command-line logs
C:\Users\AAA>pip install wheel scikit-image matplotlib argparse
Collecting wheel
Using cached wheel-0.35.1-py2.py3-none-any.whl (33 kB)
Collecting scikit-image
Downloading scikit_image-0.17.2-cp38-cp38-win_amd64.whl (11.7 MB)
|████████████████████████████████| 11.7 MB 3.3 MB/s
Collecting matplotlib
Downloading matplotlib-3.3.2-cp38-cp38-win_amd64.whl (8.5 MB)
|████████████████████████████████| 8.5 MB 6.4 MB/s
Collecting argparse
Using cached argparse-1.4.0-py2.py3-none-any.whl (23 kB)
Collecting scipy>=1.0.1
Downloading scipy-1.5.3-cp38-cp38-win_amd64.whl (31.4 MB)
|████████████████████████████████| 31.4 MB 6.4 MB/s
Collecting imageio>=2.3.0
Downloading imageio-2.9.0-py3-none-any.whl (3.3 MB)
|████████████████████████████████| 3.3 MB ...
Requirement already satisfied: pillow!=7.1.0,!=7.1.1,>=4.3.0 in c:\home\sdk\python38\lib\site-packages (from scikit-image) (8.0.0)
Collecting tifffile>=2019.7.26
Downloading tifffile-2020.10.1-py3-none-any.whl (152 kB)
|████████████████████████████████| 152 kB 6.8 MB/s
Collecting PyWavelets>=1.1.1
Downloading PyWavelets-1.1.1-cp38-cp38-win_amd64.whl (4.3 MB)
|████████████████████████████████| 4.3 MB 6.8 MB/s
Requirement already satisfied: numpy>=1.15.1 in c:\home\sdk\python38\lib\site-packages (from scikit-image) (1.19.2)
Collecting networkx>=2.0
Downloading networkx-2.5-py3-none-any.whl (1.6 MB)
|████████████████████████████████| 1.6 MB ...
Collecting pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3
Using cached pyparsing-2.4.7-py2.py3-none-any.whl (67 kB)
Collecting certifi>=2020.06.20
Using cached certifi-2020.6.20-py2.py3-none-any.whl (156 kB)
Collecting python-dateutil>=2.1
Using cached python_dateutil-2.8.1-py2.py3-none-any.whl (227 kB)
Collecting cycler>=0.10
Using cached cycler-0.10.0-py2.py3-none-any.whl (6.5 kB)
Collecting kiwisolver>=1.0.1
Downloading kiwisolver-1.2.0-cp38-none-win_amd64.whl (58 kB)
|████████████████████████████████| 58 kB ...
Collecting decorator>=4.3.0
Downloading decorator-4.4.2-py2.py3-none-any.whl (9.2 kB)
Collecting six>=1.5
Using cached six-1.15.0-py2.py3-none-any.whl (10 kB)
Installing collected packages: wheel, scipy, imageio, tifffile, PyWavelets, pyparsing, certifi, six, python-dateutil, cycler, kiwisolver, matplotlib, decorator, networkx, scikit-image, argparse
Successfully installed PyWavelets-1.1.1 argparse-1.4.0 certifi-2020.6.20 cycler-0.10.0 decorator-4.4.2 imageio-2.9.0 kiwisolver-1.2.0 matplotlib-3.3.2 networkx-2.5 pyparsing-2.4.7 python-dateutil-2.8.1 scikit-image-0.17.2 scipy-1.5.3 six-1.15.0 tifffile-2020.10.1 wheel-0.35.1
c:\home\sdk\python38
is a directory name that is unique to my environment.
First run
Click here to see command-line logs
C:\home\src\colorization>python demo_release.py -i imgs/ansel_adams3.jpg
Downloading: "https://colorizers.s3.us-east-2.amazonaws.com/colorization_release_v2-9b330a0b.pth" to C:\Users\AAA/.cache\torch\hub\checkpoints\colorization_release_v2-9b330a0b.pth
100.0%
Downloading: "https://colorizers.s3.us-east-2.amazonaws.com/siggraph17-df00044c.pth" to C:\Users\AAA/.cache\torch\hub\checkpoints\siggraph17-df00044c.pth
100.0%
C:\home\sdk\python38\lib\site-packages\torch\nn\functional.py:3118: 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.
warnings.warn("Default upsampling behavior when mode={} is changed "
C:\home\sdk\python38\lib\site-packages\skimage\color\colorconv.py:1128: UserWarning: Color data out of range: Z < 0 in 367 pixels
return xyz2rgb(lab2xyz(lab, illuminant, observer))
C:\home\sdk\python38\lib\site-packages\skimage\color\colorconv.py:1128: UserWarning: Color data out of range: Z < 0 in 33 pixels
return xyz2rgb(lab2xyz(lab, illuminant, observer))![](https://storage.googleapis.com/zenn-user-upload/owfupao294w6w9z4j0wr2w813agg)
Note
This page is a clone of the Zenn article.