DDColor can provide vivid and natural colorization for historical black and white old photos.
In this post, I’ll introduce how to run DDColor on Google Colab free-tier, T4.
Step 1. Clone the repo & install dependencies
First we need to install dependencies and this step will take some time.
!git clone https://github.com/piddnad/DDColor
!cd DDColor
!pip install -r requirements.txt
!python setup.py develop
!pip install "modelscope[cv]" -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html
Step 2. Adding Colors to Image
import cv2
from modelscope.outputs import OutputKeys
from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks
from google.colab.patches import cv2_imshow
img_colorization = pipeline(Tasks.image_colorization, model='damo/cv_ddcolor_image-colorization')
result = img_colorization('https://th.bing.com/th/id/R.bfff865861dc593b14fa030a9ac2aee5?rik=Of2Q7oLKe0r0fg&riu=http%3a%2f%2fstatic.guim.co.uk%2fsys-images%2fGuardian%2fPix%2fpictures%2f2013%2f2%2f18%2f1361186749737%2fblack-and-white-picture-o-005.jpg&ehk=zoDQaeRIcKRivy%2fXZH7lZa3ixweCv47WKzD8uJGwZgw%3d&risl=&pid=ImgRaw&r=0')
cv2.imwrite('result.png', result[OutputKeys.OUTPUT_IMG])
cv2_imshow(result[OutputKeys.OUTPUT_IMG])
Original
Colorized
My Google Colab note is 👇
https://colab.research.google.com/drive/1heF4BYz0Y35TNsmshseaD37USDSp3jY0?usp=sharing