watch the demo on youtube:

Deep-learning-Colorization-for-visual-media

Automatic colorization for grayscale (images/ videos) based on Deep-Learning using (Python & Tensorflow).

A TensorFlow version of (Let there be Color!: Joint End-to-end Learning of Global and Local Image Priors for Automatic Image Colorization with Simultaneous Classification) http://hi.cs.waseda.ac.jp/~iizuka/projects/colorization/en/ Applied on Landscape images only(2000 images from MIT Places) data-set for leak of resources.

implement videos part
apply and re-train the model using classification network
train the model on more than one category.
find all information needed in project documentation and presentation files from google drive link below. https://drive.google.com/drive/folders/0B7FFqObqrfTDOG5OSVZ4UUJ5S1U?usp=sharing

note: it's trained only on simple landscape images(2000 image) so it will not give a good result if tried to test anothe category or complex images
download .exe file attached from google drive and instruction file
read insteraction to use .exe.txt to know how to run for first time
Colorization trained model weights https://drive.google.com/file/d/1QzTMl8jHeowjzRP7DcfIQk4IpwVyTaGo/view?usp=sharing
let me know if you faced any problems with loading the pre-trained weights

project is still under maintenance and processing.
you should be aware of change file pathes corrosponding to your data set locations when try to read or test images
you should be aware of handling creating Model weight directory for first time to save trained model's weights every time you perform tarining.
There is a single file containing the whole code as functions used temporarily for testing.