Deep Learning Applications (Darknet - YOLOv3, YOLOv4 | DeOldify - Image Colorization, Video Colorization | Face-Recognition) with Google Colaboratory - on the free Tesla K80/Tesla T4/Tesla P100 GPU - using Keras, Tensorflow and PyTorch. - Deep-Learning-with-GoogleColab/VideoColorizerColab.ipynb at master · hardik0/Deep-Learning-with-GoogleColab. Video_Colorizer_Colab_DeOldify Python · No attached data sources. Video_Colorizer_Colab_DeOldify. Notebook. Input. Output. Logs. Comments (0) Run. 3.6s. history Version 4 of 4. License . This Notebook has been released under the Apache 2.0 open source li. 1 sept. 2021 · video_moredata_l1 under the checkpoints folder; vgg19_conv.pth and vgg19_gray.pth under the data folder; Data Preparation. In order to colorize your own video, it requires to extract the video frames, and provide a reference image as an example. Place your video frames into one folder, e.g., ./sample_videos/v32_180. Running the Jupyter notebook on your own machine is recommended (and faster) for larger video sizes. #### Credits: Big special thanks to: Robert Bell for all his work on the video Colab notebook, and paving the way to video in DeOldify! Dana Kelley for doing things, breaking stuff & having an opinion on everything. Following up on my goal of doing things easily, I wanted to try DeOldify to convert B&W video content with audio over and over again, without having to change code or lose progress due to the free resource session timing out on Google Colab. Below are the steps — around 10 clicks, enabling you to do just that! Keep in mind I have tested only.