GitHub repository for "Towards an Understanding of Our World by GANing Videos in the Wild"
For more information please refer to our homepage.
- Tensorflow 1.2.1
- Python 2.7
- ffmpeg
Videos are stored as JPEGs of vertically stacked frames. Every frame needs to be at least 64x64 pixels; videos contain between 16 and 32 frames. For an example datasets see: http://carlvondrick.com/tinyvideo/#data
python main_train.py
Important Parameters:
- mode: one of 'generate', 'predict', 'bw2rgb', 'inpaint' depending on weather you want to generate videos, predict future frames, colorize videos or do inpainting.
- batch_size: Recommended 64, for colorization use 32 for memory issues.
- root_dir: root directory of dataset
- index_file: must be in root_dir, containing a list of all training data clips; path relative to root_dir.
- experiment_name: name of experiment
- output_every: output loss to stdout and write to tensorboard summary every xx steps.
- sample_every: generate a visual sample every xx steps.
- save_model_very: save the model every xx steps.
- recover_model: if true recover model and continue training