lucifer99966623/pix2pix-next-frame-prediction

pix2pix-Next-Frame-Prediction generates video by recursively generating images with pix2pix.

pix2pix-Next-Frame-Prediction

Description

pix2pix-Next-Frame-Prediction generates video by recursively generating images with pix2pix.
We use the memo's script for training and prediction.

training : affinelayer/pix2pix-tensorflow
prediction : memo/webcam-pix2pix-tensorflow

ToDo

• simple training
• re-training using this technique
• run realtime

Demo

Source : https://vimeo.com/223771736

Dependence

• ffmpeg

Usage

Create Dataset

1. Split movie to image sequence

python create_dataset.py data/XXX.mp4 data/XXX 30 png

2. Resize source images

python pix2pix/tools/process.py --input_dir data/XXX --operation resize --output_dir data/resized

3. Copy the file at step2

cp -r data/resized data/resized2

4. Delete image_0000.png of resized2 and image_xxxx.png(last image) of resized1

5. Rename the images

python rename.py data/resized
python rename.py data/resized2

5. Combine resized 2 set of images

python pix2pix/tools/process.py --input_dir data/resized --b_dir data/resized2 --operation combine --output_dir data/combined

• Split into train/val set

python pix2pix/tools/split.py --dir data/combined

Training

python pix2pix/pix2pix.py --mode train --output_dir dst_path --max_epochs 200 --input_dir data_path --which_direction AtoB

Generate image sequence

python generate.py models/XXX.json generate/src generate/dst num_itr

Generate movie

1. combine

ffmpeg -r 30 -i generate/dst/%04d.png -vcodec libx264 -pix_fmt yuv420p -r 30 movie.mp4

2. Resize

ffmpeg -i movie.mp4 -vf scale=640:-1 m.mp4

Reference

• affinelayer/pix2pix-tensorflow
• memo/webcam-pix2pix-tensorflow
• magenta/magenta/video/next_frame_prediction_pix2pix
• A train window

Licence

MIT