Deep3D

Real-Time end-to-end 2D-to-3D Video Conversion, based on deep learning.
Inspired by piiswrong/deep3d, we rebuild the network on pytorch and optimize it in time domain and faster inference speed. So, try it and enjoy your own 3D movies.

Left is input video and right is output video with parallax.

More examples:

• wood-1080p
• Journey to the West (86)

Inference speed

Plan	360p (FPS)	720p (FPS)	1080p (FPS)	4k (FPS)
GPU (2080ti)	84	87	77	26
CPU (Xeon Platinum 8260)	27.7	14.1	7.2	2.0

Run Deep3D

Prerequisites

• Linux, Mac OS, Windows
• Python 3.7+
• ffmpeg 3.4.6+
• Pytorch 1.7.1
• CPU or NVIDIA GPU
  

Dependencies

This code depends on opencv-python available via pip install.

pip install opencv-python

Clone this repo

git clone https://github.com/HypoX64/Deep3D
cd Deep3D

Get Pre-Trained Models

You can download pre_trained models from: [Google Drive] [百度云,提取码xxo0 ]
Note:

• 360p can get the best result.
• The published models are not inference optimized.
• Models are still under training, 1080p and 4k models will be uploaded in the future.

Run it!

python inference.py --model ./export/deep3d_v1.0_640x360_cuda.pt --video ./medias/wood.mp4 --out ./result/wood.mp4 --inv
# some video need to reverse left and right views (--inv)

Acknowledgements

This code borrows heavily from [deep3d] [DeepMosaics]