DeepMosaics

You can use it to automatically remove the mosaics in images and videos, or add mosaics to them.
This porject based on ‘semantic segmentation’ and ‘Image-to-Image Translation’.

• 中文版
  

More example

origin	auto add mosaic	auto clean mosaic

• Compared with DeepCreamPy

mosaic image	DeepCreamPy	ours

Notice

The code do not include the part of training, I will finish it in my free time.

Run DeepMosaics

You can either run DeepMosaics via pre-built binary package or from source.

Pre-built binary package

For windows, we bulid a GUI version for easy test.
Download this version via [Google Drive] [百度云,提取码1x0a]

Attentions:

• Require Windows_x86_64, Windows10 is better.
  
• Different pre-trained models are suitable for different effects.
  
• Run time depends on computer performance.
  
• If output video cannot be played, you can try with potplayer.
• GUI version update slower than source.

Run from source

Prerequisites

• Linux, Mac OS, Windows
• Python 3.6+
• ffmpeg 3.4
• Pytorch 1.0+ (Old version codes)
• CPU or NVIDIA GPU + CUDA CuDNN
  

Dependencies

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

Clone this repo

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

Get pre_trained models and test video

You can download pre_trained models and test video and replace the files in the project.
[Google Drive] [百度云,提取码7thu]

Simple example

• Add Mosaic (output video will save in './result')

python3 deepmosaic.py

• Clean Mosaic (output video will save in './result')

python3 deepmosaic.py --mode clean --model_path ./pretrained_models/clean_hands_unet_128.pth --media_path ./result/hands_test_AddMosaic.mp4

More parameters

If you want to test other image or video, please refer to this file. [options.py]

Acknowledgments

This code borrows heavily from [pytorch-CycleGAN-and-pix2pix] [Pytorch-UNet][pix2pixHD].