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    README.md

    image

    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".

    More example

    origin auto add mosaic auto clean mosaic
    image image image
    image image image
    mosaic image DeepCreamPy ours
    image image image
    image image image
    • Style Transfer
    origin to Van Gogh to winter
    image image image

    An interesting example:Ricardo Milos to cat

    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 and pre-trained model via [Google Drive] [百度云,提取码1x0a]

    image
    Attentions:

    • Require Windows_x86_64, Windows10 is better.
    • Different pre-trained models are suitable for different effects.[Introduction to pre-trained models]
    • Run time depends on computer performance(The current version does not support gpu, if you need to use gpu please run source).
    • If output video cannot be played, you can try with potplayer.
    • GUI version update slower than source.

    Run from source

    Prerequisites

    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

    You can download pre_trained models and put them into './pretrained_models'.
    [Google Drive] [百度云,提取码1x0a]
    [Introduction to pre-trained models]

    Simple example

    • Add Mosaic (output media will save in './result')
    python3 deepmosaic.py --media_path ./imgs/ruoruo.jpg --model_path ./pretrained_models/mosaic/add_face.pth --use_gpu 0
    • Clean Mosaic (output media will save in './result')
    python3 deepmosaic.py --media_path ./result/ruoruo_add.jpg --model_path ./pretrained_models/mosaic/clean_face_HD.pth --use_gpu 0

    More parameters

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

    Training with your own dataset

    If you want to train with your own dataset, please refer to training_with_your_own_dataset.md

    Acknowledgments

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

    项目简介

    使用深度学习方法去掉图片或视频中的马赛克

    发行版本

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    贡献者 2

    HypoX64 @weixin_36721459
    H HypoX64 @HypoX64

    开发语言

    • Python 100.0 %