DeepMosaics

# DeepMosaics **English | [中文](./README_CN.md)**
You can use it to automatically remove the mosaics in images and videos, or add mosaics to them.
This project is based on "semantic segmentation" and "Image-to-Image Translation".
Try it at this [website](http://118.89.27.46:5000/)!
### Examples | origin | auto add mosaic | auto clean mosaic | | :----------------------------------: | :--------------------------------------: | :----------------------------------------: | | | | | | | | | - Compared with [DeepCreamPy](https://github.com/deeppomf/DeepCreamPy) | mosaic image | DeepCreamPy | ours | | :----------------------------------------: | :--------------------------------: | :---------------------------------------: | | | | | | | | | - Style Transfer | origin | to Van Gogh | to winter | | :------------------------------: | :--------------------------------------: | :--------------------------------------------: | | | | | An interesting example:[Ricardo Milos to cat](https://www.bilibili.com/video/BV1Q7411W7n6) ## Run DeepMosaics You can either run DeepMosaics via a pre-built binary package, or from source.
### Try it on web You can simply try to remove the mosaic on the **face** at this [website](http://118.89.27.46:5000/).
### Pre-built binary package For Windows, we bulid a GUI version for easy testing.
Download this version, and a pre-trained model via [[Google Drive]](https://drive.google.com/open?id=1LTERcN33McoiztYEwBxMuRjjgxh4DEPs) [[百度云,提取码1x0a]](https://pan.baidu.com/s/10rN3U3zd5TmfGpO_PEShqQ)
- [[Help document]](./docs/exe_help.md)
- Video tutorial => [[youtube]](https://www.youtube.com/watch?v=1kEmYawJ_vk) [[bilibili]](https://www.bilibili.com/video/BV1QK4y1a7Av)
Attentions:
- Requires Windows_x86_64, Windows10 is better.
- Different pre-trained models are suitable for different effects.[[Introduction to pre-trained models]](./docs/pre-trained_models_introduction.md)
- Run time depends on computers performance (GPU version has better performance but requires CUDA to be installed).
- If output video cannot be played, you can try with [potplayer](https://daumpotplayer.com/download/).
- GUI version updates slower than source.
### Run From Source #### Prerequisites - Linux, Mac OS, Windows - Python 3.6+ - [ffmpeg 3.4.6](http://ffmpeg.org/) - [Pytorch 1.0+](https://pytorch.org/) - CPU or NVIDIA GPU + CUDA CuDNN
#### Dependencies This code depends on opencv-python, torchvision available via pip install. #### Clone this repo ```bash git clone https://github.com/HypoX64/DeepMosaics.git cd DeepMosaics ``` #### Get Pre-Trained Models You can download pre_trained models and put them into './pretrained_models'.
[[Google Drive]](https://drive.google.com/open?id=1LTERcN33McoiztYEwBxMuRjjgxh4DEPs) [[百度云,提取码1x0a]](https://pan.baidu.com/s/10rN3U3zd5TmfGpO_PEShqQ)
[[Introduction to pre-trained models]](./docs/pre-trained_models_introduction.md)
In order to add/remove mosaic, there must be a model file `mosaic_position.pth` at `./pretrained_models/mosaic/mosaic_position.pth` #### Install dependencies (Optional) Create a virtual environment ```bash virtualenv mosaic source mosaic/bin/activate ``` Then install the dependencies ```bash pip install -r requirements.txt ``` If you can not build `scikit-image`, running `export CFLAGS='-Wno-implicit-function-declaration` then try to rebuild. #### Simple Example - Add Mosaic (output media will be saved in './result')
```bash python deepmosaic.py --media_path ./imgs/ruoruo.jpg --model_path ./pretrained_models/mosaic/add_face.pth --gpu_id 0 ``` - Clean Mosaic (output media will save in './result')
```bash python deepmosaic.py --media_path ./result/ruoruo_add.jpg --model_path ./pretrained_models/mosaic/clean_face_HD.pth --gpu_id 0 ``` If you see the error `Please check mosaic_position_model_path!`, check if there is a model file named `mosaic_position.pth` at `./pretrained_models/mosaic/mosaic_position.pth` #### More Parameters If you want to test other images or videos, please refer to this file.
[[options_introduction.md]](./docs/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](./docs/training_with_your_own_dataset.md) ## Acknowledgements This code borrows heavily from [[pytorch-CycleGAN-and-pix2pix]](https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix) [[Pytorch-UNet]](https://github.com/milesial/Pytorch-UNet) [[pix2pixHD]](https://github.com/NVIDIA/pix2pixHD) [[BiSeNet]](https://github.com/ooooverflow/BiSeNet) [[DFDNet]](https://github.com/csxmli2016/DFDNet) [[GFRNet_pytorch_new]](https://github.com/sonack/GFRNet_pytorch_new).