Anime-InPainting

youyuge34/Anime-InPainting is ranked 11,476 among these 8 peers; google-deepmind/dramatron is ranked 11,472.

27 Update:** Our **latest** drawing method PI-REC is more powerful. Take a look on it, and I'm sure it won't disappoint you. Make sure you have read their awesome work and license thoroughly. Compared with the original work, this project has such improvements : Add tool application modes Optimize the training phase Auto-save and auto-load latest weights files Add a fast training phase combined with origin phase 2 and 3 bugs fixed (most of them are merged into

the original work) Add utility files Add configs in PRINT_FREQUENCY DEVICE : cpu or gpu . **You can do the amazing Anime inpainting conveniently here. ** **And detailed training manual is released. You may train your own dataset smoothly now. ** Prerequisites Python 3 PyTorch ( is not supported) NVIDIA GPU + CUDA cuDNN Installation Clone this repo Install PyTorch and dependencies from Install python requirements: Run the Tool I want to run the tool! Calm down and follow such step: **Info: The following weights

files are trained on anime face dataset which performs not good on a large whole anime character. Unzip the and put it under your root directory. Complete the above Prerequisites and Installation 4. (Optional) Check and edit the config file as you wish 5. Run the cooool tool: Default Tool: Tool with edge window: Args help PS. You can run any well trained model, not only above one. You can download more model weights files from the original work Edge

-Connect. Only one thing to be careful: The in this project has some additional options than the config from the Edge-Connect. Tool operation For detailed manual, refer to your prints or the in . Except where otherwise noted, this content is published under a CC BY-NC license, which means that you can copy, remix, transform and build upon the content as long as you do not use the material for commercial purposes and give appropriate credit and provide a

link to the license. Citation If you use this code for your research, please cite our paper EdgeConnect: Generative Image Inpainting with Adversarial Edge Learning :