highcwu / anime_biggan_toy

Generate Amazing Anime Pictures With BigGAN. Just Have Fun !!!

Anime BigGAN Toy

Generate Amazing Anime Pictures With BigGAN. Just Have Fun !!!

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Free V100 GPU For Model Test

My AI Studio Project

You can download the pretrained model of PaddlePaddle for local play from Anime BigGAN Pretrained Models As A Dataset or Google Drive which just contain the Generator Parameters.

File Samples.ipynb is a backup of this project's notebook.

My QQ Group: 1044867291

My Discord: https://discord.gg/YwWcAS47qb

Play in colab

Play it right now!

Play with TF!

Steps to convert model to TFHub, PyTorch and PaddlePaddle

• 1. Convert Shawwn's Model to TFHub version.
• 2. If you want to play the TFHub model, come here.
• 3. Convert TFHub generator model to PyTorch.
• 4. Convert TFHub discrimator model to PyTorch.
• 5. If you want to play the PyTorch model, come here.
• 6. Convert TFHub generator model to PaddlePaddle.
• 7. Convert TFHub discrimator model to PaddlePaddle.
• 8. If you want to play the PaddlePaddle model, come here.
• Wish you can have fun and find out more interesting ways to play it.

**Update 2020-10-25: Add truncnorm. Add a fast way to play the source tf pretrained model.

**Update 2022-05-22: Add colab for directly converting tf model to pytorch.

TODO

• Test code release.
• Make my AI Studio project public.
• Publish the colab notebook of model converting from TF to PaddlePaddle and PyTorch.
• Publish a gradio demo on HuggingFace Spaces.
• Update PaddlePaddle version to 2.3.

References

Models converted from Shawwn's training [1] and Gwern's release [2]. 2D character picture (HatsuneMiku) is licensed under CC BY-NC by piapro [3].

• [1] Shawwn, The model is trained based on his fork of google's 'compare_gan', https://github.com/shawwn/compare_gan/
• [2] Gwern, "A prototype anime BigGAN 256px trained on Danbooru2019+e621 for 600k iterations is now available for download", https://www.gwern.net/Faces#danbooru2019e621-256px-biggan
• [3] "For Creators", http://piapro.net/en_for_creators.html