推理需自行准备对应的 .onnx 模型文件,仓库不保证自带;部分风格模型和训练数据发布在 Patreon 等外部渠道;视频转动漫需另用 tools/video2anime.py 并指定模型路径。
AnimeGANv3
TachibanaYoshino长期未更新用 AnimeGANv3 把照片或视频一键转成日漫风格,支持 Colab、ONNX、CoreML、TFLite 等多种部署格式,方便直接产出动画作品。
Use AnimeGANv3 to make your own animation works, including turning photos or videos into anime.
git clone https://github.com/TachibanaYoshino/AnimeGANv3.git
cd AnimeGANv3
pip install -r requirements.txt
python deploy/test_by_onnx.py -i inputs/imgs/ -o output/results -m deploy/AnimeGANv3_Hayao_36.onnxREADME 未说明显存要求;提到 tiny 模型在 iPhone14 上 512*512 输入可达 50 FPS,并给出 TensorRT、rknn 推理分支,但未列出具体 GPU 型号。
用 GAN 把照片和视频转成动漫风格,自带多种预训练 onnx 模型可直接推理
用 AnimeGANv3 把照片或视频一键转成日漫风格,支持 Colab、ONNX、CoreML、TFLite 等多种部署格式,方便直接产出动画作品。
核心能力
- 提供照片转动漫的 onnx 推理脚本
- 提供视频转动漫的 onnx 推理脚本
- 覆盖吉卜力、新海诚、迪士尼等多种风格模型
- 附带 UI 工具和官方在线 Demo
- 提供 TensorRT 与 rknn 转换推理分支
容易踩的坑
- v1.1.0The Hayao style and Shinkai style最新正式版2023-11-23 · 2023-11-23 06:06 UTC
For the .tflite, its input shape is (1, 512, 512, 3). For the .mlmodel, its input is an image of 512*512 size.
- v1.0.3Hayao style and Shinkai style2023-11-23 · 2023-11-23 05:50 UTC
查看更新说明
old version
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AnimeGANv3
Paper Title: A Novel Double-Tail Generative Adversarial Network for Fast Photo Animation.
Let's use AnimeGANv3 to produce our own animation.
📢 Updates
2025-08-22Added a new AnimeGANv3 model for Face to Ghibli-c1 style. Its model files and training data have been open source. The training data of Ghibli-o1 style can be accessed here.2025-02-16Released the TensorRT-based model conversion and inference repo.2024-12-15Released the rknn-based model conversion and inference repo.2024-11-27Disney and Trump styles updated to version 2.0.2024-10-31Added a new styles of AnimeGANv3: Portrait to Pixar. :jack_o_lantern:2024-08-28A repo more suitable for portrait style inference based on the AnimeGANv3 models has been released. Highly recommended.🔥2023-12-10Added a new AnimeGANv3 model for Portrait to Oil-painting style. Its onnx is available here.2023-11-23The code and the manuscript are released. 🦃2023-10-31Added three new styles of AnimeGANv3: Portrait to Cute, 8bit and Sketch-0 style. :ghost:2023-09-18Added a new AnimeGANv3 model for Face to Kpop style.2023-01-16Added a new AnimeGANv3-photo.exe for the inference of AnimeGANv3's onnx model.2023-01-13Added a new AnimeGANv3 model for Face to comic style.2022-12-25Added the tiny model (2.4MB) ofNordic myth styleand USA style 2.0. It can go upto 50 FPS on iphone14 with 512*512 input. :santa:2022-11-24Added a new AnimeGANv3 model for Face to Nordic myth style.🦃2022-11-06Added a new AnimeGANv3 model for Face to Disney style V1.0.2022-10-31Added a new AnimeGANv3 model for Face to USA cartoon and Disney style V1.0. :jack_o_lantern:2022-10-07The USA cartoon Style of AnimeGANv3 is integrated to ProfileProfile with Core ML. Install it by the Apple Store and have a try.2022-09-26Official online demo is integrated to Huggingface Spaces with Gradio.2022-09-24Added a new great AnimeGANv3 model for Face to USA cartoon Style.2022-09-18Update a new AnimeGANv3 model for Photo to Hayao Style.2022-08-01Added a new AnimeGANv3 onnx model (Colab) for Face to Arcane style.2022-07-13Added a new AnimeGANv3 onnx model (Colab) for Face to portrait sketch.2021-12-25The paper of AnimeGANv3 will be released in 2022. :christmas_tree:
🎮 Usage
-
Download this repository and use AnimeGANv3's UI tool and pre-trained *.onnx to turn your photos into anime. :blush:
-
🛠️ Installation
-
Clone repo
git clone https://github.com/TachibanaYoshino/AnimeGANv3.git cd AnimeGANv3 -
Install dependent packages
pip install -r requirements.txt -
Inference with *.onnx
python deploy/test_by_onnx.py -i inputs/imgs/ -o output/results -m deploy/AnimeGANv3_Hayao_36.onnx -
video to anime with *.onnx
python tools/video2anime.py -i inputs/vid/1.mp4 -o output/results -m deploy/AnimeGANv3_Hayao_36.onnx
-
🚀 Landscape Demos
:fire: Video to anime (Hayao Style)
:art: Photo to Hayao Style







:art: Photo to Shinkai Style






🚀 Portrait Style Demos
The paper has been completed in 2022. The study of portrait stylization is an extension of the paper.
:art: Face to USA cartoon style


https://github.com/user-attachments/assets/9644b1f5-78a4-4dcd-9da0-0186fbf5ab94
:art: Face to Disney cartoon style


| v1.9 | v2.0 |
|---|---|
:art: Face to Ghibli-c1 style
:art: Face to Trump style

| v1.9 | v2.0 |
|---|---|

:art: Face to Arcane style


https://github.com/user-attachments/assets/ab082d32-cc77-4c89-92c1-6a50cfa6a77b
:art: Portrait to comic style


https://github.com/user-attachments/assets/3e999a8e-a331-46f6-863c-c01fd50591c8
:art: Face to Kpop style


https://github.com/user-attachments/assets/3a59537c-fff2-4c86-8462-d53b07ff596b
:art: Portrait to Oil-painting style


:art: Portrait to Cute style


https://github.com/user-attachments/assets/0b105ee7-8116-4456-931c-ec196200e288
:art: Portrait to Pixar style
https://github.com/user-attachments/assets/d9c4e931-3b3c-4b03-9531-63d9e391b4df
:art: Portrait to Sketch-0 style

https://github.com/user-attachments/assets/ed3f3511-4583-41d8-aad9-e47fdd2f5c32
:art: Portrait to 8bit style


:art: Face to portrait sketch
| input | Face | panoramic image |
|---|---|---|

🔨 Train
1. Download dataset and pretrained vgg19
2. Do edge_smooth
cd tools && python edge_smooth.py --dataset Hayao --img_size 256
3. Do superPixel
cd tools && python visual_superPixel_seg_image.py
4. Train
python train.py --style_dataset Hayao --init_G_epoch 5 --epoch 100
✒️ Citation
Consider citing as below if you find this repository helpful to your project:
@article{Liu2024dtgan,
title={A Novel Double-Tail Generative Adversarial Network for Fast Photo Animation},
author={Gang LIU and Xin CHEN and Zhixiang GAO},
journal={IEICE Transactions on Information and Systems},
volume={E107.D},
number={1},
pages={72-82},
year={2024},
doi={10.1587/transinf.2023EDP7061}
}
:scroll: License
This repo is made freely available to academic and non-academic entities for non-commercial purposes such as academic research, teaching, scientific publications. Permission is granted to use the AnimeGANv3 given that you agree to my license terms. Regarding the request for commercial use, please contact us via email to help you obtain the authorization letter.
:e-mail: Author
Asher Chan [email protected]