DiffSynth Studio is a Diffusion engine. We have restructured architectures including Text Encoder, UNet, VAE, among others, maintaining compatibility with models from the open-source community while enhancing computational performance. We provide many interesting features. Enjoy the magic of Diffusion models!
Until now, DiffSynth Studio has supported the following models:
- ExVideo
- Stable Video Diffusion
- Hunyuan-DiT
- RIFE
- ESRGAN
- Ip-Adapter
- AnimateDiff
- ControlNet
- Stable Diffusion XL
- Stable Diffusion
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June 21, 2024. 🔥🔥🔥 We propose ExVideo, a post-tuning technique aimed at enhancing the capability of video generation models. We have extended Stable Video Diffusion to achieve the generation of long videos up to 128 frames.
- Project Page
- Source code is released in this repo. See
examples/ExVideo
. - Models are released on HuggingFace and ModelScope.
- Technical report is released on arXiv.
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June 13, 2024. DiffSynth Studio is transferred to ModelScope. The developers have transitioned from "I" to "we". Of course, I will still participate in development and maintenance.
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Jan 29, 2024. We propose Diffutoon, a fantastic solution for toon shading.
- Project Page
- The source codes are released in this project.
- The technical report (IJCAI 2024) is released on arXiv.
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Dec 8, 2023. We decide to develop a new Project, aiming to release the potential of diffusion models, especially in video synthesis. The development of this project is started.
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Nov 15, 2023. We propose FastBlend, a powerful video deflickering algorithm.
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Oct 1, 2023. We release an early version of this project, namely FastSDXL. A try for building a diffusion engine.
- The source codes are released on GitHub.
- FastSDXL includes a trainable OLSS scheduler for efficiency improvement.
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Aug 29, 2023. We propose DiffSynth, a video synthesis framework.
- Project Page.
- The source codes are released in EasyNLP.
- The technical report (ECML PKDD 2024) is released on arXiv.
git clone https://github.com/modelscope/DiffSynth-Studio.git
cd DiffSynth-Studio
pip install -e .
The Python examples are in examples
. We provide an overview here.
We trained an extended video synthesis model, which can generate 128 frames. examples/ExVideo
github_title.mp4
Generate high-resolution images, by breaking the limitation of diffusion models! examples/image_synthesis
512*512 | 1024*1024 | 2048*2048 | 4096*4096 |
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1024*1024 | 2048*2048 |
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Render realistic videos in a flatten style and enable video editing features. examples/Diffutoon
Diffutoon.mp4
Diffutoon_edit.mp4
Video stylization without video models. examples/diffsynth
winter_stone.mp4
Use Hunyuan-DiT to generate images with Chinese prompts. We also support LoRA fine-tuning of this model. examples/hunyuan_dit
Prompt: 少女手捧鲜花,坐在公园的长椅上,夕阳的余晖洒在少女的脸庞,整个画面充满诗意的美感
1024x1024 | 2048x2048 (highres-fix) |
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Prompt: 一只小狗蹦蹦跳跳,周围是姹紫嫣红的鲜花,远处是山脉
Without LoRA | With LoRA |
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python -m streamlit run DiffSynth_Studio.py