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modelscope/DiffSynth-Studio

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license: Apache-2.0

Language: Python .

Enjoy the magic of Diffusion models!

最后发布版本: v1.0.0 ( 2024-07-29 20:22:56)

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DiffSynth Studio

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modelscope%2FDiffSynth-Studio | Trendshift

Document: https://diffsynth-studio.readthedocs.io/zh-cn/latest/index.html

Introduction

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:

News

  • October 25, 2024 We provide extensive FLUX ControlNet support. This project supports many different ControlNet models that can be freely combined, even if their structures differ. Additionally, ControlNet models are compatible with high-resolution refinement and partition control techniques, enabling very powerful controllable image generation. See ./examples/ControlNet/.

  • October 8, 2024. We release the extended LoRA based on CogVideoX-5B and ExVideo. You can download this model from ModelScope or HuggingFace.

  • August 22, 2024. CogVideoX-5B is supported in this project. See here. We provide several interesting features for this text-to-video model, including

    • Text to video
    • Video editing
    • Self-upscaling
    • Video interpolation
  • August 22, 2024. We have implemented an interesting painter that supports all text-to-image models. Now you can create stunning images using the painter, with assistance from AI!

  • August 21, 2024. FLUX is supported in DiffSynth-Studio.

    • Enable CFG and highres-fix to improve visual quality. See here
    • LoRA, ControlNet, and additional models will be available soon.
  • 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.

  • 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.

  • 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.
  • 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.

  • Nov 15, 2023. We propose FastBlend, a powerful video deflickering algorithm.

  • 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.
      • The original repo of OLSS is here.
      • The technical report (CIKM 2023) is released on arXiv.
      • A demo video is shown on Bilibili.
      • Since OLSS requires additional training, we don't implement it in this project.
  • Aug 29, 2023. We propose DiffSynth, a video synthesis framework.

Installation

Install from source code (recommended):

git clone https://github.com/modelscope/DiffSynth-Studio.git
cd DiffSynth-Studio
pip install -e .

Or install from pypi:

pip install diffsynth

Usage (in Python code)

The Python examples are in examples. We provide an overview here.

Download Models

Download the pre-set models. Model IDs can be found in config file.

from diffsynth import download_models

download_models(["FLUX.1-dev", "Kolors"])

Download your own models.

from diffsynth.models.downloader import download_from_huggingface, download_from_modelscope

# From Modelscope (recommended)
download_from_modelscope("Kwai-Kolors/Kolors", "vae/diffusion_pytorch_model.fp16.bin", "models/kolors/Kolors/vae")
# From Huggingface
download_from_huggingface("Kwai-Kolors/Kolors", "vae/diffusion_pytorch_model.fp16.safetensors", "models/kolors/Kolors/vae")

Video Synthesis

Text-to-video using CogVideoX-5B

CogVideoX-5B is released by ZhiPu. We provide an improved pipeline, supporting text-to-video, video editing, self-upscaling and video interpolation. examples/video_synthesis

The video on the left is generated using the original text-to-video pipeline, while the video on the right is the result after editing and frame interpolation.

https://github.com/user-attachments/assets/26b044c1-4a60-44a4-842f-627ff289d006

Long Video Synthesis

We trained extended video synthesis models, which can generate 128 frames. examples/ExVideo

https://github.com/modelscope/DiffSynth-Studio/assets/35051019/d97f6aa9-8064-4b5b-9d49-ed6001bb9acc

https://github.com/user-attachments/assets/321ee04b-8c17-479e-8a95-8cbcf21f8d7e

Toon Shading

Render realistic videos in a flatten style and enable video editing features. examples/Diffutoon

https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/b54c05c5-d747-4709-be5e-b39af82404dd

https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/20528af5-5100-474a-8cdc-440b9efdd86c

Video Stylization

Video stylization without video models. examples/diffsynth

https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/59fb2f7b-8de0-4481-b79f-0c3a7361a1ea

Image Synthesis

Generate high-resolution images, by breaking the limitation of diffusion models! examples/image_synthesis.

LoRA fine-tuning is supported in examples/train.

FLUX Stable Diffusion 3
image_1024_cfg image_1024
Kolors Hunyuan-DiT
image_1024 image_1024
Stable Diffusion Stable Diffusion XL
1024 1024

Usage (in WebUI)

Create stunning images using the painter, with assistance from AI!

https://github.com/user-attachments/assets/95265d21-cdd6-4125-a7cb-9fbcf6ceb7b0

This video is not rendered in real-time.

Before launching the WebUI, please download models to the folder ./models. See here.

  • Gradio version
pip install gradio
python apps/gradio/DiffSynth_Studio.py

20240822102002

  • Streamlit version
pip install streamlit streamlit-drawable-canvas
python -m streamlit run apps/streamlit/DiffSynth_Studio.py

https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/93085557-73f3-4eee-a205-9829591ef954

最近版本更新:(数据更新于 2024-09-09 08:31:14)

2024-07-29 20:22:56 v1.0.0

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