brief
FramePack is an open sourceAI Video Generation Tool, developed by the lllyasviel team, focuses on video diffusion techniques becoming really practical. This project has received 8.7k starred and 536 forks on GitHub, showing its popularity in the AI video generation space. The most important thing is that it makes the threshold of AI video generation lower, so that novices and newbies can also use it on less configured devices!
Key Features
- Next Generation Frame Prediction: FramePack utilizes an innovative "next frame (next segment) prediction" neural network architecture to generate video content incrementally.
- Efficient Context Compression: By compressing the input context to a fixed length, the generation workload is made independent of the video length, which greatly improves the processing efficiency.
- low resource requirement::
- Handles a large number of frames even on laptop GPUs
- Generates 1 minute of video at 30fps (1800 fps) with only 6GB of video memory
- Training can be done with batch sizes similar to image diffusion training
- Intuitive GUI interface: Provides a Gradio-based graphical interface that allows users to upload images and enter prompt words to generate videos.
Technical characteristics
FramePack's most distinguishing feature is that it makes "video diffusion feel as simple as image diffusion". Through innovative architectural design, it solves several key challenges faced by traditional video generation models:
- Memory efficiency: Significantly lower graphics memory requirements compared to traditional methods
- Generation length: supports the generation of high-quality videos up to several minutes in length
- Real-time preview: Adopt frame-by-frame/segment-by-segment generation, users can see the progress of generation in real time.
Fits the crowd
FramePack is suitable for the following categories of users:
- AI video generation researcher: Video generation algorithms can be researched and improved based on this project.
- content creator: AI assistance for the creation of short videos, animations, etc.
- developers: Technicians who want to integrate video generation capabilities into their applications
- AI enthusiasts: Individual users interested in the latest AI video technology
Experience
FramePack's performance on different hardware according to the project description:
- RTX 4090 desktop: 1.5-2.5 sec/frame
- Laptop GPUs (e.g. 3070ti/3060): 4-8 times slower
The project provides a number of example videos that demonstrate the ability to generate various dynamic scenes such as dancing, skateboarding, writing, etc. from static images. Particularly noteworthy is its ability to maintain the coherence and naturalness of movements over long periods of time.
Installation and use
FramePack supports Windows and Linux systems:
Windows user::
- Download one-click installer (CUDA 12.6 + Pytorch 2.6)
- Unzip and run update.bat to update the
- Starting the program with run.bat
Linux user::
- Requires Python 3.10 environment
- Install dependencies via pip
- Run demo_gradio.py to start the GUI
caveat
Special reminder for project authors:
- This is the only official GitHub repository, all other similar sites are fake!
- It is recommended to run sanity check in its entirety first to ensure that the hardware and software are working properly.
summarize
FramePack represents an important advancement in video generation technology, addressing the limitations of traditional methods in terms of memory efficiency and generation length through an innovative architectural design. It is a tool well worth trying for users who want to explore the possibilities of AI video generation.
Official website link:FramePack GitHub Repository
byword
AI video generation, FramePack, next frame prediction, video diffusion modeling, open source AI tools, low graphics memory video generation
