FlashVideo: Efficient High-Resolution Video Generation with Flowing Fidelity
Summary
FlashVideo is an innovative GitHub repository that introduces a novel approach for efficient high-resolution video generation. It leverages a two-stage diffusion model to produce detailed videos, scaling from 270p to 1080p. This project focuses on maintaining fidelity to detail while significantly improving the efficiency of the video generation process.
Repository Info
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Introduction
FlashVideo, from FoundationVision, presents a cutting-edge solution for efficient high-resolution video generation. This project, titled "Flowing Fidelity to Detail for Efficient High-Resolution Video Generation," utilizes advanced diffusion models to create detailed videos, starting from text prompts. It employs a unique two-stage process, first generating 270p videos and then enhancing them to stunning 1080p resolution, all while prioritizing computational efficiency.
Installation
To get started with FlashVideo, follow these steps to set up your environment and download the necessary model checkpoints.
Environment Setup
This repository is tested with PyTorch 2.4.0+cu121 and Python 3.11.11. Install the required dependencies using pip:
pip install -r requirements.txt
Preparing the Checkpoints
Download the 3D VAE (identical to CogVideoX), Stage-I, and Stage-II weights. Navigate to the FlashVideo directory and use huggingface-cli to download them:
cd FlashVideo
mkdir -p ./checkpoints
huggingface-cli download --local-dir ./checkpoints FoundationVision/FlashVideo
Ensure your checkpoints are organized as follows:
??? 3d-vae.pt
??? stage1.pt
??? stage2.pt
Examples
FlashVideo offers flexible ways to generate videos from text prompts. It's important to note that both Stage-I and Stage-II models are trained with long, comprehensive prompts for best results.
Jupyter Notebook
You can conveniently provide user prompts and generate videos using the provided Jupyter notebook:
flashvideo/demo.ipynb
For GPUs with less memory, consider increasing the spatial and temporal slice configuration in the VAE Decoder.
Inferring from a Text File
For generating videos with multiple GPUs or from a text file containing prompts, use the following script:
bash inf_270_1080p.sh
Experience the quality of FlashVideo's output:
Why Use FlashVideo
FlashVideo stands out for its ability to generate high-resolution videos efficiently, maintaining exceptional fidelity to detail. Its two-stage generation process allows for flexible scaling from lower to higher resolutions, making it suitable for various applications. The project is built on robust diffusion models and provides clear instructions for setup and usage, making it accessible for researchers and developers in the generative AI space.
Links
- GitHub Repository: FoundationVision/FlashVideo
- Project Page: More visualizations and examples
- arXiv Paper: FlashVideo: Flowing Fidelity to Detail for Efficient High-Resolution Video Generation