NormalCrafter: Learning Temporally Consistent Video Normal from Video Diffusion Priors
🔆 Notice
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🔆 Introduction
🤗 If you find NormalCrafter useful, please help ⭐ this repo, which is important to Open-Source projects. Thanks!
🔥 NormalCrafter can generate temporally consistent normal sequences with fine-grained details from open-world videos with arbitrary lengths.
[24-04-01]🔥🔥🔥 NormalCrafter is released now, have fun!
🚀 Quick Start
🤖 Gradio Demo
- Online demo: NormalCrafter
- Local demo:
🛠️ Installation
- Clone this repo:
git clone git@github.com:Binyr/NormalCrafter.git
- Install dependencies (please refer to requirements.txt):
pip install -r requirements.txt
🤗 Model Zoo
NormalCrafter is available in the Hugging Face Model Hub.
🏃♂️ Inference
1. High-resolution inference, requires a GPU with ~20GB memory for 1024x576 resolution:
python run.py --video-path examples/example_01.mp4
2. Low-resolution inference requires a GPU with ~6GB memory for 512x256 resolution:
python run.py --video-path examples/example_01.mp4 --max-res 512