Update README.md

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IDGallagher
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1. `IG_MotionVideoSearch`: Takes an image input and returns the top 5 ranked URLs from the FAISS index.
2. `IG_MotionVideoFrame`: Converts 24 consecutive frames into a single “dot frame,” which encodes motion features in a color-coded image.
## ComfyUI
We have some ComfyUI nodes ready to be used with a pre-existing video database consisting of roughly 100,000 videos. You can get started using the following workflow:
[MotionSearch](workflows/MotionSearch.json)
## Installation
### 1. Set Up Environment
@@ -137,28 +141,6 @@ If you want to use the motion search in [ComfyUI](https://github.com/comfyanonym
- **IG_MotionVideoSearch**: Takes an image and returns URLs + ranks.
- **IG_MotionVideoFrame**: Takes a stack of 24 frames and returns a single “dot frame.”
## Repository Structure
```
├─ checkpoints/ # Checkpoints for the DOT motion model
├─ configs/ # Model configuration files
├─ data/ # Default location for data.sqlite & index.faiss
│ ├─ datasets/
│ └─ temp/
├─ debug/ # Debug output (if enabled)
├─ dot/ # DOT model code and configs
├─ videos/ # Example video files (not in repo by default)
├─ WatermarkRemoval/ # Optional submodule for removing watermarks
├─ database.py # Database interactions (SQLite)
├─ dot_functions.py # DOT model logic (motion extraction)
├─ functions.py # Core logic for storing and handling frames
├─ main.py # CLI entry point (Typer)
├─ nodes.py # ComfyUI node definitions
├─ pyproject.toml # Project metadata
├─ README.md # This README
└─ requirements.txt # Dependencies (for pip)
```
## Contributing
Contributions and suggestions are welcome! Feel free to open issues or pull requests for enhancements or bug fixes.