inventorado7
f2fc83e72a
Add GROUT segmentation nodes for mosaic grout line detection: - GROUTSegmentation: Main segmentation node with scale and sliding window modes - GROUTThreshold: Threshold adjustment without re-running inference - GROUTHeatmapColorize: Colormap visualization for probability heatmaps Features: - Auto-download model from HuggingFace - Scale mode: resize to 512x512 for inference - Sliding window mode: process large images with overlapping patches - Configurable patch size and overlap settings
110 lines
3.1 KiB
Markdown
110 lines
3.1 KiB
Markdown
# ComfyUI-GROUT
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Custom ComfyUI nodes for **GROUT** (Geometric Reasoning Over Unstructured Tessellations) - a deep learning model for detecting and segmenting grout lines in mosaic images.
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## Nodes
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### GROUT Segmentation
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Main segmentation node that processes mosaic images.
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**Inputs:**
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- `image`: Input mosaic image
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- `device`: Select CUDA or CPU for inference
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- `threshold`: Initial threshold for binary mask (0.0 - 1.0)
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- `model_path` (optional): Custom path to model weights. Leave empty to auto-download from HuggingFace.
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**Outputs:**
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- `probability_heatmap`: Grayscale probability map (0-1 range)
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- `binary_mask`: Thresholded binary mask as image
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- `mask`: ComfyUI MASK format for compositing
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### GROUT Threshold
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Post-processing node to adjust threshold without re-running inference.
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**Inputs:**
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- `probability_heatmap`: Output from GROUT Segmentation node
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- `threshold`: Threshold value (0.0 - 1.0)
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**Outputs:**
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- `binary_mask`: Thresholded binary mask as image
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- `mask`: ComfyUI MASK format
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### GROUT Heatmap Colorize
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Visualization node to apply colormap to probability heatmap.
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**Inputs:**
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- `probability_heatmap`: Output from GROUT Segmentation node
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- `colormap`: Select from magma, viridis, plasma, inferno, hot, jet
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**Outputs:**
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- `colored_heatmap`: Colorized visualization
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## Installation
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### Option 1: ComfyUI Manager
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Search for "GROUT" in ComfyUI Manager and install.
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### Option 2: Manual Installation
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1. Navigate to your ComfyUI custom nodes folder:
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```bash
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cd ComfyUI/custom_nodes/
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```
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2. Clone this repository:
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```bash
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git clone https://github.com/advancedtech-sk/ComfyUI-GROUT.git
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```
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3. Install dependencies:
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```bash
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cd ComfyUI-GROUT
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pip install -r requirements.txt
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```
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**For standalone Windows version** (portable/embedded Python):
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```bash
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cd ComfyUI-GROUT
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..\..\..\python_embeded\python.exe -m pip install -r requirements.txt
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```
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4. Restart ComfyUI
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## Model Download
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The model will be automatically downloaded from HuggingFace on first use. It will be saved to:
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```
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ComfyUI/models/grout/grout_b3_zeroshot_v1.pth
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```
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Alternatively, you can manually download from:
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- [HuggingFace Model](https://huggingface.co/advancedtech-sk/GROUT)
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## Example Workflow
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```
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[Load Image] -> [GROUT Segmentation] -> [probability_heatmap] -> [GROUT Threshold] -> [binary_mask]
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+-> [GROUT Heatmap Colorize] -> [Preview Image]
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```
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**Workflow Tips:**
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1. Use **GROUT Segmentation** to run inference once
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2. Connect the `probability_heatmap` output to **GROUT Threshold**
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3. Adjust the threshold slider in GROUT Threshold to tune the mask without re-running the model
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4. Use **GROUT Heatmap Colorize** for visualization with different colormaps
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## Links
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- [GROUT Paper (Zenodo)](https://zenodo.org/records/18187265)
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- [GROUT Model (HuggingFace)](https://huggingface.co/advancedtech-sk/GROUT)
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- [GROUT Demo (HuggingFace Spaces)](https://huggingface.co/spaces/advancedtech-sk/GROUT)
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- [GROUT GitHub](https://github.com/advancedtech-sk/GROUT)
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## License
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MIT License
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## Author
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Radoslav Lovecky, Institute of Advanced Technologies, Slovakia
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