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README.md

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-license: other
-license_name: synspill-dataset-license
-license_link: https://github.com/eternal-f1ame/SynSpill/blob/main/LICENSE.md
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+# Data Directory
+
+This directory contains datasets and annotations for the SynSpill project.
+
+## Structure
+
+- `synthetic/` - Generated synthetic spill images and annotations
+- `real/` - Real-world industrial CCTV footage (test set)
+- `annotations/` - Ground truth labels and bounding boxes
+
+## Synthetic Data
+
+The synthetic dataset is generated using our AnomalInfusion pipeline:
+
+- Stable Diffusion XL for base image generation
+- IP adapters for style conditioning
+- Inpainting for precise spill placement
+
+## Citation
+
+If you use this data in your research, please cite our ICCV 2025 paper.
+=======
+# SynSpill Data Directory
+
+This directory contains datasets, annotations, and workflow configurations for the SynSpill project - a comprehensive dataset for industrial spill detection and synthesis.
+
+## Directory Structure
+
+```text
+data/
+├── README.md                    # This file
+├── generation_workflow.json    # ComfyUI workflow for synthetic image generation
+├── inpainting_workflow.json    # ComfyUI workflow for inpainting operations
+├── release/                     # Full dataset release
+│   ├── annotation_masks/        # Binary masks for spill regions (PNG format)
+│   ├── annotations/             # Ground truth annotations and metadata
+│   └── generated_images/        # Complete set of synthetic spill images
+└── samples/                     # Sample data for preview and testing
+    ├── annotation_masks/        # Sample binary masks
+    ├── generated_images/        # Sample synthetic images
+    └── inpainted_images/        # Sample inpainted results
+```
+
+## Dataset Contents
+
+### Release Dataset (`release/`)
+
+- **Generated Images**: High-quality synthetic industrial spill scenarios
+- **Annotation Masks**: Pixel-perfect binary masks identifying spill regions
+- **Annotations**: Structured metadata including bounding boxes, class labels, and scene descriptions
+
+### Sample Dataset (`samples/`)
+
+A subset of the full dataset for quick evaluation and testing purposes, containing:
+
+- Representative examples from each category
+- Various spill types and industrial environments
+- Both generated and inpainted image samples
+
+### Workflow Configurations
+
+- **`generation_workflow.json`**: ComfyUI workflow for generating base synthetic images using Stable Diffusion XL
+- **`inpainting_workflow.json`**: ComfyUI workflow for precise spill placement and inpainting operations
+
+## Synthetic Data Generation
+
+The synthetic dataset is created using our AnomalInfusion pipeline:
+
+1. **Base Generation**: Stable Diffusion XL creates industrial environment images
+2. **Style Conditioning**: IP adapters ensure consistent visual style across scenes
+3. **Spill Synthesis**: Controlled inpainting places realistic spills in specified locations
+4. **Mask Generation**: Automated creation of precise segmentation masks
+
+## Usage
+
+The data is organized for direct use with computer vision frameworks:
+
+- Images are in standard formats (PNG/JPG)
+- Masks are binary images (0 = background, 255 = spill)
+- Annotations follow standard object detection formats
+
+## Citation
+
+If you use this dataset in your research, please cite our ICCV 2025 paper:
+
+```bibtex
+@inproceedings{baranwal2025synspill,
+    title={SynSpill: Improved Industrial Spill Detection With Synthetic Data},
+    author={Baranwal, Aaditya and Bhatia, Guneet and Mueez, Abdul and Voelker, Jason and Vyas, Shruti},
+    booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision - Workshops (ICCV-W)},
+    year={2025}
+}
+```
+
+## License
+
+Please refer to the `LICENSE.md` file in the root directory for licensing information.
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