Update README with model details and usage instructions

README.md

@@ -1,3 +1,65 @@
-# kyc-document-corner-detector
-KYC document segmentation | MobileNetV3-Small | CPU trained
-Dataset: Jwalit/moire-docs | 8 epochs
+# KYC Document Corner Detector
+
+Lightweight document segmentation model trained on KYC documents (Aadhaar, PAN, passports, visas) from the `Jwalit/moire-docs` dataset.
+
+## Model Details
+
+| Property | Value |
+|----------|-------|
+| Architecture | MobileNetV3-Small encoder + upsampling decoder |
+| Task | Binary segmentation (document vs background) |
+| Training | CPU only, 8 epochs |
+| Images | 461 (391 train, 70 val) |
+| **Best Val IoU** | **74.79%** |
+| Model size | ~10 MB |
+| Labels | Self-supervised via OpenCV contour detection |
+
+## How It Works
+
+1. **Input**: Raw KYC document image (any size)
+2. **Segmentation**: Model predicts binary mask of document region
+3. **Corner Detection**: OpenCV contour extraction finds 4 corners from mask
+4. **Perspective Transform**: Crops to document boundaries
+
+## Self-Supervised Label Generation
+
+Labels are generated automatically using classical computer vision:
+- Grayscale → Gaussian blur → Adaptive thresholding
+- Morphological closing connects text regions
+- Largest contour extraction → 4-corner approximation
+
+No manual annotation required.
+
+## Files
+
+| File | Description |
+|------|-------------|
+| `pytorch_model.bin` | Trained model weights |
+| `config.json` | Model configuration |
+| `inference_pipeline.py` | Complete inference script (crop + rotate) |
+| `train_rotation_classifier.py` | Script to train rotation classifier |
+
+## Usage
+
+```python
+import torch
+from inference_pipeline import SegModel, predict_corners
+
+model = SegModel()
+model.load_state_dict(torch.load("pytorch_model.bin", map_location="cpu"))
+corners = predict_corners(model, "your_document.jpg")
+```
+
+## Related Model
+
+- **Rotation Classifier**: https://huggingface.co/Jwalit/kyc-document-rotation-classifier
+  - 4-class classifier: 0°, 90°, 180°, 270°
+  - Run `train_rotation_classifier.py` to train on your CPU
+
+## Pipeline
+
+```
+Raw Image → SegModel → Mask → Contours → 4 Corners → Crop
+                                    ↓
+                              RotModel → Classify Rotation → Correct Orientation
+```