Update README.md

README.md

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----
-license: mit
----
+---
+license: mit
+datasets:
+- dhvazquez/mtg_synthetic_cards_semantic_segmentation
+language:
+- en
+---
+# Magic The Gatering Image Semantic Segmentation model.
+
+## Model Details
+- Architecture: lraspp_mobilenet_v3_large
+- Input Size: 320x240
+- Number of Classes: 2
+- Classes: Background (0), Card (1)
+
+## Model Files
+- `card_segmentation.onnx`: ONNX format for cross-platform deployment
+- `card_segmentation.pt`: TorchScript format for PyTorch deployment
+- `card_segmentation_state_dict.pth`: PyTorch state dict for training/fine-tuning
+
+## Input/Output
+- Input: RGB image tensor of shape (1, 3, 320, 240)
+- Input normalization: mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]
+- Output: Segmentation logits of shape (1, 2, 320, 240)
+
+## Usage
+See `inference_example.py` for example usage.
+
+## Requirements
+- PyTorch >= 1.9.0
+- torchvision >= 0.10.0
+- onnxruntime (for ONNX inference)
+- opencv-python
+- numpy
+- Pillow
+
+## Aditional Information
+
+[Demo](https://huggingface.co/spaces/dhvazquez/mtg_semantic_segmentation)  
+[Dataset](https://huggingface.co/datasets/dhvazquez/mtg_synthetic_cards_semantic_segmentation)  
+[Source Code](https://github.com/diegovazquez/mtg_card_image_segmentation)  
+