Update README.md

README.md

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----
-license: mit
----
+---
+license: mit
+base_model:
+- google/efficientnet-b0
+pipeline_tag: image-classification
+tags:
+- biology
+- medical
+---
+# Eye Disease Model
+
+**Model Information:**
+- **Architecture:** EfficientNet-B0
+- **Task:** Multi-class classification (4 diseases)
+- **Dataset:** [Eye Disease Dataset](https://www.kaggle.com/datasets/gunavenkatdoddi/eye-diseases-classification)
+- **Input Size:** 224×224 RGB images
+
+**Classes:**
+1. Cataract
+2. Diabetic Retinopathy
+3. Glaucoma
+4. Normal
+
+**Performance Metrics:**
+- **Accuracy:** 95%
+- **Precision:** 0.95
+- **Recall:** 0.9555
+- **F1-Score:** 0.95
+
+**Usage:**
+```python
+from shifaa.vision import VisionModelFactory
+
+model = VisionModelFactory.create_model(
+    model_type="classification",
+    model_name="Eye_Disease"
+)
+
+result = model.run("eye_image.jpg", show_image=True)
+print(f"Disease: {result['predicted_class']}")
+print(f"Confidence: {result['confidence']:.2f}%")
+```
+
+**Confusion Matrix:**
+
+![Confusion Matrix](./ED_CM.png)
+
+
+**Preprocessing:**
+- Resize to 224×224
+- Convert to tensor
+- ImageNet normalization
+
+**Training Details:**
+- **Loss Function:** CrossEntropyLoss
+- **Optimizer:** Adam (lr=0.0001)
+- **Scheduler:** ReduceLROnPlateau (factor=0.5, patience=3)
+
+---