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README.md

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+---
+license: mit
+language: en
+library_name: pytorch
+tags:
+- image-classification
+- plant-disease
+- pytorch
+- efficientnet
+datasets:
+- plant-village
+---
+
+# Plant Disease Classification Model
+
+This repository contains a PyTorch model for classifying diseases in various plants. The model is based on a pre-trained EfficientNet-B2 architecture with a custom classifier head.
+
+## Model Details
+
+- **Architecture:** EfficientNet-B2 backbone with a custom attention mechanism and classifier head.
+- **Dataset:** Trained on a subset of the Plant Village dataset.
+- **Classes:** 29 classes, combining plant type and disease.
+- **Input Size:** 224x224 RGB images.
+
+## How to Use
+
+Install the required dependencies:
+```bash
+pip install -r requirements.txt
+```
+
+You can use the `PlantDiseasePredictor` class from the notebook to load the model and make predictions.
+
+```python
+# Save the PlantDiseasePredictor class to a file named predictor.py
+from predictor import PlantDiseasePredictor
+
+# Load the model from the Hub
+predictor = PlantDiseasePredictor.from_hub("Abuzaid01/plant_detector")
+
+# Predict a single image
+results = predictor.predict('path/to/your/image.jpg')
+print(results)
+```