🩺 Dr. Disease (MobileNetV2)
Dr. Disease is a lightweight, offline-capable image classification model designed to detect crop diseases on mobile devices. It is the core AI engine of the AgroTech Ecosystem.
🌾 Model Details
- Architecture: MobileNetV2 (Transfer Learning)
- Framework: TensorFlow / Keras
- Input Resolution: 224x224 pixels
- Target Platform: Android/iOS (via TensorFlow Lite)
- License: Apache 2.0
🎯 Intended Use
- Primary Use Case: Real-time diagnosis of crop diseases (e.g., Tomato Early Blight, Potato Late Blight) from leaf photos.
- Users: Farmers and agricultural extension workers in low-bandwidth regions.
📊 Performance
- Dataset: Trained on the PlantVillage Dataset.
- Goal Accuracy: >90% on validation set.
- Latency: Optimized for <200ms inference time on standard smartphones.
⚠️ Limitations
- Lighting conditions significantly affect accuracy.
- Currently limited to 10 common crop diseases (list to be updated).
Part of the AgroTech Project.
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