Banana Disease Classification
__Overview:__ This machine learning-based system detects and classifies common banana plant diseases from images. It is designed for use in agricultural environments to assist farmers and researchers with early and accurate diagnosis of banana diseases using an embedded, portable solution.
### 🧱 Tech Stack
- **Frontend:** - **PyQt** – Used to develop a desktop-based GUI for image input, classification results, and user interaction. - **Machine Learning:** - **TensorFlow (MobileNetV2)** – Lightweight convolutional neural network used to classify banana leaf diseases from images with high accuracy. - **Processing Unit:** - **Raspberry Pi 4** – Performs real-time image classification using the trained MobileNetV2 model. - **Hardware Integration:** - **Raspberry Pi Camera V2** – Captures leaf images for disease detection. - **Blender** – Used for designing and developing the physical casing of the device for field deployment. - **Targeted Diseases:** - Sigatoka - Bacterial Wilt - Bunchy Top - Panama Disease