This project is a Flask-based API for detecting plant diseases (Healthy, Powdery Mildew, Rust) using a deep learning model. The model is trained on an image dataset and deployed with an endpoint to classify uploaded images.
- Dataset: The dataset was obtained from Kaggle (View Dataset).
- Data Preparation: Organized into
train
,test
, andvalidation
folders. - Model Training: A convolutional neural network (CNN) was trained using TensorFlow/Keras to classify plant disease images.
- API Development: A Flask API was created to handle image uploads and return predictions.
- Frontend Integration: The API is connected to an Expo (React Native) app for users to upload images and receive disease diagnosis.
- Future Plans: Integration with Gemini AI to provide treatment instructions.