Welcome to the Plant Disease Recognition System! This project is designed to help farmers and agricultural experts easily identify plant diseases using state-of-the-art deep learning models.
- Accurate Predictions: Utilizes a TensorFlow model for high-precision disease recognition.
- User-Friendly Interface: Built with Streamlit, offering an intuitive and simple user experience.
- Instant Analysis: Upload an image, and receive immediate feedback on the health status of your plant.
- Introduction to the system.
- Steps on how to use the application.
- Insights on why our system is beneficial.
- Upload an image of your plant.
- Get predictions on whether your plant is healthy or affected by a disease.
- View the specific disease and receive recommendations.
- Information on the dataset used for training the model.
- Dataset structure details.
The dataset used in this project contains approximately 87,000 images of healthy and diseased crop leaves, classified into 38 categories. It is split into training, validation, and test sets:
- trainingSet: "70,295 images",
- validationSet: "17,572 images",
- testSet: "33 images".