This project is still under development, and not all features have been added yet.
- Developed an advanced Crop Disease Predictor Web App using AI-powered image recognition.
- Implemented a deep learning model - CNN using TensorFlow and Keras for accurate disease identification.
- Built a Flask server backend to handle image uploads and deliver real-time disease predictions.
- Supports identification of various crop diseases across multiple plant species.
- Working on building the managment system for all the crops.
CropVista.mp4
- AI-Powered Disease Detection: Utilizes advanced machine learning algorithms to identify crop diseases from uploaded images.
- Real-Time Predictions: Flask server processes image uploads and provides immediate disease classification results.
- User-Friendly Interface: Intuitive web app design allows easy image upload and clear presentation of results.
- Comprehensive Disease Management: Offers detailed information and treatment recommendations for identified diseases.
- Programming Language: Python
- Machine Learning Libraries: TensorFlow, Keras
- Web Framework: Flask
- Frontend: HTML5, CSS3, JavaScript
- Dataset: Extensive collection of labeled crop disease images for training and validation
- Python Documentation: Python Documentation
- Flask Documentation: Flask Documentation
- Keras Documentation: Keras Documentation
- TensorFlow Documentation: TensorFlow Documentation