Krishi-Sakha is an AI-powered solution designed to help farmers detect crop diseases early and receive preventive guidance based on weather conditions. The project consists of a mobile application and a backend service integrated with TensorFlow models for real-time disease prediction and multilingual support in 11 regional languages.
- Real-Time Disease Detection: Upload crop images to receive instant disease diagnosis using an image classification model.
- Weather-Driven Alerts: Provides preventive advice based on local weather data to help farmers take proactive measures.
- Multilingual Audio Support: Supports 11 languages with text-to-speech functionality, making the app accessible to farmers with varied language needs.
- User-Friendly Interface: Simple and intuitive design for ease of use by farmers with limited technical knowledge.
- App Repository: Contains the source code for the mobile app built with React Native and Expo.
- Backend Repository: Contains the FastAPI backend and TensorFlow models for disease prediction.
- Frontend (App): React Native with Expo for cross-platform compatibility on Android and iOS devices.
- Backend: FastAPI to handle image processing and disease prediction requests.
- Machine Learning: TensorFlow and Keras for building and training crop disease detection models.
- Google Sheets API: Manages disease information and treatment guidelines in multiple languages.
- Text-to-Speech (TTS): Expo’s TTS library for providing audio guidance in regional languages.
- Clone the app repository:
git clone https://github.com/ImaginedTime/Crop-Disease-Prediction-App.git
- Clone the backend repository:
git clone https://github.com/ImaginedTime/Crop-disease-prediction-backend.git
- Navigate to the backend directory:
cd Crop-disease-prediction-backend - Install the required dependencies:
pip install -r requirements.txt
- Run the FastAPI server:
uvicorn main:app --reload
- Navigate to the app directory:
cd Crop-Disease-Prediction-App - Install the required dependencies:
npm install
- Start the app with Expo:
expo start
- Upload Crop Images: Farmers can upload an image of their crop through the app to receive a diagnosis.
- Receive Disease Information: The app provides disease information and preventive tips based on the prediction.
- Audio Guidance: Text-to-speech functionality provides audio instructions in the selected language.
- Extended Crop Support: Add more crops and diseases to the database.
- Soil-Based Recommendations: Provide crop suggestions based on soil data and weather patterns.
- Offline Mode: Enable the app to function in low-connectivity areas by storing key information offline.
Uday Om SrivastavaKarthik Ragulan
This project is licensed under the MIT License - see the LICENSE file for details.
Feel free to add any other relevant links or details to further enhance the README. Let me know if you'd like more customization!