A plant disease detection, shopping, and community app for farmers, gardeners, and plant enthusiasts.
- Simple, clean, and easy app interface 👍
- Email-password and Google authentication
- Plant disease detection through leaf scanning (currently supports Tomato, Potato, Corn)
- Assistance via phone call or WhatsApp for farming and gardening support
- Weather updates including temperature and sky status
- Latest trends and news in the agriculture sector
- Fully functional marketplace for seeds, pesticides, irrigation supplies, indoor plants, gardening tools, fertilizers, etc., with cart, ordering, and payment integration via SSL Commerz
- Minimal social features including posting, liking, and commenting
- Profile page with user information display, edit profile functionality, profile picture upload, and view user's orders
FlutterFire
- Ensure to login to Firebase from CLI
- Use FlutterFire to connect to Firebase (generates a Dart file - without it the app won't run)
- Firebase
Auth
for authentication - Firebase
CloudStore
for database - Firebase
Storage
for storage service OpenWeather
API for weather informationAgro Care Flask
API for plant disease detection: agro-care-flask- Run the Flask app locally or host it
- Set the prediction API link to the Firebase CloudStore
- Run the app and scan any leaf
- Note: Without starting the server, the detection won't work. Currently, the server is hosted locally, so detection might not work.
Flutter
v3.16.9 or higher (The project was developed onv3.16.9
)
- Clone the repository:
git clone https://github.com/codernayeem/agro-care-app.git
- Navigate to the project directory:
cd agro-care-app
- Install dependencies:
flutter pub get
- Configure FlutterFire:
flutterfire configure
- Run the app:
flutter run
- Download the latest release from GitHub Releases
- Install the APK on your device (As the app is not uploaded to the Play Store, you might get a warning. You can safely ingore that.)
- Open the app and explore its features
- Regarding The Disease Detection through leaf scanning
- The server for detection api is not hosted in remote server yet.
- Since, the detection server agro-care-flask can be hosted locally, the local api needs to be set in the cloudstore everytime it changes.
- Currently, the api saved in cloud store is
http://192.168.0.103:4000/predict
- You can run the server locally on that local IP address & port. Then, the detection in app should work fine.
- Currently, the model is not that robust yet, as the dataset was not that versatile. It is just for testing purpose of the pipeline.
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Various images, news information, marketplace details, and disease descriptions used in the app were sourced from the internet for educational purposes only.