Crop-AI
A diagnostic AI-enabled mobile app which is able to classify upto 38 different plant diseases ranging for 14 crops and vegetables. The application makes use of the VGG-Net CNN architecture for the purpose of multi-class classification of the images of infected plant leaves. The trained model was then deployed using a Flask backend server, along with a Flutter-based frontend mobile application to interact with the REST API.
[This is the backend API of the project, the frontend mobile application can be found here ] A diagnostic AI-enabled mobile app which is able to classify upto 38 different plant diseases ranging for 14 crops and vegetables. The application makes use of the VGG-Net CNN architecture for the purpose of multi-class classification of the images of infected plant leaves. The trained model was then deployed using a Flask backend server, along with a Flutter based frontend mobile application to interact with the REST API.
🏠 Homepage
Install
pip install -r requirements.txt
Usage
python app.py
API Routes
| Route | Method | Field Name | Input Type | Returns |
|---|---|---|---|---|
/ |
POST | InputImg | Image File (png or jpg or jpeg) | Returns a string bearing the name of the plant disease. |
Author
👤 Neelanjan Manna
- Website: https://neelanjanmanna.ml/
- Twitter: @NeelanjanManna
- Github: @neelanjan00
- LinkedIn: @neelanjan00
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