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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 …

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Welcome to Crop AI 👋

Version Twitter: NeelanjanManna

[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.

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

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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 …

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