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https://github.com/neelanjan00/crop-ai-frontend

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.
https://github.com/neelanjan00/crop-ai-frontend

dart flutter image-classification

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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 with a Flutter based frontend mobile application to interact with the REST API.

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Welcome to Crop AI 👋



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Twitter: NeelanjanManna

> [This is the frontend mobile application of the project, the backend 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](https://github.com/neelanjan00/Crop-AI)

## Author

👤 **Neelanjan Manna**

* Website: https://neelanjanmanna.ml/
* Twitter: [@NeelanjanManna](https://twitter.com/NeelanjanManna)
* Github: [@neelanjan00](https://github.com/neelanjan00)
* LinkedIn: [@neelanjan00](https://linkedin.com/in/neelanjan00)

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