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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.

Kotlin 1.84% Swift 5.62% Objective-C 0.53% Dart 92.02%
dart flutter image-classification

crop-ai-frontend's Introduction

Neelanjan Manna is a Software Engineer at Harness. He is a maintainer of the CNCF LitmusChaos project, a chaos engineering orchestration framework for validating the resiliency of cloud-native environments. He contributes to the development of emerging technologies including chaos engineering, distributed applications, and Kubernetes applications at Harness.


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Go         19 hrs 36 mins  ████████████████████▒░░░░   81.18 %
Rust       3 hrs 22 mins   ███▒░░░░░░░░░░░░░░░░░░░░░   13.94 %
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