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Repo 2 of AushadHub, a FlaskApp with HTML, CSS and Javascript as FrontEnd. This is client side FrontEnd which posts the Image input to endpoint of FlaskApp hosted on google cloud for preprocessing and Inferencing.

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AusafMo/AushadHubFrontEnd

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AushadHubFrontEnd

🙋‍♂️ It takes a hot minute (1~2 mins) to load the site, why ? well, render drops all the resources after 15 mins of no incoming traffic. And, I am quite sure you're probably the first one visiting the site in weeks ( well, technically i do stare into this void of a site every morning, don't ask me why ) .

The Front-End is entirely designed and implemented by Abhinav, check him out @abhinav0git


This Project is divided across three repositories, This repo deals with the Frontend App

What is this? :

  • The Project aims to solve the problem of identification of medicinal herbs.
  • The Machine Learning Model uses ResNet, with a validation accuracy of 98% and testing accuracy of 96%.
  • The training and testing dataset contains over 1500 images across 30 medicinal herb species.

Tech Stack Used for this:

  • Python 3
  • Flask
  • Pillow
  • HTML
  • CSS
  • JavaScript
  • GitHub

In Action :

Old Site design, but you get the Idea.

FrontEndDemo.mp4

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Repo 2 of AushadHub, a FlaskApp with HTML, CSS and Javascript as FrontEnd. This is client side FrontEnd which posts the Image input to endpoint of FlaskApp hosted on google cloud for preprocessing and Inferencing.

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