We were inspired first by the excitement shown over crisp, delicious apples. To help preserve those apples, they hype around them, and answer the question provided to us by Agritech, we decided on PlantMD.

What it does

You provide us with either your symptoms, or a picture of your plant, and we provide you with information and solutions.

How I built it

We used an ML model trained on 87,000 leaf images for image recognition, and we provide fields for customizable input in order to determine what disease(s) you are presenting to us. We then check our database of web-scraped info to determine solutions for you, and point to you external products known to be helpful in solving your issue.

Challenges I ran into

Introducing ourselves to new frameworks for development (Fast API, React) and uploading images to google cloud storage to use on google vision AI were some of the most difficult challenges we ran into.

Accomplishments that I'm proud of

We accomplished most of what we set out to do, and our UI is minimalistic and cleaned up from the start!

What I learned

We learned how to incorporate CV and an ML model into a front end application.

What's next for PlantMD

We hope to broaden the knowledge of our model, and increase the data we have for plant diseases to account for more crops!

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