Leaf Buster AI

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  Landing page

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  Leaf disease detector

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  Leaf disease detector results

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  Trivia Game

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  About us page

Inspiration

Our goal as a team was to make a project that contributes to Farm Food Future Innovation. This project has the potential to help apple farmers quickly identify and treat diseased apples, improving crop yield and reducing waste.

What it does

Leaf Buster AI aims to differentiate between two apple leaf diseases, rot and blotch, using image recognition technology. The project involves training an AI model using a dataset of images of apple rot leaves, and leaf blotch. The trained model can then analyze new images of apple leaves and accurately classify them as healthy, rot, or blotched.

How we built it

Through the utilization of image recognition techniques with machine learning, we were able to identify leaf blotch. To accomplish this, we employed a dataset obtained from Kaggle, consisting of images depicting both healthy leaves and leaves affected by leaf blotch. Our approach involved using machine learning algorithms to train an AI model to recognize the visual patterns associated with leaf blotch. The model was taught to differentiate between healthy leaves and leaves affected by leaf blotch based on features such as the color, shape of the spots, size, distribution of the lesions, and other characteristics. Upon completion of the training process, the trained model can be used to automatically detect leaf blotch. This can be achieved via a computer vision system that examines images of plant leaves captured by a camera and delivers a diagnosis of leaf blotch based on its analysis.

Challenges we ran into

Some challenges we ran into were finding the correct dataset to use when training our model, actually training the model, and displaying the corresponding labels to the images parsing the response from the machine-learning model.

Accomplishments that we're proud of

We are proud that we managed to create a working solution that returns actual results in such a limited timeframe. On top of that, we are proud of our minimalist UI design.

What we learned

We learned about machine learning, image detection, as well as honing our skills in front-end development with REACT.js and Figma for the UI/UX.

What's next for Leaf Buster AI

We wanted to implement a trivia game but did not have enough time. We could also train the model more on various types of diseases. Once we complete those tasks, we look forward to deploying our application.

Built With

• css
• figma
• html
• javascript
• kaggle
• pytorch
• react.js
• yolo