Whyâť“:
I made this project for my SAE, a rigorous, Supervised Agricultural Experience. To learn more about SAE’s, go here.
How⚙️:
This project utilizes Google Teachable Machine, a free, light weight, embeddable image classification model, to classify a tomato as either ripe or not ripe. I used a combination of 2 datasets for this project: TomatoD and LaboroTomato. Like both of the prior, this project is licensed under CC BY-NC-SA 4.0.
When📆:
This project was created on XX XXXX 2026
More✨:
Tomato Tester was tested to have an accuracy of 92% as shown in the accuracy matrix below. Also, to view this project on Github, go here.
