APT4900-A Applied Computer Technology Project for Spring Semester 2022. Using machine learning to detect diseases in tomato crops from pictures of their leaves.
A user is able to:
- Sign up if they are a new user
- Sign in
- Select a photo from their gallery
- Take a photo with their camera
- Get results of scanned photo
- Edit their account details
An administrator is able to
- Sign in
- View and delete users
- View some statistics on a dashboard
- Generate a report on most frequently detected diseases
- How to create a convolutional neural network that uses computer vision to detect tomato diseases
- How to integrate a machine learning model with a Flutter application
- CRUD operations on Firebase Firestore database
- Asynchronous functions in Flutter
- Jeff Shelton Okang'a was instrumental in documenting the project
- The data used to train the model was obtained from Kaggle
- Photo and icon credits to depositphotos and flaticon
- I used a model by Animesh1911
- The design and fucntionality of the application was derived from root458's project
This project is licensed under the MIT license - see the LICENSE.md for details.