Inspiration
Senior citizens find it hard to use phones to order groceries.
What it does
Lets you scan grocery items at home that will be identified by an ML model and parses it directly to the payment and required quantity page.
How we built it
Built a sequential neural network that detects the type of grocery item from its image.
Challenges we ran into
Integration of the web application with the model
Accomplishments that we're proud of
Completed the project within due time.
What we learned
Teamwork, Coordination. This is our first ever machine learning project we attempted and completed successfully.
What's next for Scan Mart - Team 108_Incognito
Scaling the model to identify more variety of grocery items.
Built With
- css
- flask
- html5
- ibmz
- javascript
- jupyter
- keras
- python
- tf
Log in or sign up for Devpost to join the conversation.