What motivated us the most was the amount of moving parts that the project would require to work, as we found more and more relevant features that we could implement every time we discussed.

What it does

Our app was designed to streamline Autonation's customer experience with an automatic check-in system that reads license plates in real time. Leveraging Google Cloud's Vision API and Twilio's communication platform allowed us to create a safer environment by maintaining social distancing guidelines and remain contactless when creating appointments and checking in.

How I built it

For the license plate recognition we used python OpenVC for computer vision and video parsing and Google Cloud Vision for Image Recognition and OCR (Optical Character Recognition). For the database we implemented a Google Cloud MySQL database and used Flask as the Web Frame Framework. For the web app we used HTML, CSS and JavaScript. For the text message feature we used Twilio.

Challenges I ran into

We had a hard time figuring out how to separate all the text from the pictures from what we would actually need. We also struggled a bit with communicating with Twilio.

Accomplishments that I'm proud of

We are extremely proud of ourselves for being able to read text from an image and being able to detect via code what part of it is actually relevant for the license plate/ database search. We are also proud of being able to implement the Twilio's text message service for a contactless check in.

What I learned

We had an amazing time working with Google Vision API and we learned so much. We also learned how to collaborate with each other virtually.

What's next for HandsFree

We would love to finish features that we were not able to implement during the Hackathon due the time constraint, like adding clients to the database using the form on the web app.

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