Danger Det

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  Team

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  Gun

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  Fire

Inspiration

We were initially planning on creating an American Sign Language interpreter using Computer Vision. We then brainstormed for a while and got to the interesting idea of security. Using Computer Vision, we could build an app that detects possible hazards.

What it does

Danger Det detects firearm (rifle and guns) and fire hazards using the pretrained YOLO model. It notifies the user of possibile dangers.

How we built it

We used JavaScript, React, and HTML for the frontend, and Flask, Python, and OpenCV for the backend. The training data is taken from the YOLO image recognition model.

Challenges we ran into

The biggest challenge was integrating the AI model and parsing the video into frames.

Accomplishments that we're proud of

We are very proud that we successfully implemented the AI model and worked with Computer Vision.

What we learned

We learn how to work with computer vision, which was our main objective.

What's next for Danger Det

We would like to add a lot to Danger Det, such as more security features like intruder alerts, license plate recognition, and more. We are proud of what we were able to do in the time we had and would like to add more to it in the future.

Built With

• flask
• javascript
• opencv
• python