When i heard projects regarding surveillance camera using machine learning to detect traffic, theft and other computer vision project i felt inspired and need to create such system to detect accidents for better healthcare

What it does

It detects whether the frames captured by video feeds generated by a dashcam/CCTV are predicted to be classified as 'accidents' or 'non-accidents', as to insure better safety measures for drivers and report that to nearby emergency services

How we built it

I built this project using both the Pytorch Deep Learning framework and trained my model on my laptop on different Convolution neural networks architecture

Challenges we ran into

Our main challenge was to gather accident images and videos and manually categuorize images into accient and non-accident frames

To design a deep convolutional neural networks model for this project.

Limited hardware resorces like GPU's.

Accomplishments that we're proud of

As a deep learning fresher, I have build this project with limited hardware and manually categorizing Data to yield better results and accuracy

What we learned

I am pround that i have learnt about computer vision, Pytorch framework and i will continue to learn more advances deep learning concepts

What's next for Dash cam accident detection

To improve model further more to increase its accuracy and to create a responsive web app with google map api to share location during accident to nearby emergency services

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