Illegal parking detection method based on deep learning
A parking violation and deep learning technology, applied in the field of parking violation detection based on deep learning, can solve the problems of unsatisfactory real-time effect, high hardware dependence, high deployment cost, etc., to solve the tracking timing problem, improve the calculation speed, Solve the effect of illegal parking detection
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[0024] A method for detecting illegal parking based on deep learning, comprising the steps of:
[0025] Step 1. Designate a no-parking zone (NPZ, no parking zone) for the surveillance video.
[0026] Step 2. Access the real-time video screen or video, detect the vehicle in the video, and obtain the vehicle detection frame, specifically:
[0027] The video is input into the yolo-mini network model to detect the vehicle in the video screen. The yolo-mini network model uses yolo-tiny as the backbone network, and the two largest calculations (Bflops) of the 12th layer and the 21st layer are used. The convolution operation between the convolution filter F of the layer and the input feature X is modified from multiplication to the L1 distance, that is, the absolute value of the difference between F and X, and a BN layer is added to normalize the result , to ensure that the original activation function can be used normally, and the modified network is named yolo-mini.
[0028] Step...
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