Application of convolutional networks of the YOLO architecture for calculating free parking spaces in an arbitrary parking lot

Abstract

The paper describes the solution of the problem of automatic fixation of the availability of free parking spaces in parking lots based on the video stream of the surveillance camera. The problem was solved using a combination of the YOLOv7 model for detecting objects of interest of the “car” type, trained on a specially created training sample and grouping of objects using the k-means algorithm. The proposed solution has shown satisfactory accuracy and suitability for practical use in conditions of significant optical interference – daily light fluctuations and precipitation for calculating free parking spaces by the model without retraining it for various parking lots