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As the spots are well defined and assuming camera is fixed, you could use opencv background subtraction with sufficient amount of history to detect if there is an object in a particular parking spot. Look at this opencv tutorial for more information. I am trying to use opencv to automatically find and locate all parking spots in an empty parking lot. Currently, I have a code that thresholds the image, applies canny edge detection, and then uses probabilistic hough lines to find the lines that mark each parking spot. The program then draws the lines and the points that make up the lines. Perform bitwise xor between above mask and first threshold image, this will give you mask for each parking slot. Using this mask you can analyse the background colour for parking slot, can decide whether it is occupied or not.
OpenCV is an extensive open source library (available in python, Java, and C) that’s used for image analysis and is pretty neat. The lofty goal for my OpenCV experiment was to take any static image or video of a parking lot and be able to automatically detect whenever a parking space was available.
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