Our team aimed to create a parking detection program that would be able to observe cars in a street parking environment and identify open spots with high accuracy. The program takes in a video feed and applies the model to identify vehicles within a frame and then notifies users when a parking spot in the frame opens up. Our program aims to streamline finding parking by automating the process, relying on a model with the capacity to alert users when a parking spot is open, or opening up. Using : Keras 2.3.1, OpenCV-Python 4.2.0.34, Tensorflow 1.15.2, ImageAI 2.1.5, PyCharm, Python 3.7, YoloV3 Using openCV, video input data (live or prerecorded) is broken down frame by frame and fed into ImageAI’s CustomObjectDetection method. By calculating the center of each set of box points and creating a dictionary of centroids per frame we are able individualize objects.