main.py

import cv2
import numpy as np
import cvzone
import pickle

width,height = (158-50), (240-192)

cap=cv2.VideoCapture('carPark.mp4')

with open('CarParkPos', 'rb') as f:
    posList = pickle.load(f)

def checkParkingSpace(imgPro):
    spaceCounter = 0
    for pos in posList:

        x,y=pos
        cv2.imshow('Image', img)

        imgCrop=imgPro[y:y+height,x:x+width]
        #cv2.imshow(str(x*y),imgCrop)
        count=cv2.countNonZero(imgCrop)
        cvzone.putTextRect(img,str(count),(x,y+height-2),scale=1,thickness=2,offset=0,colorR=(0,0,255))

        if count < 500:
            color=(0,255,0)
            thickness=4
            spaceCounter+=1
        else:
            color=(0,0,255)
            thickness=2
        cv2.rectangle(img,pos,(pos[0]+width,pos[1]+height),color,thickness)
    cvzone.putTextRect(img,f'FREE{str(spaceCounter)}/{len(posList)}',(450,50),scale=2,thickness=5,offset=10,colorR=(0,255,0))


while True:

    if cap.get(cv2.CAP_PROP_POS_FRAMES)== cap.get(cv2.CAP_PROP_FRAME_COUNT):
        cap.set(cv2.CAP_PROP_POS_FRAMES,0)

    success, img = cap.read()

    imgGray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    imgBlur=cv2.GaussianBlur(imgGray,(3,3),1)
    imgThreshold=cv2.adaptiveThreshold(imgBlur,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
                          cv2.THRESH_BINARY_INV,25,16)
    imgMedian=cv2.medianBlur(imgThreshold,5)
    kernel=np.zeros((3,3),np.uint8)
    imgDilate=cv2.dilate(imgMedian,kernel,iterations=1)

    checkParkingSpace(imgDilate)


    cv2.imshow('Image',img)
    #cv2.imshow('ImageBlur',imgBlur)
    #cv2.imshow('ImageThreshold', imgThreshold)
    # cv2.imshow('ImageMedian', imgMedian)
    # cv2.imshow('ImageDilate', imgDilate)

    cv2.waitKey(1)