Project 2: Parking Space Detection Using Fisheye Camera data

import cv2
import numpy as np
import pickle

rectW,rectH=107,48

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

with open('carParkPos','rb') as f:
posList=pickle.load(f)
frame_counter = 0
def check(imgPro):
spaceCount=0
for pos in posList:
x,y=pos
crop=imgPro[y:y+rectH,x:x+rectW]
count=cv2.countNonZero(crop)
if count<900:
spaceCount+=1
color=(0,255,0)
thick=5
else:
color=(0,0,255)
thick=2

cv2.rectangle(img,pos,(x+rectW,y+rectH),color,thick)
cv2.rectangle(img,(45,30),(250,75),(180,0,180),-1)
cv2.putText(img,f'Free: {spaceCount}/{len(posList)}',(50,60),cv2.FONT_HERSHEY_SIMPLEX,0.9,(255,255,255),2)

while True:
_,img=cap.read()
if frame_counter == cap.get(cv2.CAP_PROP_FRAME_COUNT):
frame_counter = 0 #Or whatever as long as it is the same as next line
cap.set(cv2.cv.CV_CAP_PROP_POS_FRAMES, 0)
gray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
blur=cv2.GaussianBlur(gray,(3,3),1)
Thre=cv2.adaptiveThreshold(blur,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,cv2.THRESH_BINARY_INV,25,16)
blur=cv2.medianBlur(Thre,5)
kernel=np.ones((3,3),np.uint8)
dilate=cv2.dilate(blur,kernel,iterations=1)
check(dilate)

cv2.imshow("Image",img)
cv2.waitKey(10)