import numpy as np
import cv2
import sys
from random import randint
TEXT_COLOR = (randint(0, 255), randint(0,255), randint (0,255))
BORDER_COLOR = (randint(0, 255), randint(0,255), randint (0,255))
FONT = cv2.FONT_HERSHEY_SIMPLEX
VIDEO_SOURCE =”Video/Traffic_4.mp4″
#print (TEXT_COLOR)
BGS_TYPES = (‘GMG’, ‘MOG’, ‘MOG2’, ‘KNN’, ‘CNT’)
#print(BGS_TYPES[1])
def getKernel(KERNEL_TYPE):
if KERNEL_TYPE == ‘dilation’:
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3,3))
if KERNEL_TYPE == ‘opening’:
kernel = np.ones((3,3), np.uint8)
if KERNEL_TYPE == ‘closing’:
kernel = np.ones((3,3), np.uint8)
return kernel
#print(getKernel(‘opening’))
def getFiltrer(img, filter):
if filter == ‘closing’:
return cv2.morphologyEx(img, cv2.MORPH_CLOSE, getKernel(‘closing’), iterations=2)
if filter == ‘opening:’:
return cv2.morphologyEx(img, cv2.MORPH_OPEN, getKernel(‘opening’), iterations=2)
if filter == ‘dilation:’:
return cv2.dilate(img, getKernel(‘dilation’), iterations=2)
if filter == ‘combine’:
closing = cv2.morphologyEx(img, cv2.MORPHCLOSE, getKernel(‘closing’), iterations=2)
opening = cv2.morphologyEx(closing, cv2.MORPH_OPEN, getKernel(‘opening’), iterations=2)
dilation = cv2.dilate(opening, getKernel(‘dilation’), iterations=2)
return dilation
def getBGSubtractor(BGS_TYPE):
if BGS_TYPE == ‘GMG’:
return cv2.bgsegm.createBackgroundSubtractorGMG(initializationFrames = 120, decisionThreshold=0.8)
if BGS_TYPE == ‘MOG’:
return cv2.bgsegm.createBackgroundSubtractorMOG(history=200, nmixtures=5,
backgroundRatio=0.7, noiseSigma=0)
if BGS_TYPE == ‘MOG2’:
return cv2.createBackgroundSubtractorMOG2(history=500, detectShadows=True, varThreshold=100)
if BGS_TYPE == ‘KNN’:
return cv2.createBackgroundSubtractorKNN(history=500, dist2Threshold=400, detectShadows=True)
if BGS_TYPE == ‘CNT’:
return cv2.createBackgroundSubtractorCNT(minPixelStability=15, useHistory=True, maxPixelStability=15*60, isParallel=True)
print(‘Detector Inválido’)
sys.exit(1)
cap = cv2.VideoCapture(VIDEO_SOURCE)
bg_subtractor = getBGSubtractor(BGS_TYPES[0])
def main():
while cap.isOpened():
ok, frame = cap.read()
#print(‘frame.shape’)
frame = cv2.resize(frame, (0,0), fx=0.5, fy=0.5)
#print(frame.shape)
bg_mask = bg_subtractor.apply(frame)
fg_mask = getFiltrer(bg_mask, ‘dilation’)
if not ok:
print(‘Erro’)
break
cv2.imshow(‘Frame’, frame)
cv2.imshow(‘BG mask’, bg_mask)
cv2.imshow(‘BG mask filtrer ‘, fg_mask)
if cv2.waitKey(1) & 0xFF == ord(‘q’):
break
main()