def GMG(cap):
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(3,3))
fgbg = cv2.createBackgroundSubtractorGMG()
while(1):
ret, frame = cap.read()
fgmask = fgbg.apply(frame)
fgmask = cv2.morphologyEx(fgmask, cv2.MORPH_OPEN, kernel)
cv2.imshow('frame',fgmask)
k = cv2.waitKey(30) & 0xff
if k == 27:
break
cap.release()
cv2.destroyAllWindows()
def test_414(self):
#41.4BackgroundSubtractorGMG
# 此算法结合了静态背景图像估计和每个像素的贝叶斯分割
cap = cv2.VideoCapture('vtest.avi')
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3))
fgbg = cv2.createBackgroundSubtractorGMG()
while (1):
ret, frame = cap.read()
fgmask = fgbg.apply(frame)
fgmask = cv2.morphologyEx(fgmask, cv2.MORPH_OPEN, kernel)
cv2.imshow('frame', fgmask)
k = cv2.waitKey(30) & 0xff
if k == 27:
break
cap.release()
cv2.destroyAllWindows()
print("")
def bg_separation(frames, t):
if (FLAGS.bgs == "MOG"):
separator = cv2.createBackgroundSubtractorMOG()
elif (FLAGS.bgs == "MOG2"):
separator = cv2.createBackgroundSubtractorMOG2()
elif (FLAGS.bgs == "GMG"):
separator = cv2.createBackgroundSubtractorGMG()
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3))
else:
print FLAGS.bgs, "method not supported"
sys.exit(0)
n, h, w, _ = frames.shape
output_frames = np.zeros((n, h, w), dtype=np.uint8)
for i in range(n):
output_frames[i] = separator.apply(frames[i])
return output_frames
def setupof(U: dict, P):
xpix = U['xpix']
ypix = U['ypix']
gmm = None
lastflow = None #if it stays None, signals to use GMM
if U['ofmethod'] == 'hs':
pass
elif U['ofmethod'] == 'farneback':
lastflow = np.zeros((ypix, xpix, 2))
# %% GMM
elif U['ofmethod'] == 'mog':
# http://docs.opencv.org/3.2.0/d7/d7b/classcv_1_1BackgroundSubtractorMOG2.html
gmm = cv2.createBackgroundSubtractorMOG2(
history=P.getint('gmm', 'nhistory'),
varThreshold=P.getfloat('gmm', 'varThreshold'),
detectShadows=False)
gmm.setNMixtures(P.getint('gmm', 'nmixtures'))
gmm.setComplexityReductionThreshold(P.getfloat('gmm', 'CompResThres'))
elif U['ofmethod'] == 'knn':
gmm = cv2.createBackgroundSubtractorKNN(history=P.getint(
'gmm', 'nhistory'),
detectShadows=True)
elif U['ofmethod'] == 'gmg':
try:
gmm = cv2.createBackgroundSubtractorGMG(
initializationFrames=P.getint('gmm', 'nhistory'))
except AttributeError as e:
raise ImportError(
f'GMG is for OpenCV3, part of opencv_contrib. {e}')
else:
raise TypeError(f'unknown method {U["ofmethod"]}')
return lastflow, gmm
def background_subtractor(video_link, method="MOG"):
cap = cv2.VideoCapture(video_link)
if method == "MOG":
fgbg = cv2.createBackgroundSubtractorMOG()
elif method == "MOG2":
fgbg = cv2.createBackgroundSubtractorMOG2()
elif method == "GMG":
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3))
fgbg = cv2.createBackgroundSubtractorGMG()
while (1):
ret, frame = cap.read()
fgmask = fgbg.apply(frame)
if method == "GMG":
fgmask = cv2.morphologyEx(fgmask, cv2.MORPH_OPEN, kernel)
cv2.imshow('frame', fgmask)
print(fgmask)
k = cv2.waitKey(30) & 0xff
if k == 27:
break
cap.release()
cv2.destroyAllWindows()
# -*- coding: utf-8 -*-
import numpy as np
import cv2
cap = cv2.VideoCapture('../assets/test.avi')
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(3,3))
# 沒有這個 attribute
fgbg = cv2.createBackgroundSubtractorGMG()
while(1):
ret, frame = cap.read()
fgmask = fgbg.apply(frame)
fgmask = cv2.morphologyEx(fgmask, cv2.MORPH_OPEN, kernel)
cv2.imshow('frame',fgmask)
k = cv2.waitKey(30) & 0xff
if k == 27:
break
cap.release()
cv2.destroyAllWindows()
def __init__(self):
self.bgsubstractor = cv2.createBackgroundSubtractorGMG()
import numpy as np
import cv2
cap = cv2.VideoCapture(0)
fgbg = cv2.createBackgroundSubtractorGMG()
while(1):
ret, frame = cap.read()
fgmask = fgbg.apply(frame)
cv2.imshow('frame',fgmask)
k = cv2.waitKey(30) & 0xff
if k == 27:
break
cap.release()
cv2.destroyAllWindows()
pt4 = [w, line_up]
pts_L2 = np.array([pt3, pt4], np.int32)
pts_L2 = pts_L2.reshape((-1, 1, 2))
pt5 = [0, up_limit]
pt6 = [w, up_limit]
pts_L3 = np.array([pt5, pt6], np.int32)
pts_L3 = pts_L3.reshape((-1, 1, 2))
pt7 = [0, down_limit]
pt8 = [w, down_limit]
pts_L4 = np.array([pt7, pt8], np.int32)
pts_L4 = pts_L4.reshape((-1, 1, 2))
#fgbg = cv2.createBackgroundSubtractorMOG2(detectShadows = False) #Create the background substractor
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3))
fgbg = cv2.createBackgroundSubtractorGMG() #Create the background substractor
kernelOp = np.ones((3, 3), np.uint8)
kernelCl = np.ones((11, 11), np.uint8)
#Variables
font = cv2.FONT_HERSHEY_SIMPLEX
persons = []
max_p_age = 5
pid = 1
# Start the frame count
frame_count = 0
while True:
_, frame = cap.read() #read a frame
