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import numpy as np
import cv2
import sys
TEXT_COLOR = (0, 255, 0)
TRACKER_COLOR = (255, 0, 0)
FONT = cv2.FONT_HERSHEY_SIMPLEX
VIDEO_SOURCE = "videos/Animal_1.mp4"
BGS_TYPES = ["GMG", "MOG", "MOG2", "KNN", "CNT"]
BGS_TYPE = BGS_TYPES[2]
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
def getFilter(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.MORPH_CLOSE, 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()
if BGS_TYPE == "MOG":
return cv2.bgsegm.createBackgroundSubtractorMOG()
if BGS_TYPE == "MOG2":
return cv2.createBackgroundSubtractorMOG2()
if BGS_TYPE == "KNN":
return cv2.createBackgroundSubtractorKNN()
if BGS_TYPE == "CNT":
return cv2.bgsegm.createBackgroundSubtractorCNT()
print("Invalid detector")
sys.exit(1)
cap = cv2.VideoCapture(VIDEO_SOURCE)
bg_subtractor = getBGSubtractor(BGS_TYPE)
minArea = 250
def main():
while (cap.isOpened):
ok, frame = cap.read()
if not ok:
print("Finished processing the video")
break
frame = cv2.resize(frame, (0, 0), fx=0.50, fy=0.50)
bg_mask = bg_subtractor.apply(frame)
bg_mask = getFilter(bg_mask, 'combine')
bg_mask = cv2.medianBlur(bg_mask, 5)
(contours, hierarchy) = cv2.findContours(bg_mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
#print(contours)
for cnt in contours:
area = cv2.contourArea(cnt)
if area >= minArea:
x, y, w, h = cv2.boundingRect(cnt)
cv2.rectangle(frame, (10,30), (250,55), (255,0,0), -1)
cv2.putText(frame, 'Motion detected!', (10,50), FONT, 0.8, TEXT_COLOR, 2, cv2.LINE_AA)
#cv2.drawContours(frame, cnt, -1, TRACKER_COLOR, 3)
#cv2.drawContours(frame, cnt, -1, (255,255,255), 1)
#cv2.rectangle(frame, (x,y), (x+w, y+h), TRACKER_COLOR, 3)
#cv2.rectangle(frame, (x, y), (x + w, y + h), (255,255,255), 1)
# https://www.pyimagesearch.com/2016/03/07/transparent-overlays-with-opencv/
for alpha in np.arange(0.8, 1.1, 0.9)[::-1]:
frame_copy = frame.copy()
output = frame.copy()
cv2.drawContours(frame_copy, [cnt], -1, TRACKER_COLOR, -1)
frame = cv2.addWeighted(frame_copy, alpha, output, 1 - alpha, 0, output)
result = cv2.bitwise_and(frame, frame, mask=bg_mask)
cv2.imshow('Frame', frame)
cv2.imshow('Mask', result)
if cv2.waitKey(1) & 0xFF == ord("q"):
break
main()
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