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motion_detect.py
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import datetime
import imutils
import cv2
import numpy as np
from database_handler import getLastSetting
class motionDetect:
frame_width = 800
first_frame = None
# videoAddress for camera is 0
# http://208.139.200.133/mjpg/video.mjpg
# http://192.168.1.53:8000/stream.mjpg
video_stream = cv2.VideoCapture("http://208.139.200.133/mjpg/video.mjpg")
output_frame = np.zeros([frame_width, frame_width, 3], dtype=np.uint8)
output_frame2 = np.zeros([frame_width, frame_width, 3], dtype=np.uint8)
ticks=0
settings = None
def put_timestamp(self, frame):
if (self.settings.displayTimestamp == "yes"):
cv2.putText(frame,
datetime.datetime.now().strftime("%a %d/%m/%Y %H:%M:%S"),
(10, frame.shape[0] - 10),
cv2.FONT_HERSHEY_DUPLEX, 0.35, (0, 0, 255), 1)
def put_area_mark(self, frame, area ,text,x,y):
cv2.putText(frame, area, (x, y), cv2.FONT_HERSHEY_DUPLEX,
0.5, (0, 0, 255), 2)
cv2.putText(frame, text, (x, y+15), cv2.FONT_HERSHEY_DUPLEX,
0.5, (0, 0, 255), 2)
def save_outputs(self, frame):
#cv2.imwrite("static/img/sysfeed.jpg", frame)
self.output_frame = cv2.imencode('.jpg', frame)[1].tobytes()
self.output_frame2 = frame
def no_analysis(self):
frame = self.video_stream.read()
frame = frame[1]
frame = imutils.resize(frame, width=self.frame_width)
self.put_timestamp(frame)
self.save_outputs(frame)
def two_area_analysis(self, vertical):
if(self.settings.area1 == 'True'):
detect_first_area = True
else:
detect_first_area = False
if (self.settings.area2 == 'True'):
detect_second_area = True
else:
detect_second_area = False
frame = self.video_stream.read()
frame = frame[1]
if(detect_first_area):
text_ar1 = "No movement"
else:
text_ar1 = "Detection turned off"
if (detect_second_area):
text_ar2 = "No movement"
else:
text_ar2 = "Detection turned off"
frame = imutils.resize(frame, width=self.frame_width)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (21, 21), 0)
if self.first_frame is None or (self.ticks > self.settings.maxTicks):
self.first_frame = gray
self.ticks = 0
frameDelta = cv2.absdiff(self.first_frame, gray)
thresh = cv2.threshold(frameDelta, 25, 255, cv2.THRESH_BINARY)[1]
thresh = cv2.dilate(thresh, None, iterations=2)
cnts = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
cnts = imutils.grab_contours(cnts)
for c in cnts:
if cv2.contourArea(c) < self.settings.sensitivity:
continue
(x, y, w, h) = cv2.boundingRect(c)
# perform verification for 1st Area
if(vertical):
if(detect_first_area and x < int(frame.shape[1]/2)):
cv2.rectangle(frame, (x, y), (x + w, y + h),
(255, 0, 255), 2)
# verify movement for the 1st Area
text_ar1 = "Movement"
detected_movement = True
# perform verification for 2nd Area
if (detect_second_area and x > int(frame.shape[1]/2)):
cv2.rectangle(frame, (x, y), (x + w, y + h),
(255, 0, 255), 2)
# verify movement for the 1st Area
text_ar2 = "Movement"
else:
if (detect_first_area and y < int(frame.shape[0]/2)):
cv2.rectangle(frame, (x, y), (x + w, y + h),
(255, 0, 255), 2)
# verify movement for the 1st Area
text_ar1 = "Movement"
detected_movement = True
# perform verification for 2nd Area
if (detect_second_area and y > int(frame.shape[0]/2)):
cv2.rectangle(frame, (x, y), (x + w, y + h),
(255, 0, 255), 2)
# verify movement for the 1st Area
text_ar2 = "Movement"
self.put_area_mark(frame, "Area 1", text_ar1, 10, 20)
if(vertical):
self.put_area_mark(frame, "Area 2", text_ar2,
int(frame.shape[1]/2) + 10, 20)
else:
self.put_area_mark(frame, "Area 2", text_ar2,
10, int(frame.shape[0]/2) + 20)
if(self.settings.displayBoundaries == 'yes'):
if(vertical):
cv2.line(frame, (int(frame.shape[1]/2), 0),
(int(frame.shape[1]/2), frame.shape[0]),
(255, 0, 255), 2, 8, 0)
else:
cv2.line(frame, (0, int(frame.shape[0]/2)),
(int(frame.shape[1]), int(frame.shape[0]/2)),
(255, 0, 255),
2, 8, 0)
cv2.putText(frame, "Counter no:" + str(self.ticks),
(10, frame.shape[0] - 20), cv2.FONT_HERSHEY_DUPLEX, 0.35,
(0, 0, 255), 1)
self.put_timestamp(frame)
self.ticks = self.ticks + 1
self.save_outputs(frame)
def three_area_analysis(self, vertical):
if (self.settings.area1 == 'True'):
detect_first_area = True
else:
detect_first_area = False
if (self.settings.area2 == 'True'):
detect_second_area = True
else:
detect_second_area = False
if (self.settings.area3 == 'True'):
detect_third_area = True
else:
detect_third_area = False
frame = self.video_stream.read()
frame = frame[1]
if(detect_first_area):
text_ar1 = "No movement"
else:
text_ar1 = "Detection turned off"
if (detect_second_area):
text_ar2 = "No movement"
else:
text_ar2 = "Detection turned off"
if (detect_third_area):
text_ar3 = "No movement"
else:
text_ar3 = "Detection turned off"
frame = imutils.resize(frame, width=self.frame_width)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (21, 21), 0)
if self.first_frame is None or (self.ticks > self.settings.maxTicks):
self.first_frame = gray
self.ticks = 0
frameDelta = cv2.absdiff(self.first_frame, gray)
thresh = cv2.threshold(frameDelta, 25, 255, cv2.THRESH_BINARY)[1]
thresh = cv2.dilate(thresh, None, iterations=2)
cnts = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
cnts = imutils.grab_contours(cnts)
for c in cnts:
if cv2.contourArea(c) < self.settings.sensitivity:
continue
(x, y, w, h) = cv2.boundingRect(c)
if(vertical):
if(detect_first_area and x < int(frame.shape[1]/3)):
cv2.rectangle(frame, (x, y), (x + w, y + h),
(255, 0, 255), 2)
# verify movement for the 1st Area
text_ar1 = "Movement"
detected_movement = True
# perform verification for 2nd Area
if (detect_second_area and x > int(frame.shape[1]/3) and x < int(frame.shape[1]*2/3)):
cv2.rectangle(frame, (x, y), (x + w, y + h),
(255, 0, 255), 2)
# verify movement for the 1st Area
text_ar2 = "Movement"
# perform verification for 3rd Area
if (detect_third_area and x > int(frame.shape[1] * 2 / 3)):
cv2.rectangle(frame, (x, y), (x + w, y + h),
(255, 0, 255), 2)
# verify movement for the 1st Area
text_ar3 = "Movement"
else:
if (detect_first_area and y < int(frame.shape[0] / 3)):
cv2.rectangle(frame, (x, y), (x + w, y + h),
(255, 0, 255), 2)
# verify movement for the 1st Area
text_ar1 = "Movement"
detected_movement = True
# perform verification for 2nd Area
if (detect_second_area and y > int(frame.shape[0] / 3) and y < int(frame.shape[0] * 2 / 3)):
cv2.rectangle(frame, (x, y), (x + w, y + h),
(255, 0, 255), 2)
# verify movement for the 1st Area
text_ar2 = "Movement"
# perform verification for 3rd Area
if (detect_third_area and y > int(frame.shape[0] * 2 / 3)):
cv2.rectangle(frame, (x, y), (x + w, y + h),
(255, 0, 255), 2)
# verify movement for the 1st Area
text_ar3 = "Movement"
self.put_area_mark(frame, "Area 1", text_ar1, 10, 20)
if (vertical):
self.put_area_mark(frame, "Area 2", text_ar2,
int(frame.shape[1]/3) + 10, 20)
self.put_area_mark(frame, "Area 3", text_ar3,
int(frame.shape[1]*2/3) + 10, 20)
else:
self.put_area_mark(frame, "Area 2", text_ar2, 10,
int(frame.shape[0]/3) + 20)
self.put_area_mark(frame, "Area 3", text_ar3, 10,
int(frame.shape[0]*2/3) + 20)
if(self.settings.displayBoundaries == 'yes'):
if (vertical):
cv2.line(frame, (int(frame.shape[1] / 3), 0),
(int(frame.shape[1] / 3), frame.shape[0]),
(255, 0, 255),
2, 8, 0)
cv2.line(frame, (int(frame.shape[1]*2/3), 0),
(int(frame.shape[1]*2/3), frame.shape[0]),
(255, 0, 255), 2, 8, 0)
else:
cv2.line(frame, (0, int(frame.shape[0]/3)),
(int(frame.shape[1]), int(frame.shape[0]/3)),
(255, 0, 255),
2, 8, 0)
cv2.line(frame, (0, int(frame.shape[0]*2/3)),
(int(frame.shape[1]), int(frame.shape[0]*2/3)),
(255, 0, 255),
2, 8, 0)
cv2.putText(frame, "Counter no:" + str(self.ticks),
(10, frame.shape[0] - 20), cv2.FONT_HERSHEY_DUPLEX, 0.35,
(0, 0, 255), 1)
self.put_timestamp(frame)
self.ticks = self.ticks + 1
self.save_outputs(frame)
def simple_analysis(self):
frame = self.video_stream.read()
frame = frame[1]
text = "No movement"
frame = imutils.resize(frame, width=self.frame_width)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (21, 21), 0)
#reset the comparision frame to prevent false positives
if self.first_frame is None or (self.ticks > self.settings.maxTicks):
self.first_frame = gray
self.ticks = 0
# calculate the odds between present frame and comparision frame
frameDelta = cv2.absdiff(self.first_frame, gray)
thresh = cv2.threshold(frameDelta, 25, 255, cv2.THRESH_BINARY)[1]
# dilate the thresholded image to fill in holes, then find contours on thresholded image
thresh = cv2.dilate(thresh, None, iterations=2)
cnts = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
cnts = imutils.grab_contours(cnts)
# loop over the contours
for c in cnts:
# ignore countours with small area
if cv2.contourArea(c) < self.settings.sensitivity:
continue
# compute the bounding box for the contour, draw it on the frame,
# and update the text
(x, y, w, h) = cv2.boundingRect(c)
cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 255), 2)
text = "Detected"
# Put information about detected movement and put timestamp
cv2.putText(frame, "Movement Status: {}".format(text),
(10, 20), cv2.FONT_HERSHEY_DUPLEX, 0.5, (0, 0, 255), 2)
cv2.putText(frame, "Counter no:" + str(self.ticks),
(10, frame.shape[0] - 20), cv2.FONT_HERSHEY_DUPLEX,
0.35, (0, 0, 255), 1)
self.put_timestamp(frame)
self.ticks = self.ticks + 1
self.save_outputs(frame)
#cv2.imshow("Security Feed", self.output_frame)
#key = cv2.waitKey(1) & 0xFF
def start_analysis(self):
while True:
self.settings = getLastSetting()
if(self.settings.analysisMode == "noAn"):
self.no_analysis()
elif(self.settings.analysisMode == "simple"):
self.simple_analysis()
elif (self.settings.analysisMode == "2areaVert"):
self.two_area_analysis(True)
elif (self.settings.analysisMode == "3areaVert"):
self.three_area_analysis(True)
elif (self.settings.analysisMode == "2areaHor"):
self.two_area_analysis(False)
elif (self.settings.analysisMode == "3areaHor"):
self.three_area_analysis(False)
else:
self.no_analysis()
def display_window(self):
while True:
cv2.imshow("Security Feed", np.array(self.output_frame))
key = cv2.waitKey(1) & 0xFF
#def get_frame(self):
# return self.output_frame
m_d = motionDetect()