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Part 2: Smoke and fire detection using opencv,raspberry pi
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Part 2: Smoke and fire detection using opencv,raspberry pi
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import numpy as np
import cv2
import time
import smtplib
import RPi.GPIO as GPIO
tStart = time.time()
color=0
smoke=0
inten=0
res=0
cap = cv2.VideoCapture(0)
fgbg = cv2.createBackgroundSubtractorMOG2(detectShadows=False)
frame_count = 1
#GPIO SETUP
channel = 21
GPIO.setmode(GPIO.BCM)
GPIO.setup(channel, GPIO.IN)
flame_sen=0
def callback(channel):
flame_sen=1
if smoke==1 and color==1 and inten==1:
res=1
print('res=',res)
print("flame successfully detected")
if(res==1):
try:
server = smtplib.SMTP('smtp.gmail.com', 587)
server.starttls()
server.login("senders mail id", "password")
msg = "WARNING/n fire detected"
server.sendmail("your email adresss", "recievers mail", msg)
server.quit()
print ("email sending succesfull!")
except:
print ('0')
# print("flame detected by sensor")
GPIO.add_event_detect(channel, GPIO.BOTH, bouncetime=300) # let us know when the pin goes HIGH or LOW
GPIO.add_event_callback(channel, callback)
# +++++++++++++++++++++Processing video++++++++++++++++++++++
while True:
ret, frame = cap.read()
if frame is None:
print("video read complete")
break
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
blur = cv2.GaussianBlur(frame, (21, 21), 0)
hsv = cv2.cvtColor(blur, cv2.COLOR_BGR2HSV)
a = [18, 50, 50]
b = [35, 255, 255]
a = np.array(a, dtype="uint8")
b = np.array(b, dtype="uint8")
mask = cv2.inRange(hsv, a, b)
output = cv2.bitwise_and(frame, hsv, mask=mask)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
gray_frame = cv2.GaussianBlur(gray, (5, 5), 5)
fmask = fgbg.apply(gray_frame)
kernel = np.ones((20, 20), np.uint8)
fmask = cv2.medianBlur(fmask, 3)
fmask = cv2.dilate(fmask, kernel)
ret, binary = cv2.threshold(gray, 180, 255, cv2.THRESH_BINARY)
height, width = binary.shape
npframe = np.array(frame)
npbinary = np.array(binary)
# +++++++++++++++++++++Denoising+++++++++++++++++++++++++
#Median blur
dst = cv2.medianBlur(binary, 5)
# +++++++++++++++Open operation (corrosion and re-expansion) denoising++++++++++++
kernal2 = np.ones((5, 5), np.uint8)
opening = cv2.morphologyEx(dst, cv2.MORPH_OPEN, kernal2)
# +++++++++++++++Determine if the highlight color is R >= G > B+++++++++++++
binary_x = 0
Rt = 135
St = 55
while binary_x < height:
binary_y = 0
while binary_y < width:
if (opening[binary_x, binary_y] == 255):
p = npframe[(binary_x, binary_y)]
# print(p)
if p[2] >= p[1] >= p[0]: # & p2[2] >= 5:
binary_y += 1
continue
else:
opening[binary_x, binary_y] = 0
binary_y += 1
binary_x += 1
# +++++++++++++++Show highlight area outline+++++++++++++++++++++++
contour_img, contours, hierarchy = cv2.findContours(fmask, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
for cnt in contours:
x, y, w, h = cv2.boundingRect(cnt)
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
smoke=1
print('smoke =',smoke)
contour_img, contours, hierarchy = cv2.findContours(mask, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
for cnt in contours:
x, y, w, h = cv2.boundingRect(cnt)
cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)
color=1
print('color =',color)
image, contour, hierarchy = cv2.findContours(opening,
cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
if contour == []:
print('No contour')
else:
# Display outlines in the video window
cv2.drawContours(frame, contour, -1, (0, 0, 255), 2)
inten=1
print('inten =',inten)
# ++++++++++++++++++++++Show video++++++++++++++++++++++
cv2.imshow('frame', output) # Original image
#cv2.imshow('binary', binary)
#cv2.imshow('original', frame)
#cv2.imshow('frame1', gray_frame)
#cv2.imshow('aa', frame)
frame_count += 1
if (cv2.waitKey(10) & 0xFF) == 27:
break
tEnd = time.time()
totalTime = (tEnd - tStart)
#print(tStart)
#print(tEnd)
print('total time %d ' % totalTime)
if cv2.waitKey(1) & 0xFF == 27:
print('Stop playing')
break
# tEnd = time.time()
# assign function to GPIO PIN, Run function on change
cap.release()
cv2.destroyAllWindows()
# totalTime = (tEnd - tStart)
print(time.process_time())
# print ('total time %d ' % totalTime)