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How to count the number of faces detected in live video by openCV using python?

I need to count the number of faces in a video taken from webcam.For example,if I am standing in front of the camera then count=1,now if any other person is detected then count=2,if another person is detected then the count should be 3.

This is the code:

import cv2 import sys

cascPath = sys.argv[1]

faceCascade = cv2.CascadeClassifier(cascPath)

video_capture = cv2.VideoCapture(0)

while True: # Capture frame-by-frame

ret, frame = video_capture.read()

gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

faces = faceCascade.detectMultiScale(
    gray,
    scaleFactor=1.1,
    minNeighbors=5,
    minSize=(30, 30),
    flags=cv2.cv.CV_HAAR_SCALE_IMAGE
)

# Draw a rectangle around the faces
for (x, y, w, h) in faces:
    cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)

# Display the resulting frame
cv2.imshow('Video', frame)

if cv2.waitKey(1) & 0xFF == ord('q'):
    break

video_capture.release()

cv2.destroyAllWindows()

I am using frontal_face_haarcascade.xml by opencv in python. I can detect faces in frame and then increase the count, but what's happening is that the count is increasing as the number of frames.So, even if 1 person was detected standing for 10 sec, it shows count as some '67'

How can I overcome this problem.

How to count the number of faces detected in live video by openCV using python?

I need to count the number of faces in a video taken from webcam.For example,if I am standing in front of the camera then count=1,now if any other person is detected then count=2,if another person is detected then the count should be 3.

This is the code:

code:

import cv2
import sys

sys cascPath = sys.argv[1]

sys.argv[1] faceCascade = cv2.CascadeClassifier(cascPath)

cv2.CascadeClassifier(cascPath) video_capture = cv2.VideoCapture(0)

cv2.VideoCapture(0) while True: # Capture frame-by-frame

frame-by-frame ret, frame = video_capture.read()

video_capture.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

faces = faceCascade.detectMultiScale(
    gray,
    scaleFactor=1.1,
    minNeighbors=5,
    minSize=(30, 30),
    flags=cv2.cv.CV_HAAR_SCALE_IMAGE
)

# Draw a rectangle around the faces
for (x, y, w, h) in faces:
    cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)

# Display the resulting frame
cv2.imshow('Video', frame)

if cv2.waitKey(1) & 0xFF == ord('q'):
    break

video_capture.release()

cv2.destroyAllWindows()

video_capture.release()

cv2.destroyAllWindows()

I am using frontal_face_haarcascade.xml by opencv in python. I can detect faces in frame and then increase the count, but what's happening is that the count is increasing as the number of frames.So, even if 1 person was detected standing for 10 sec, it shows count as some '67'

How can I overcome this problem.