I am working on a school project which is related to Image Processing using OpenCV Python and Raspberry Pi 3.

The hardware of Raspberry Pi 3 cannot handle the video from camera consecutively, therefore I'm thinking about only capture a picture after every 5 seconds from the camera and use it to recognize what I need, then continue.

I did some research on the internet and found a function called time.sleep(5), however this function only pause the camera 5 seconds and then continue.

Can anyone help me to solve my problem. Thank you so much. Sorry for my bad English, here is my code so far. In my code, I use a video to test first, then when figure out the solution, I will apply on camera.

import cv2
import numpy as np
import time

headcc = cv2.CascadeClassifier('lib/heads_cascade.xml')
cap = cv2.VideoCapture('image/hockey_game.avi')

def video():
    ret, frame = cap.read()

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

    head = headcc.detectMultiScale(frame, 1.2, 2, 0 , (20, 20), (40, 40))

    print type(head)
    print head
    print head.shape
    print "Number of heads detected: " + str(head.shape[0])


    if len(head) > 0:
        for (x, y, w, h) in head:
            cv2.rectangle(frame, (x,y), (x+w, y+h), (0, 255, 255), 1)

    cv2.rectangle(frame, ((0,frame.shape[0] -25)),(270, frame.shape[0]), (255,255,255), -1)
    cv2.putText(frame, "Number of head detected: " + str(head.shape[0]), (0,frame.shape[0] -10), cv2.FONT_HERSHEY_TRIPLEX, 0.5,  (0,0,0), 1)

    cv2.namedWindow('Camera',cv2.WINDOW_NORMAL)
    cv2.imshow('Camera',frame)


while(cap.isOpened()):
    video()
    time.sleep(5)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()

Update March 15th, 2018: Thanks to comment from Joe, I have found the way to skip frames. However, the program still cannot know whether the video ends, and also the fps code still appear 0.0. So if there is any help for these errors, I will really appreciate. Here is the code so far:

import cv2
import numpy as np
import time

headcc = cv2.CascadeClassifier('lib/heads_cascade.xml')
cap = cv2.VideoCapture('image/hockey_game.avi')
fps = cap.get(cv2.CAP_PROP_POS_FRAMES)

def video():
    ret, frame = cap.read()

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

    head = headcc.detectMultiScale(frame, 1.2, 2, 0 , (20, 20), (40, 40))

    # print type(head)
    # print head
    # print head.shape
    print "Number of heads detected: " + str(head.shape[0])

    if len(head) > 0:
        for (x, y, w, h) in head:
            cv2.rectangle(frame, (x,y), (x+w, y+h), (0, 255, 255), 1)

    # cv2.rectangle(frame, ((0,frame.shape[0] -25)),(270, frame.shape[0]), (255,255,255), -1)
    # cv2.putText(frame, "Number of head detected: " + str(head.shape[0]), (0,frame.shape[0] -10), cv2.FONT_HERSHEY_TRIPLEX, 0.5,  (0,0,0), 1)

    cv2.namedWindow('Camera',cv2.WINDOW_NORMAL)
    cv2.imshow('Camera',frame)


while(cap.isOpened()):
    video()
    cf = cap.get(cv2.CAP_PROP_POS_FRAMES) - 1
    cap.set(cv2.CAP_PROP_POS_FRAMES, cf+50)
    # cv2.setTrackbarPos("pos_trackbar", "Frame Grabber", 
int(cap.get(cv2.CAP_PROP_FPS)))
    time.sleep(2)
    if (cv2.waitKey(1) & 0xFF == ord('q')):
        break

print fps
cap.release()
cv2.destroyAllWindows()