Reading every nth frame from VideoCapture in OpenCV

I've had success in Python 3 using a simple counter and setting the capture to that counter's frame, as follows:

import cv2

cap = cv2.VideoCapture('XYZ.avi')
# For streams:
#   cap = cv2.VideoCapture('rtsp://url.to.stream/media.amqp')
# Or e.g. most common ID for webcams:
#   cap = cv2.VideoCapture(0)
count = 0

while cap.isOpened():
    ret, frame = cap.read()

    if ret:
        cv2.imwrite('frame{:d}.jpg'.format(count), frame)
        count += 30 # i.e. at 30 fps, this advances one second
        cap.set(cv2.CAP_PROP_POS_FRAMES, count)
    else:
        cap.release()
        break

I've tried to find a way to make this a little more pythonic using a with statement but I don't believe the CV2 library has been updated for it.

I encountered the same problem. All i did was this:

import cv2

vs = cv2.VideoCapture("<path of your video>.mp4")

print("Showing frames...")
c=1
while True:

    grabbed, frame = vs.read()
    if c%5==0:
        cv2.imshow('Frame',frame)
        cv2.waitKey(1)
    c+=1

vs.release()

I'm afraid there's not much you can do and it's not just a shortcoming of OpenCV. You see, modern video codecs, are, generally, complex beasts. To get a higher compression rate the encoding of a frame is often dependent on previous and sometimes even successive frames.

So, most of the time you have to decode frames before the desired one even if you don't need them.

There are rather non-trivial tricks to specifically encode a video file, so that it would be cheap to get every Nth frame, but it's not feasible in general case.

That said, you can try the seeking functionality OpenCV provides (see OpenCV Seek Function/Rewind). It may (as well as may not) work faster depending on the circumstances. However, personally, I wouldn't bet on it.

I got it to work in Python... See below for two sample use cases and some caveats.

# First, import some packages

import cv2
import math
import numpy as np

# Make sure that the print function works on Python 2 and 3
from future import print_function

# Capture every n seconds (here, n = 5) 

#################### Setting up the file ################
videoFile = "Jumanji.mp4"
vidcap = cv2.VideoCapture(videoFile)
success, image = vidcap.read()

#################### Setting up parameters ################

seconds = 5
fps = vidcap.get(cv2.CAP_PROP_FPS) # Gets the frames per second
multiplier = fps * seconds

#################### Initiate Process ################

while success:
    frameId = int(round(vidcap.get(1))) #current frame number, rounded b/c sometimes you get frame intervals which aren't integers...this adds a little imprecision but is likely good enough
    success, image = vidcap.read()

    if frameId % multiplier == 0:
        cv2.imwrite("FolderSeconds/frame%d.jpg" % frameId, image)
        
vidcap.release()
print("Complete")

# Alternatively, capture every n frames (here, n = 10)


#################### Setting up the file ################
videoFile = "Jumanji.mp4"
vidcap = cv2.VideoCapture(videoFile)
success, image = vidcap.read()

#################### Setting up parameters ################

#OpenCV is notorious for not being able to good to 
# predict how many frames are in a video. The point here is just to 
# populate the "desired_frames" list for all the individual frames
# you'd like to capture. 

fps = vidcap.get(cv2.CAP_PROP_FPS)
est_video_length_minutes = 3         # Round up if not sure.
est_tot_frames = est_video_length_minutes * 60 * fps  # Sets an upper bound # of frames in video clip

n = 5                             # Desired interval of frames to include
desired_frames = n * np.arange(est_tot_frames) 


#################### Initiate Process ################

for i in desired_frames:
    vidcap.set(1, i-1)                      
    success, image = vidcap.read(1)         # image is an array of array of [R,G,B] values
    frameId = vidcap.get(1)                # The 0th frame is often a throw-away
    cv2.imwrite("FolderFrames/frame%d.jpg" % frameId, image)

vidcap.release()
print("Complete")

That's pretty much it.

---

Some unfortunate caveats... depending on your version of `opencv` (this is built for `opencv` V3), you may need to set the fps variable differently. See [here][1] for details. To find out your version, you can do the following:

major_ver, minor_ver, subminor_ver = cv2.__version__.split('.')
print(major_ver)