OpenCV 3 Computer Vision with Python Cookbook

How to do it...

The steps for this recipe are:

1. First, let's create a VideoCapture object and obtain the total number of frames:

import cv2capture = cv2.VideoCapture('../data/drop.avi')frame_count = int(capture.get(cv2.CAP_PROP_FRAME_COUNT))print('Frame count:', frame_count)

2. Get the total number of frames:

print('Position:', int(capture.get(cv2.CAP_PROP_POS_FRAMES)))_, frame = capture.read()cv2.imshow('frame0', frame)

3. Note that the capture.read method advances the current video position one frame forward. Get the next frame:

print('Position:', capture.get(cv2.CAP_PROP_POS_FRAMES))_, frame = capture.read()cv2.imshow('frame1', frame)

4. Let's jump to frame position 100:

capture.set(cv2.CAP_PROP_POS_FRAMES, 100)print('Position:', int(capture.get(cv2.CAP_PROP_POS_FRAMES))) ...