Extract Images from Video Using OpenCV in Python

Tips and Traps¶

Most videoes have a FPS of 24. Some videos have higher FPS (e.g., 30 or 60) so that they can capture motions better. A record video on a computer has a FPS of the refresh rate of the monitor, which is usually 60. You can get the FPS of a video using OpenCV in Python.

Installation¶

Install OpenCV for Python following instructions at http://www.legendu.net/misc/blog/tips-on-opencv/#installation.

import numpy as np
from PIL import Image
import cv2

Download the big buck bunny video.

!wget --no-check-certificate https://www.sample-videos.com/video123/mp4/720/big_buck_bunny_720p_5mb.mp4 -O bunny.mp4

--2022-05-21 17:15:54--  https://www.sample-videos.com/video123/mp4/720/big_buck_bunny_720p_5mb.mp4
Resolving www.sample-videos.com (www.sample-videos.com)... 103.145.51.95
Connecting to www.sample-videos.com (www.sample-videos.com)|103.145.51.95|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 5253880 (5.0M) [video/mp4]
Saving to: ‘bunny.mp4’

bunny.mp4           100%[===================>]   5.01M  2.11MB/s    in 2.4s    

2022-05-21 17:15:58 (2.11 MB/s) - ‘bunny.mp4’ saved [5253880/5253880]

import cv2

vidcap = cv2.VideoCapture("bunny.mp4")
vidcap.get(cv2.CAP_PROP_FPS)

25.0

You can get total number of frames in a video using the following Python code.

vidcap.get(cv2.CAP_PROP_FRAME_COUNT)

739.0

cv2.VideoCapture.read returns a tuple of (bool, numpy.ndarray). The returned numpy array is the BGR representation of the frame/image.

success, arr = vidcap.read()

The first value of the returned tuple is a flag indicating whether the read success.

success

True

The second value of the returned tuple is a nump array with the dimension (image_height, image_width, 3).

arr

array([[[ 46, 112, 104],
        [ 31,  97,  89],
        [ 21,  92,  83],
        ...,
        [251, 223, 205],
        [251, 223, 205],
        [251, 223, 205]],

       [[ 44, 110, 102],
        [ 30,  96,  88],
        [ 22,  93,  84],
        ...,
        [251, 223, 205],
        [251, 223, 205],
        [251, 223, 205]],

       [[ 38, 104,  96],
        [ 26,  92,  84],
        [ 26,  97,  88],
        ...,
        [251, 223, 205],
        [251, 223, 205],
        [251, 223, 205]],

       ...,

       [[ 43, 131, 138],
        [ 57, 145, 152],
        [ 70, 153, 161],
        ...,
        [ 24, 117, 109],
        [ 27, 135, 116],
        [ 46, 154, 135]],

       [[ 54, 145, 151],
        [ 67, 158, 164],
        [ 72, 160, 167],
        ...,
        [ 27, 115, 108],
        [ 25, 128, 110],
        [ 46, 149, 131]],

       [[ 62, 153, 159],
        [ 68, 159, 165],
        [ 70, 158, 165],
        ...,
        [ 33, 121, 114],
        [ 28, 131, 113],
        [ 42, 145, 127]]], dtype=uint8)

The numpy array is the BGR (instead of RGB) representation of the image, which means that you have to flip the last dimension of the numpy array so that it can loaded using the Pillow library correctly.

Image.fromarray(np.flip(arr, 2))

<PIL.Image.Image image mode=RGB size=1280x720>

Extract PNG images from the downloaded video every 5 frames.

import cv2

vidcap = cv2.VideoCapture("bunny.mp4")
count = 0
while True:
    success, image = vidcap.read()
    if not success:
        break
    if count % 5 == 0:
        cv2.imwrite(f"frame_{'{:0>3}'.format(count)}.png", image)
    count += 1

Use Pillow to Handle FLI¶

If you are dealing with a FLI animation file, you can also use the Python package Pillow to extract frames from it. For more details, please refer to ImageSequence Module.

from PIL import Image, ImageSequence

im = Image.open("animation.fli")

index = 0
for frame in ImageSequence.Iterator(im):
    frame.save("frame%d.png" % index)
    index += 1

Extract Images from Video Using OpenCV in Python

Tips and Traps¶

Installation¶

Use Pillow to Handle FLI¶

References¶