How to change video resolution in OpenCV in Python

In this article, we will describe how you can capture each frame from the video and also resize them according to your needs. What we will exactly do is take the video as input from the user and capture it frame by frame. Moreover, we run the video in the loop and save the image frames with certain names after resizing those frames.

Stepwise Implementation:

Step 1: Importing the libraries

Here, we are importing the cv2 library, the cv2 is the OpenCV package that helps us to call the imread(), startWindowThread(), namedWindow(), and imshow() functions respectively.

import cv2

Step 2: Define a video capture object

In this step, we will use the function VideoCapture() to get a video capture object for the camera. Here, you can use either your camera or directly upload the video from your system.

vidcap = cv2.VideoCapture(“#Define the video path”)

Step 3: Capture video frame by frame

Now, we will capture the length of the video for running the loop. Also, the video gets automatically closed once all the frames have been captured.

success,image = vidcap.read()

Step 4: Declare the variable 

Then, declare the variable, and count with the value 0. This variable will further be incremented while running the loop.

count = 0

Step 5: Creating a loop for running the video

Moreover, we create a while loop for running the video and saving all the frames from your video into your local system. 

while success:

Step 5.1: Capture video frame by frame

Next, we will read the video frame by frame for resizing the frames and saving them to your local computer.

  success,image = vidcap.read()

Step 5.2: Resizing the image frames

In this step, we have used resize() function with particular dimensions for which the image frames need to be set.

  resize = cv2.resize(image, (#x-axis dimensions, #y-axis dimensions))

Step 5.3: Saving the frames with certain names

Later on, we save the image frames we resize in the last step. Also, we give the frames certain names with the extensions.

  cv2.imwrite(“%04d.jpg” % count, resize)

Step 5.4:  Closing the video automatically once it gets over

Further, the waitKey() function is used for closing the video automatically once the video gets over.

  if cv2.waitKey(10) == 27:
     break

Step 5.5 Incrementing the variable by 1

Finally, we increment the value of the variable declared, count by 1.

  count += 1

Example:

In this example, we have used the video (link) from which we will extract certain frames, resize those frames and save them with the particular names on the local computer.

Output: