OpenCV (Open Source Computer Vision) is a powerful library used for computer vision tasks such as image and video processing, object detection, and recognition. While it is primarily known for its image processing capabilities, OpenCV also has the ability to write and save video files in the AVI format. In this article, we will explore the process of writing AVI files with OpenCV.
To begin, we need to import the necessary libraries. Along with OpenCV, we will also be using the NumPy library for array manipulation.
```
import cv2
import numpy as np
```
Next, we need to create a VideoWriter object. This object will handle the process of writing frames to the video file. It takes in several parameters such as the output file name, four-character code for the video codec, frames per second (fps), and frame size.
```
out = cv2.VideoWriter('output.avi', cv2.VideoWriter_fourcc(*'DIVX'), 30, (640, 480))
```
The four-character code is used to specify the video codec. Different codecs have different compression algorithms and settings, so it is important to choose the right one for your needs. In this case, we are using the DIVX codec, which is commonly used for AVI files. The next parameter is the fps, which determines the number of frames per second in the video. Finally, we specify the frame size, which in this example is set to 640x480 pixels.
Now, let's create a loop to capture frames from a video source and write them to the output file. Here, we are using a webcam as our video source, but you can also use a pre-recorded video file or any other video source.
```
cap = cv2.VideoCapture(0) # 0 for webcam, 1 for external camera
while True:
ret, frame = cap.read() # read frame from video source
out.write(frame) # write frame to output file
cv2.imshow('frame', frame) # display frame
if cv2.waitKey(1) == ord('q'): # press 'q' to quit
break
cap.release()
out.release()
cv2.destroyAllWindows()
```
In the above code, we use the `cap.read()` function to read frames from the video source. The `ret` variable returns a boolean value indicating whether the frame was successfully read or not, while the `frame` variable contains the actual frame data. We then use the `out.write()` function to write the frame to our output file. Finally, we use the `cv2.imshow()` function to display the frame on our screen and `cv2.waitKey()` to wait for a key press to break out of the loop.
Once the loop ends, we release the video capture and writer objects, and destroy any open windows using the `cv2.destroyAllWindows()` function.
And that's it! We have successfully written a video file in the AVI format using OpenCV. You can now play the output file using any media player that supports the AVI format.
In conclusion, OpenCV provides a simple and efficient way to write AVI files using its powerful video processing capabilities. With just a few lines of code, you can create your own video files and use them for various computer vision applications. So go ahead and give it a try!
