OpenCV VideoCapture RTMP

OpenCV is a widely-used computer vision library that provides developers with many useful tools for image and video processing. One of such tools is the VideoCapture class, which loads and reads video data from many sources, including local files, web cameras, and IP cameras. In this article, we'll discuss how to use OpenCV's VideoCapture class to stream video from an RTMP server.

RTMP (Real-Time Messaging Protocol) is a streaming protocol that is commonly used for live streaming video over the internet. It is supported by many popular video streaming platforms, such as Facebook, Twitch, and YouTube. To stream video from an RTMP server using OpenCV, we need the following:

• An RTMP server URL and stream key.
• OpenCV installed on our system.
• FFmpeg installed on our system.

First, let's create a VideoCapture object and set its properties. We'll set the backend to FFMPEG, and the URL to our RTMP server's URL with the stream key appended to it.

import cv2

url = "rtmp://your.server.url:1935/stream_key"
cap = cv2.VideoCapture(url)

cap.set(cv2.CAP_PROP_FOURCC, cv2.VideoWriter_fourcc('H', '2', '6', '4'))
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)

In the above code, we are setting the FourCC codec to H.264, and the video frame size to 1280x720. These properties can be tweaked to match the RTMP server's requirements.

Next, we'll define a loop to continuously read frames from the RTMP stream, process them and display them on the screen.

while True:
    # Read a frame from the stream
    ret, frame = cap.read()

    if not ret:
        break

    # Process the frame
    # ...

    # Display the frame
    cv2.imshow('frame', frame)

    # Exit on ESC
    if cv2.waitKey(1) == 27:
        break

# Release resources
cap.release()
cv2.destroyAllWindows()

In the loop, we read frames from the stream using the read() method of the VideoCapture object. We check the return value of this method to make sure that a frame was successfully read. If the return value is False, it means that the end of the stream has been reached or an error has occurred.

Next, we can process the frame to perform various operations on it, such as filtering, feature detection, or object tracking. After processing, we display the frame on the screen using OpenCV's imshow() function.

Finally, we check for the user pressing the ESC key to exit the loop. After exiting the loop, we must release the resources used by the VideoCapture object and destroy any OpenCV windows that were created.

In summary, OpenCV's VideoCapture class provides a simple and efficient way to stream video from an RTMP server. By setting its properties, we can configure the stream to match the server's requirements, and by processing the frames, we can perform various computer vision tasks on the video data.