Solving the OpenCV GStreamer VideoWriter Write Hangs in a Python Multiprocessing Process

Solution Overview

To overcome the OpenCV VideoWriter hang issue in a Python multiprocessing process, we’ll employ a multi-step approach:

1. Update GStreamer to a compatible version.
2. Configure the video codec correctly.
3. Implement efficient multiprocessing using Python’s multiprocessing module.
4. Optimize system resource allocation.

Step 1: Update GStreamer to a Compatible Version

First, ensure you have a compatible GStreamer version installed. OpenCV’s VideoWriter is known to work seamlessly with GStreamer 1.14.x and 1.16.x. You can check your GStreamer version using the following command:

gst-inspect-1.0 --version

If your GStreamer version is outdated, update it using the following command (for Ubuntu-based systems):

sudo apt-get install libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev

Step 2: Configure the Video Codec Correctly

A correctly configured video codec is crucial for smooth video writing. We’ll focus on the H.264 codec, which is widely supported and efficient. Create a Four Character Code (FOURCC) for the H.264 codec:

fourcc = cv2.VideoWriter_fourcc(*'X264')

Next, define the video codec properties:

fps = 30.0
width = 640
height = 480
codec = cv2.VideoWriter_fourcc(*'X264')

Step 3: Implement Efficient Multiprocessing

Python’s multiprocessing module allows us to distribute tasks across multiple processes. To avoid synchronization issues, we’ll use the `Process` class and implement a queue-based approach to manage video frame writing:

import multiprocessing
import queue

# Create a queue to store video frames
frame_queue = multiprocessing.Manager().Queue()

# Define the video writing process
def write_video_process(frame_queue, video_file_path):
    video_writer = cv2.VideoWriter(video_file_path, codec, fps, (width, height))
    while True:
        try:
            frame = frame_queue.get(block=True, timeout=1)
            video_writer.write(frame)
        except queue.Empty:
            break
    video_writer.release()

# Create the video writing process
process = multiprocessing.Process(target=write_video_process, args=(frame_queue, 'output.mp4'))
process.start()

# Capture video frames and put them in the queue
while capture.read():
    frame_queue.put(frame)

# Signal the video writing process to stop
frame_queue.put(None)
process.join()

Step 4: Optimize System Resource Allocation

To ensure efficient system resource allocation, we’ll implement a few tweaks:

• Limit CPU usage**: Use the `taskset` command to limit CPU usage for the video writing process. This prevents other processes from competing for resources:

taskset -c 0-3 python script.py

• Assign sufficient memory**: Ensure the system has sufficient memory to handle the video writing process. You can use the `ulimit` command to set the maximum memory allocation:

ulimit -v 4096