opencv / opencv/opencv-python

Error while using GStream and OpenCV

Open
#1,036 0 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Dominant language
Python
Stars
5.4k
Forks
1k
Avg merge
22h 17m
Merged PRs (30d)
3

Description

Expected behaviour

The idea is to use GStream with OpenCV to compress a video.

Actual behaviour

The code raises an error because of the pipeline

Steps to reproduce
  • operating system: ubuntu 20.04
  • opencv-python version 4.20

My code is:
`compressed_video_path = os.path.join(picture_path, f"{datetime.datetime.now()}.mp4")

        gst_pipeline = (
            f"appsrc format=GST_APP_FORMAT_TIME ! videoconvert ! x264enc ! mp4mux ! filesink location={compressed_video_path}"
        )


        recorded_video = cv2.VideoWriter(gst_pipeline, 
                                        cv2.CAP_GSTREAMER, 
                                        0,  
                                        self.camera_fps, 
                                        (self.frame_size[1], self.frame_size[0]))

        if not recorded_video.isOpened():
            raise ValueError("Error!!!")

        for frame in frames_to_compress:
            recorded_video.write(frame)

        recorded_video.release()   

        rospy.loginfo(f"Compressed video saved in {compressed_video_path}.")`

And when calling the ros service involved, I have the error "Error!!!"

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by reproducing the shown cv2.VideoWriter call on Ubuntu 20.04 with the stated opencv-python version and GStreamer pipeline. Check why recorded_video.isOpened() fails and compare the pipeline requirements with the packaged OpenCV build. Done means identifying the cause and documenting a verified compatible configuration or a clearly reproducible limitation.

Written by the indexing model from the issue text.

Assessment

Tech stack
opencv, python
Domain
computer-vision
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.