Write in Gstreamer pipeline from opencv in python

Question

I'm trying to stream some images form opencv using gstreamer and I got some issues with the pipeline. I'm new to gstreamer and opencv in general. I compiled opencv 3.2 with gstreamer for python3 on a raspberry pi 3. I have a little bash script that I use with raspivid

raspivid -fps 25 -h 720 -w 1080 -vf -n -t 0 -b 2000000 -o - | gst-launch-1.0 -v fdsrc ! h264parse ! rtph264pay config-interval=1 pt=96 ! gdppay ! tcpserversink host=192.168.1.27 port=5000

I wanted to translate this pipeline in order to use it from opencv and feed it images that my algorithm manipulates. I did some research and figured that I can use videoWriter with appsrc instead of fdsrc but I get the following error

GStreamer Plugin: Embedded video playback halted; module appsrc0 reported: Internal data flow error.

The python script that I came up with is the following by the way import cv2

cap = cv2.VideoCapture(0)
# Define the codec and create VideoWriter object
fourcc = cv2.VideoWriter_fourcc(*'MJPG')
out = cv2.VideoWriter('appsrc ! h264parse ! '
 'rtph264pay config-interval=1 pt=96 ! '
 'gdppay ! tcpserversink host=192.168.1.27 port=5000 ',
 fourcc, 20.0, (640, 480))
while cap.isOpened():
 ret, frame = cap.read()
 if ret:
 frame = cv2.flip(frame, 0)
 # write the flipped frame
 out.write(frame)
 if cv2.waitKey(1) & 0xFF == ord('q'):
 break
 else:
 break
# Release everything if job is finished
cap.release()
out.release()
cv2.destroyAllWindows()

Are there any errors in the pipeline? I don't understand the error. I already have a Python client that can read from the bash pipeline and the results are pretty good from the latency perspective and consumed resources.

Answer 1

Please add videoconvert after appsrc as you need to convert format of the video to display it on autovideosink or stream it using udpsink. It could be something like this:

video = cv2.VideoWriter('appsrc ! queue ! videoconvert ! video/x-raw ! omxh264enc ! video/x-h264 ! h264parse ! rtph264pay ! udpsink host=192.168.0.2 port=5000 sync=false',0,25.0,(640,480))

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