Hi, I am currently performing semantic segmentation in Python based on the demo example https://github.com/openvinotoolkit/open_model_zoo/blob/2021.3/demos/segmentation_demo/python/segment...
I am processing a pre-recorded video at 30fps and saving the results into a video with cv2.VideoWriter. I noticed that the video writing operation seems to be too slow to run smoothly at 30fps, in the sense that some frames in the input video are skipped and not read. If I use an input video with a lower fps (e.g. 15fps) everything works fine.
Since the example code is already using an async pipeline, is there any way that the reading and writing of the frames can be async? Or is there a way to improve the performance of the video writing process?
I am not too familiar on how the async pipeline works and if it can be modified, so I'm not sure on how to proceed
@Letty OMZ demos use OpenCV to process media files (for input and for output), which in its turn use various media backends available in the system (ffmpeg, microsoft media foundation, intel media sdk and so on). I do not know what is your target operating system and what media backend selected by OpenCV on your system, might be it is not optimal. Definitely, application could be written in more efficient way, but in this case you'll have to know how to implement asynchronous processing and how to use hardware acceleration for media decoding or encoding.
This thread will no longer be monitored since Vladimir_Dudnik had provided explanations and suggestions.
If you need any additional information from Intel, please submit a new question.