In this post, I had found a bug in nvv4l2decoder for certain YUV cameras as confirmed by @DaneLLL in a response. I figure it was better to start a new issue for this rather than post on a page for a different issue.
I was told that release 32.4.3 would fix the issue. I noticed today, that 32.4.3 was released and I was excited to try it. Unfortunately, the same issue seems to persist. The output of
cat /etc/nv_tegra_release after
# R32 (release), REVISION: 4.3, GCID: 21589087, BOARD: t210ref, EABI: aarch64, DATE: Fri Jun 26 04:38:25 UTC 2020
The pipeline I tried was:
gst-launch-1.0 v4l2src device=/dev/video2 ! image/jpeg, width=1280, height=720, format=MJPG ! nvv4l2decoder mjpeg=true ! nvvidconv ! videoconvert ! xvimagesink
These are the two cameras I have been trying for this:
- I think this is it. At least the module number is the same as what I have, but mine looks slightly different on the front.
- And this one. I’ve had this work sometimes with the above pipeline, but I’ve been mainly getting the following error which is not happening for the other camera:
Pipeline is live and does not need PREROLL ... Setting pipeline to PLAYING ... New clock: GstSystemClock NvMMLiteOpen : Block : BlockType = 277 NVMEDIA: Reading vendor.tegra.display-size : status: 6 NvMMLiteBlockCreate : Block : BlockType = 277 nvbuf_utils: Invalid memsize=0 NvBufferCreateEx with memtag 5376 failed ERROR: from element /GstPipeline:pipeline0/nvv4l2decoder:nvv4l2decoder0: Failed to allocate required memory. Additional debug info: /dvs/git/dirty/git-master_linux/3rdparty/gst/gst-v4l2/gst-v4l2/gstv4l2videodec.c(1572): gst_v4l2_video_dec_handle_frame (): /GstPipeline:pipeline0/nvv4l2decoder:nvv4l2decoder0: Buffer pool activation failed Execution ended after 0:00:00.462404369 Setting pipeline to PAUSED ... Setting pipeline to READY ... Setting pipeline to NULL ... Freeing pipeline ...
This link has the original file I provided to find a fix for nvv4l2decoder, but my issue is basically the same where the color is all over the place and the rest of the image is in grayscale. The file was captured using the first camera link that I gave above.