I’m having the same error message under python. I’ve been using OpenCV4Tegra. I’m trying to figure out how to set Gstreamer in CV4Tegra
UPDATE: From the looks of other comment threads, Nvidia doesn’t provide Gstreamer with CV4Tegra. I’m installing regular old 3.2 for now using the Jetsonhacks script as a starter, with GStreamer enabled (in the script it’s disabled by default). But from the looks of this thread, https://devtalk.nvidia.com/default/topic/936870/jetson-tx1/opencv4tegra-vs-opencv3-1-w-cuda/ , the Tegra optimised CV is 10x faster.
UPDATE3: I’m seeing current chatter about the bug, so it’s still outstanding. It looks like I’m going to have to work on my prototype under CV3.2 until I can order in a camera that works with the Tegra optimized opencv.
Incidentally, the program I’m trying to get running on my TX2 worked on my Ubuntu 16.04 desktop with Opencv3.2.
Default Opencv4Tegra doesn’t enable GStreamer support, but you can build one from source:
This page will guide you to do this: http://dev.t7.ai/jetson/opencv/
Please remember to open onboard camera with nvcamerasrc. V4l2 is for USB-Camera.
Thanks for sharing this.
However, even after boosting my TX2 with jetson_clocks, I only get (2.5 - 2.6 fps) with yolo.weights model (mostly GPU limited as showed by tegrastats).
I have also added cuda arch 6.2 in Makefile and I am using opencv-3.3.0 compiled for TX2.
Do you have higher rates ?
I also only get 2~3 fps on my TX2 with the regular yolo model/weights. And I can get 16~17 fps if I run the tiny yolo. I’ve shared my experience in this post: [url]https://jkjung-avt.github.io/yolov2/[/url]
Yes i know. But i want to run it with the onboard cam.
But as i was told OpenCV 3.3.1 that comes with JetPack 3.2 does not support gstream. Is that correct?