Live Streaming over USB on Ubuntu and Linux, NVIDIA Jetson

craig · August 28, 2020, 4:43pm

There is only thetauvc.c

libuvc-theta-sample/gst/thetauvc.c at master · ricohapi/libuvc-theta-sample · GitHub

BTW, I was able to compile OpenCV 4.4 on the Nano and use OpenCV with Python accessing the theta on /dev/video0. I’m not familiar with gstreamer and this may not be what you want.

I was also able to use gst-launch from the command line with /dev/video0.

I read this blog and the technique the author used for Python was with gstreamer and opencv.

This video has some information on my initial test

https://youtu.be/At5uMIMfBQY

I’ve since improved the OpenCV Python script performance with the recompile.

The test pipeline is:

$ gst-launch-1.0 -v v4l2src ! videoconvert ! videoscale ! video/x-raw,width=1000,height=500 ! xvimagesink

This is with gst-loopback running.

Also, cuda does appear to be working with OpenCV. I have not run these tests yet, but this looks quite useful.

github.com

opencv/opencv/blob/4.0.1/modules/python/test/test_cuda.py

#!/usr/bin/env python

'''
CUDA-accelerated Computer Vision functions
'''

# Python 2/3 compatibility
from __future__ import print_function

import numpy as np
import cv2 as cv

from tests_common import NewOpenCVTests

class cuda_test(NewOpenCVTests):
    def setUp(self):
        super(cuda_test, self).setUp()
        if not cv.cuda.getCudaEnabledDeviceCount():
            self.skipTest("No CUDA-capable device is detected")

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Now with Canny edge detection in real-time. Code sent to meetup registrants.

Update: Aug 29

I’m having some problems with the nvidia-inference demos streaming from the THETA.

Normal webcam works. I’m trying to reduce the THETA 4k output to 2k, but can’t figure how to do this. The camera does support streaming at 2k, but I’m not sure how to force it to use the 2k stream for initial testing

Update Aug 29 night

I can now get a 2K stream to /dev/video0

$ v4l2-ctl --list-formats-ext
ioctl: VIDIOC_ENUM_FMT
	Index       : 0
	Type        : Video Capture
	Pixel Format: 'YU12'
	Name        : Planar YUV 4:2:0
		Size: Discrete 1920x960
			Interval: Discrete 0.033s (30.000 fps)

$ v4l2-ctl --list-devices
Dummy video device (0x0000) (platform:v4l2loopback-000):
	/dev/video0

Update Aug 30 morning

I have /dev/video0 working smoothly on x86 with v4l2loopback thanks to @Yu_You submission on GitHub. I added this and the following info to the meetup early access documentation:

video demo and code for DetectNet running on Nvidia Jetson Nano with Z1 using live stream. Good object detection of moving person in real-time
video demo and code for Canny edge detection with Python cv2 module. In real-time with minimal lag
explanation and code snippet to change video resolution from 4K to 2K for testing on Nano

Link to sign up for the meetup is at the Linux Streaming Site. Once you register for the meetup, you’ll see a page immediately with a link to early-access documentation and code. We’re not trying to sell you anything. We’re gating the content so that we can show results to our sponsor, RICOH. This helps us to secure sponsor budget to continue working with the community and produce informal documentation. If you miss the meetup, we’ll put the documentation up on the site in a week or two.

DetectNet running at 23fps. Accurate identification of person and TV.

Update Sept 4 - morning

video demo of DetectNet

x86 test using guvcview

Update Sept 4, 2020
Current plan in order of priority

publish meetup-specific documentation and technical QA to people that registered for documentation. Likely next week.
retest gphoto2 on x86 or Nano (Ubuntu) with THETA USB API based on this discussion, Test gp Python module for easier access of THETA USB API from inside of Python programs
install separate SSD on x86 and retest gstreamer and graphics system with hardware acceleration and resolution at 4K and 2K
- if successful, install ROS on x86

install ROS on Jetson Nano, ref, run basic tests with tutorial