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Ongoing Tests with Linux Streaming

canny opencv

Using Nvidia Jetson Nano live streaming from a THETA V. Processing done with Python3, OpenCV 4.4. Scroll down for code.


detect live

Running live on Jetson Nano with RICOH THETA Z1.

DetectNet applied to both single frame with SSD Mobilenet-v2 to assess accuracy and to live stream to assess framerate. Works good on both.

Video demo with Jetson Nano.

See Jetson Nano inference benchmarks.

Code is available in the at

There is super small text in the green box that says, "person". The system accurately detected the only person in the image.

It is 88.6 percent confident that I am a person. Nice.

detect person

Despite the distorted view of my feet, the program does detect the human form.

detect person

Even at night, in low-light conditions with me on the side of the shutter button, the program did detect me.

detect person

However, there were many frames where I was not detected.

To proceed, you will likely need a database of fisheye or equirectangular images to build your own model.

Sample Code

import jetson.inference
import jetson.utils

net = jetson.inference.detectNet("ssd-mobilenet-v2", threshold=0.5)
camera = jetson.utils.gstCamera(1280, 720, "/dev/video0")
display = jetson.utils.glDisplay()

while display.IsOpen():
    img, width, height = camera.CaptureRGBA()
    detections = net.Detect(img, width, height)
    display.RenderOnce(img, width, height)
    display.SetTitle("RICOH THETA Detection | Network {:.0f} FPS".format(net.GetNetworkFPS()))

OpenCV Python

canny demo

Works on live stream.

community opencv


  • install libuvc-theta
  • install libuv-theta-sample
  • install v4l2loopback
  • load kernel modules for v4l2loopback and verify that /dev/video0 or equivalent shows THETA stream
  • run Python script with cv2

Recommend you recompile OpenCV 4.4 from source code. May take 2.5 hours if you compile on the Nano.

Simple Python cv2 Test

Frame resize test.

import cv2

cap = cv2.VideoCapture(0)

# Check if the webcam is opened correctly
if not cap.isOpened():
    raise IOError("Cannot open webcam")

while True:
    ret, frame =
    frame = cv2.resize(frame, None, fx=0.25, fy=0.25, interpolation=cv2.INTER_AREA)
    cv2.imshow('Input', frame)

    c = cv2.waitKey(1)
    if c == 27:


Build OpenCV

One script to install OpenCV 4.3 is from AastaNV here.

The script I used is from mdegans here

Canny Edge Detection Test

import sys
import argparse
import cv2
import numpy as np

def parse_cli_args():
    parser = argparse.ArgumentParser()
    parser.add_argument("--video_device", dest="video_device",
                        help="Video device # of USB webcam (/dev/video?) [0]",
                        default=0, type=int)
    arguments = parser.parse_args()
    return arguments

# On versions of L4T previous to L4T 28.1, flip-method=2
# Use the Jetson onboard camera
def open_onboard_camera():
    return cv2.VideoCapture(0)

# Open an external usb camera /dev/videoX
def open_camera_device(device_number):
    return cv2.VideoCapture(device_number)

def read_cam(video_capture):
    if video_capture.isOpened():
        windowName = "main_canny"
        cv2.namedWindow(windowName, cv2.WINDOW_NORMAL)
        cv2.setWindowTitle(windowName,"RICOH THETA OpenCV Python Demo")
        showWindow=3  # Show all stages
        showHelp = True
        font = cv2.FONT_HERSHEY_PLAIN
        helpText="'Esc' to Quit, '1' for Camera Feed, '2' for Canny Detection, '3' for All Stages. '4' to hide help"
        showFullScreen = False
        while True:
            if cv2.getWindowProperty(windowName, 0) < 0: # Check to see if the user closed the window
                # This will fail if the user closed the window; Nasties get printed to the console
            ret_val, frame =;
            hsv=cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
            if showWindow == 3:  # Need to show the 4 stages
                # Composite the 2x2 window
                # Feed from the camera is RGB, the others gray
                # To composite, convert gray images to color. 
                # All images must be of the same type to display in a window
                frameRs=cv2.resize(frame, (640,360))
                vidBuf = np.concatenate((frameRs, cv2.cvtColor(hsvRs,cv2.COLOR_GRAY2BGR)), axis=1)
                vidBuf1 = np.concatenate( (cv2.cvtColor(blurRs,cv2.COLOR_GRAY2BGR),cv2.cvtColor(edgesRs,cv2.COLOR_GRAY2BGR)), axis=1)
                vidBuf = np.concatenate( (vidBuf, vidBuf1), axis=0)

            if showWindow==1: # Show Camera Frame
                displayBuf = frame 
            elif showWindow == 2: # Show Canny Edge Detection
                displayBuf = edges
            elif showWindow == 3: # Show All Stages
                displayBuf = vidBuf

            if showHelp == True:
                cv2.putText(displayBuf, helpText, (11,20), font, 1.0, (32,32,32), 4, cv2.LINE_AA)
                cv2.putText(displayBuf, helpText, (10,20), font, 1.0, (240,240,240), 1, cv2.LINE_AA)
            if key == 27: # Check for ESC key
                break ;
            elif key==49: # 1 key, show frame
                cv2.setWindowTitle(windowName,"Camera Feed")
            elif key==50: # 2 key, show Canny
                cv2.setWindowTitle(windowName,"Canny Edge Detection")
            elif key==51: # 3 key, show Stages
                cv2.setWindowTitle(windowName,"Camera, Gray scale, Gaussian Blur, Canny Edge Detection")
            elif key==52: # 4 key, toggle help
                showHelp = not showHelp
            elif key==44: # , lower canny edge threshold
                print ('Canny Edge Threshold Maximum: ',edgeThreshold)
            elif key==46: # , raise canny edge threshold
                print ('Canny Edge Threshold Maximum: ', edgeThreshold)
            elif key==74: # Toggle fullscreen; This is the F3 key on this particular keyboard
                # Toggle full screen mode
                if showFullScreen == False : 
                    cv2.setWindowProperty(windowName, cv2.WND_PROP_FULLSCREEN, cv2.WINDOW_FULLSCREEN)
                    cv2.setWindowProperty(windowName, cv2.WND_PROP_FULLSCREEN, cv2.WINDOW_NORMAL) 
                showFullScreen = not showFullScreen

     print ("camera open failed")

if __name__ == '__main__':
    arguments = parse_cli_args()
    print("Called with args:")
    print("OpenCV version: {}".format(cv2.__version__))
    print("Device Number:",arguments.video_device)
    if arguments.video_device==0:


Works on live stream with Jetpack 4.3, not 4.4.

open pose