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USB Camera

The ARTIK 530, 710, and 1020 development boards support a UVC-compatible USB camera. Once you plug your USB camera into the USB port, check for recognition of the camera by using the command below.

dmesg | grep uvc

[839.428875] [c1] uvcvideo: Found UVC 1.00 device< unnamed >(046d:0825)
[839.523992] [c2] usbcore: registered new interface driver uvcvideo

The default USB camera device node should be /dev/video0. If more than one USB camera is plugged in, they will be identified as /dev/video0, /dev/video1.

OpenCV

OpenCV^® stands for Open Source Computer Vision. It provides C++, C, Python and Java^® interfaces and supports Windows^®, Linux^®, Mac^® OS, iOS^® and Android^®. In this programming guide, our sample code is implemented with OpenCV APIs.

Capture Still Image

Using Command Line

You can use the fswebcam utility to capture a still image from the webcam. The captured image can be saved as a PNG or JPEG file. The fswebcam package is not included in the default binary; install it by using this command.

Ubuntu:
apt install fswebcam
Fedora:
dnf install fswebcam

Usage is
fswebcam –r Resolution filename
for a USB camera. For example:

fswebcam –r 1280x720 image.jpg

--- Opening /dev/video0...
Trying source module v4l2...
/dev/video0 opened.
No input was specified, using the first.
--- Capturing frame...
Captured frame in 0.00 seconds.
--- Processing captured image...
Writing JPEG image to 'image.jpg'.

Using OpenCV C++ API

OpenCV supports C interfaces. However, one issue with the C interface is that developers have to manage memory manually. C++ support was intrduced from OpenCV 2.0 to help handle memory management and keep code concise.

To use OpenCV C++ APIs, install the OpenCV devel package and gcc compiler on your ARTIK board. The latter comes pre-installed with the latest versions of the ARTIK binary.

Ubuntu:
apt install libopencv-dev
Fedora:
dnf install opencv-devel
dnf install gcc-c++

An image is basically a matrix containing all the intensity values of the pixel points. Mat is the C++ class in OpenCV that acts as the basic image container. Mat has two parts: the matrix header (containing information such as the size of the matrix) and a pointer to the matrix containing the pixel values.

The VideoCapture class is provided for video capturing from video files, images sequences or cameras. For example:

VideoCapture cap(0);

The imwrite API saves an image to a specified file. Its API is:

bool  imwrite(const string& filename, InputArray img, const vector< int > & params = vector< int >() )

Details on the VideoCapture class and imwrite in particular can be found here.

Here is our C++ code takephoto.cpp:

#include "opencv2/opencv.hpp"

using namespace cv;

int main() {
  VideoCapture cap(100);  //open the default camera
  if (!cap.isOpened())  //check if we succeed
    return -1;

  Mat frame;                  
  cap >> frame;         //get a new frame from camera
  imwrite("image.jpg", frame);
  
  //the camera is deinitialized automatically in 
  //VideoCapture destructor
  return 0;
}

            

You may need to run apt install g++ if g++is not installed.

Then, compile the code with this command line.

g++ takephoto.cpp -o takephoto `pkg-config --cflags --libs opencv`

Run it with this command line.

./takephoto

A file named image.jpg will be generated under the current directory.

Using OpenCV Python

You can also use OpenCV Python bindings to take a still image. First, you need to manually install the OpenCV Python package on your ARTIK board.

Ubuntu:
apt install python-opencv
Fedora:
dnf install opencv-python

Here is our Python code takephoto.py. Its structure is the same as our C++ code.

import cv2

cap = cv2.VideoCapture(0)
filename = "image.jpg"

#Captures a single image and returns it in PIL format
ret, frame = cap.read()
cv2.imwrite(filename,frame)
cap.release()

            

The Python code:

Imports the OpenCV library
Connects to the video camera by using VideoCapture class
Captures a frame from the camera with its read() function
– VideoCapture::read() grabs, decodes, and returns the next video frame
Saves the captured frame into a file
Releases control over the camera.

Run the Python code from command line.

python takephoto.py

An image named image.jpg will be generated under the current directory.

Record Video

Using Command Line

ffmpeg is widely used to encode and decode video streams from a device or file. It also supports grabbing input streams from V4L2(Video4Linux2) devices. To install the ffmpeg package, use this command.

Ubuntu:
apt install ffmpeg
Fedora:
dnf install ffmpeg

To record a video clip, you can use a command line like the one in this example.

ffmpeg -f alsa -ac 2 -i hw:0 -f v4l2 -s 640x480 -i /dev/video0 -t 20 video.mpg

-f alsa  	Use ALSA for audio input  
-ac 2		Audio channel is Stereo (1 for Mono, 2 for Stereo)  
-i hw:0  	Input Audio Card is 0  
-f v4l2		Use V4L2 capture device  
-s 640x480	Resolution is 640 x 480

The input audio card number can be found from arecord . In the example above, we used the built-in microphone.

arecord -l

**** List of CAPTURE Hardware Devices ****
card 0: artikak4953 [artik-ak4953], device 0: Playback ak4953-AIF1-0 []
  Subdevices: 1/1
  Subdevice #0: subdevice #0
card 1: U0x46d0x825 [USB Device 0x46d:0x825], device 0: USB Audio [USB Audio]
  Subdevices: 1/1
  Subdevice #0: subdevice #0

Using OpenCV C++ APIs

You can also use OpenCV APIs to record video from a camera. For simple video outputs, we can use the OpenCV built-in VideoWriter class.

Note that OpenCV is mainly a computer vision library, and therefore only supports the .avi extension. The video file size is limited to 2GB. You can only create and expand a single video track inside the container; no audio or other track editing is supported.

Install gstreamer packages:

Ubuntu:
apt install gstreamer*
Fedora:
dnf install gstreamer*

Here is the C++ code videocapture.cpp

#include "opencv2/highgui/highgui.hpp"
#include <iostream>

using namespace cv;
using namespace std;

int main(int argc, char* argv[])
{
  VideoCapture cap(0); // open the video camera 0
  if (!cap.isOpened())
  {
    return -1;
  }

  //get the width of the video frame
  double dWidth = cap.get(CV_CAP_PROP_FRAME_WIDTH); 
  //get the height of the video frame
  double dHeight = cap.get(CV_CAP_PROP_FRAME_HEIGHT); 

  cout << "Frame Size = " << dWidth << "x" << dHeight << endl;

  Size frameSize(static_cast<int>(dWidth),
static_cast<int>(dHeight));

  //Initialize the VideoWriter object
  VideoWriter videoWriter("myvideo.avi", CV_FOURCC('P','I','M','1'), 20, frameSize, true);
  //If VideoWriter is not initialized successfully, exit the program
  if (!videoWriter.isOpened())
  {
     cout << "ERROR: Failed to write the video" << endl;
     return -1;
  }

  while (1)
  {
    Mat frame;

    bool bSuccess = cap.read(frame); // read a new frame from video
    if (!bSuccess)
    {
      cout << "ERROR: Cannot read a frame from video file" << endl;
      break;
    }

    //write the frame into the file
    videoWriter.write(frame);
   
 }

  return 0;
}

            

Compile it with this command line.

g++ videocapture.cpp -o videocapture `pkg-config --cflags --libs opencv`

Run it with this command line.

./videocapture

Using OpenCV Python

The Python code videocapture.py below records a 10-second video clip, and saves it into myvideo.avi under the current directory.

# Import Libraries
import numpy as np
import cv2

# Define variables
framerate = 20.0   # frames per second
videolength = 10    # length of video in seconds

# Grab Camera
cap = cv2.VideoCapture(0)

# Define the codec and create VideoWriter object
fourcc = cv2.cv.CV_FOURCC(*'XVID')
out = cv2.VideoWriter('myvideo.avi',fourcc, framerate, (640,480))

# Video part
for i in range(int(videolength*framerate)):
    if (cap.isOpened()):
        ret, frame = cap.read()
        if ret==True:
            out.write(frame)
        else:
            continue

# Release the camera and video file
cap.release()
out.release()

            

Launching the code from the command line will capture myvideo.avi.

python videocapture.py

Video Streaming

Streaming video from a USB camera connected to ARTIK is possible using the protocols described here.

Streaming with ARTIK as RTSP Server

You can stream a video with RTSP protocol over the network by using ffmpeg and ffserver.

Supported resolutions and frame rates for video streaming are:

VGA(640x480) : 30fps, 24fps, 15fps, 10fps and 5fps
HD(1280x720): 15fps, 10fps, and 5fps

Set up the ARTIK board as follows.

Configure ffserver with a server configuration file, such as this ffserver.conf file for VGA 30fps streaming.

Port 8090
BindAddress 0.0.0.0

RTSPPort 8091
RTSPBindAddress 0.0.0.0

MaxClients 1000
MaxBandwidth 10000
CustomLog -

<Feed feed1.ffm>
File /tmp/feed1.ffm
ACL Allow 127.0.0.1
</Feed>

<Stream test1.mp4>
Feed feed1.ffm
Format rtp
VideoFrameRate 30
VideoBitRate 5000
VideoSize 640x480
VideoQMin 3
VideoQMax 31
NoAudio
NoDefaults
</Stream>

            

Launch ffserver in the background.
ffserver -f ffserver.conf &
Run a stream feed with ffmpeg on the ARTIK board.
ffmpeg -f v4l2 -s 640x480 -r 30 -i /dev/video0 http://localhost:8090/feed1.ffm

Receive and Play Streaming Content

These instructions are for receiving and playing the video stream on a PC, not on the ARTIK board.

You can use media players like mplayer or VLC as the RTSP client to receive and play video streams.

Example using mplayer

mplayer rtsp://[IP Address]:8091/test1.mp4

Example using VLC Client

Go to File-> Open Network -> Network
Enter RTSP server IP address, port number and streaming content as set in the configuration file described previously
Click “Open” to launch the streaming content.

Streaming with OpenCV Python and Flask

In this code snippet, we will use OpenCV and Flask to implement live video streaming.

Flask is a micro web framework that provides native support for streaming. More details about Flask can be found here.

Flask streaming uses a technique where the server provides a response to a request in chunks. During streaming, each chunk replaces the previous one on the page, so it produces an animated effect in the browser window. We use multipart response to implement in-place updates, where each chunk in the stream is an image.

Prerequisite: Install Flask framework.

pip install flask

Here is our Python code livestream.py

from flask import Flask, Response
import cv2

class Camera(object):
  def __init__(self):
    self.cap = cv2.VideoCapture(0)

  def get_frame(self):
    ret, frame = self.cap.read()
    cv2.imwrite('stream.jpg',frame)
    return open('stream.jpg', 'rb').read()


app = Flask(__name__)

def gen(camera):
  while True:
    frame = camera.get_frame()
    yield (b'--frame\r\n'
      b'Content-Type: image/jpeg\r\n\r\n' + frame 
      + b'\r\n')

@app.route('/')
def video_feed():
  return Response(gen(Camera()),
    mimetype='multipart/x-mixed-replace;boundary=frame') 

if __name__ == '__main__':
  app.run(host='0.0.0.0', debug=True)

            

Run the code with this command line.

python livestream.py

* Running on http://0.0.0.0:5000/ (Press CTRL+C to quit)
* Restarting with stat
* Debugger is active!
* Debugger pin code: 647-240-038

From your host machine, launch a web browser and visit :5000 and you can view the streamed content.

Last updated on: Jun 22 2018, 8:56 PM