doc/PythonTutorial1_8py_source.html

import libjevois as jevois

import cv2

import numpy as np


## Simple example of image processing using OpenCV in Python on JeVois

#

# This module by default simply converts the input image to a grayscale OpenCV image, and then applies the Canny

# edge detection algorithm. Try to edit it to do something else (note that the videomapping associated with this

# module has grayscale image outputs, so that is what you should output).

#

# @author Laurent Itti

#

# @displayname Python Tutorial 1

# @videomapping GRAY 640 480 20.0 YUYV 640 480 20.0 JeVois PythonOpenCV

# @email itti\@usc.edu

# @address University of Southern California, HNB-07A, 3641 Watt Way, Los Angeles, CA 90089-2520, USA

# @copyright Copyright (C) 2017 by Laurent Itti, iLab and the University of Southern California

# @mainurl http://jevois.org

# @supporturl http://jevois.org/doc

# @otherurl http://iLab.usc.edu

# @license GPL v3

# @distribution Unrestricted

# @restrictions None

# @ingroup modules

class PythonTutorial1:

    # ###################################################################################################

    ## Process function with USB output

    def process(self, inframe, outframe):

        # Get the next camera image (may block until it is captured) and convert it to OpenCV GRAY:

        inimggray = inframe.getCvGRAY()


        # Detect edges using the Canny algorithm from OpenCV:

        edges = cv2.Canny(inimggray, 100, 200, apertureSize = 3)


        # Convert our GRAY output image to video output format and send to host over USB:

        outframe.sendCvGRAY(edges)