PythonSandbox_takephoto.py

import libjevois as jevois
import cv2
import numpy as np

## Simple example of image processing using OpenCV in Python on JeVois
#
# This module is here for you to experiment with Python OpenCV on JeVois.
#
# By default, we get the next video frame from the camera as an OpenCV BGR (color) image named 'inimg'.
# We then apply some image processing to it to create an output BGR image named 'outimg'.
# We finally add some text drawings to outimg and send it to host over USB.
#
# See http://jevois.org/tutorials for tutorials on getting started with programming JeVois in Python without having
# to install any development software on your host computer.
#
# @author Laurent Itti
# 
# @videomapping YUYV 352 288 30.0 YUYV 352 288 30.0 JeVois PythonSandbox
# @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 PythonSandbox:
    # ###################################################################################################
    ## Constructor
    def __init__(self):
        # Instantiate a JeVois Timer to measure our processing framerate:
        self.timer = jevois.Timer("sandbox", 100, jevois.LOG_INFO)
        self.frame = 0
        msg="detection"
        self.i = 1
        
    # ###################################################################################################
    ## Process function with USB output
    def process(self, inframe, outframe):
        # Get the next camera image (may block until it is captured) and here convert it to OpenCV BGR by default. If
        # you need a grayscale image instead, just use getCvGRAY() instead of getCvBGR(). Also supported are getCvRGB()
        # and getCvRGBA():
        self.timer.start()
        
        msg = "detection"
        test1 = inframe.getCvBGR()
        gray_img = inframe.getCvGRAY()
        face_cascade = cv2.CascadeClassifier('share/facedetector/haarcascade_frontalface_alt.xml')
        faces = face_cascade.detectMultiScale(gray_img, scaleFactor=1.1, minNeighbors=5);
        
        for (x, y, w, h) in faces:
            cv2.rectangle(test1, (x, y), (x+w, y+h), (0,255, 0), 2)
            jevois.sendSerial("face detected".format(self.frame));
            cv2.imwrite('modules/JeVois/PythonSandbox/training-data/'+ str(self.i) + ".jpg", gray_img[y:y +h, x:x + w])
            msg = "Coucou clic Photo"
            jevois.sendSerial("photo taken");
            self.frame += 1
            self.i += 1
        outimg = test1
        
        
            
        # Start measuring image processing time (NOTE: does not account for input conversion time):
        

        # Detect edges using the Laplacian algorithm from OpenCV:
        #
        # Replace the line below by your own code! See for example
        # - http://docs.opencv.org/trunk/d4/d13/tutorial_py_filtering.html
        # - http://docs.opencv.org/trunk/d9/d61/tutorial_py_morphological_ops.html
        # - http://docs.opencv.org/trunk/d5/d0f/tutorial_py_gradients.html
        # - http://docs.opencv.org/trunk/d7/d4d/tutorial_py_thresholding.html
        #
        # and so on. When they do "img = cv2.imread('name.jpg', 0)" in these tutorials, the last 0 means they want a
        # gray image, so you should use getCvGRAY() above in these cases. When they do not specify a final 0 in imread()
        # then usually they assume color and you should use getCvBGR() here.
        #
        # The simplest you could try is:
        #    outimg = inimg
        # which will make a simple copy of the input image to output.
        #outimg = cv2.Laplacian(inimg, -1, ksize=5, scale=0.25, delta=127)
                
        # Write a title:
        cv2.putText(outimg, msg, (3, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255,255,255),
                    1, cv2.LINE_AA)
        
        # Write frames/s info from our timer into the edge map (NOTE: does not account for output conversion time):
        fps = self.timer.stop()
        height, width, channels = outimg.shape # if outimg is grayscale, change to: height, width = outimg.shape
        cv2.putText(outimg, fps, (3, height - 6), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255,255,255), 1, cv2.LINE_AA)

        # Convert our BGR output image to video output format and send to host over USB. If your output image is not
        # BGR, you can use sendCvGRAY(), sendCvRGB(), or sendCvRGBA() as appropriate:
        outframe.sendCvBGR(outimg)