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###############################################################################
#                                                                             #
# file:    3_frame_jump.py                                                    #
#                                                                             #
# authors: Andre Heil  - avh34                                                #
#          Jingyao Ren - jr386                                                #
#                                                                             #
# date:    December 1st 2015                                                  #
#                                                                             #
# brief:   This demonstrates how a we can use frame jumping to create a more  #
#          fluid image as we process only every four frames to find faces.    #
#                                                                             #
###############################################################################


### Imports ###################################################################

from picamera.array import PiRGBArray
from picamera import PiCamera

import time
import cv2
import os
import pygame


### Setup #####################################################################

os.putenv( 'SDL_FBDEV', '/dev/fb1' )

# Setup the camera
camera = PiCamera()
camera.resolution = ( 320, 240 )
camera.framerate = 30
rawCapture = PiRGBArray( camera, size=( 320, 240 ) )

fcounter = 0
facefind = 0

# Load a cascade file for detecting faces
face_cascade = cv2.CascadeClassifier( '/home/pi/opencv-2.4.9/data/lbpcascades/lbpcascade_frontalface.xml' ) 

t_start = time.time()
fps = 0

### Main ######################################################################

# Capture frames from the camera
for frame in camera.capture_continuous( rawCapture, format="bgr", use_video_port=True ):
    
    image = frame.array

    # Run the face detection algorithm every four frames
    if fcounter == 3:

        fcounter = 0

        # Look for faces in the image using the loaded cascade file
        gray = cv2.cvtColor( image, cv2.COLOR_BGR2GRAY )
        faces = face_cascade.detectMultiScale( gray )

        print "Found " + str( len( faces ) ) + " face(s)"
        
        if str( len( faces ) ) != 0:
            facefind = 1
            facess = faces
        else:
            facefind = 0

        # Draw a rectangle around every face
        for ( x, y, w, h ) in faces:
            cv2.rectangle( image, ( x, y ), ( x + w, y + h ), ( 200, 255, 0 ), 2 )
            cv2.putText( image, "Face No." + str( len( facess ) ), ( x, y ), cv2.FONT_HERSHEY_SIMPLEX, 0.5, ( 0, 0, 255 ), 2 )
            facess = faces
    
    else:
        if facefind == 1 and str( len( facess ) ) != 0:

            # Continue to draw the rectangle around every face
            for ( x, y, w, h ) in facess:
                cv2.rectangle( image, ( x, y ), ( x + w, y + h ), ( 200, 255, 0 ), 2 )
                cv2.putText( image, "Face No." + str( len( facess ) ), ( x, y ), cv2.FONT_HERSHEY_SIMPLEX, 0.5, ( 0, 0, 255 ), 2 )
                
    fcounter += 1
    

    # Calculate and show the FPS
    fps = fps + 1
    sfps = fps / ( time.time() - t_start )
    cv2.putText( image, "FPS : " + str( int( sfps ) ), ( 10, 10 ), cv2.FONT_HERSHEY_SIMPLEX, 0.5, ( 0, 0, 255 ), 2 )    
    
    cv2.imshow( "Frame", image )
    cv2.waitKey( 1 )

    # Clear the stream in preparation for the next frame
    rawCapture.truncate( 0 )