樹莓派-人臉識别資料收集

使用樹莓派進行簡易人臉識别：http://blog.csdn.net/jireren/article/details/52167791#comments

Imports

from picamera.array import PiRGBArray

from picamera import PiCamera

from functools import partial

import multiprocessing as mp

import cv2

import os

import time

Setup

os.putenv( ‘SDL_FBDEV’, ‘/dev/fb0’ )

resX = 320

resY = 240

cx = resX / 2

cy = resY / 2

os.system( “echo 0=150 > /dev/servoblaster” )

os.system( “echo 1=150 > /dev/servoblaster” )

xdeg = 150

ydeg = 150

Setup the camera

camera = PiCamera()

camera.resolution = ( resX, resY )

camera.framerate = 60

Use this as our output

rawCapture = PiRGBArray( camera, size=( resX, resY ) )

The face cascade file to be used

face_cascade = cv2.CascadeClassifier(‘/home/pi/opencv-2.4.9/data/lbpcascades/lbpcascade_frontalface.xml’)

t_start = time.time()

fps = 0

Helper Functions

def get_faces( img ):

gray = cv2.cvtColor( img, cv2.COLOR_BGR2GRAY )
faces = face_cascade.detectMultiScale( gray )

return faces, img
           

def draw_frame( img, faces ):

global xdeg
global ydeg
global fps
global time_t

# Draw a rectangle around every face
for ( x, y, w, h ) in faces:

    cv2.rectangle( img, ( x, y ),( x + w, y + h ), ( 200, 255, 0 ), 2 )
    cv2.putText(img, "Face No." + str( len( faces ) ), ( x, y ), cv2.FONT_HERSHEY_SIMPLEX, 0.5, ( 0, 0, 255 ), 2 )

    tx = x + w/2
    ty = y + h/2

    if   ( cx - tx > 15 and xdeg <= 190 ):
        xdeg += 1
        os.system( "echo 0=" + str( xdeg ) + " > /dev/servoblaster" )
    elif ( cx - tx < -15 and xdeg >= 110 ):
        xdeg -= 1
        os.system( "echo 0=" + str( xdeg ) + " > /dev/servoblaster" )

    if   ( cy - ty > 15 and ydeg >= 110 ):
        ydeg -= 1
        os.system( "echo 1=" + str( ydeg ) + " > /dev/servoblaster" )
    elif ( cy - ty < -15 and ydeg <= 190 ):
        ydeg += 1
        os.system( "echo 1=" + str( ydeg ) + " > /dev/servoblaster" )

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

cv2.imshow( "Frame", img )
cv2.waitKey( 1 )
           

Main

if name == ‘main‘:

pool = mp.Pool( processes=4 )
fcount = 0

camera.capture( rawCapture, format="bgr" )  

r1 = pool.apply_async( get_faces, [ rawCapture.array ] )    
r2 = pool.apply_async( get_faces, [ rawCapture.array ] )    
r3 = pool.apply_async( get_faces, [ rawCapture.array ] )    
r4 = pool.apply_async( get_faces, [ rawCapture.array ] )    

f1, i1 = r1.get()
f2, i2 = r2.get()
f3, i3 = r3.get()
f4, i4 = r4.get()

rawCapture.truncate( 0 )    

for frame in camera.capture_continuous( rawCapture, format="bgr", use_video_port=True ):
    image = frame.array

    if   fcount == 1:
        r1 = pool.apply_async( get_faces, [ image ] )
        f2, i2 = r2.get()
        draw_frame( i2, f2 )

    elif fcount == 2:
        r2 = pool.apply_async( get_faces, [ image ] )
        f3, i3 = r3.get()
        draw_frame( i3, f3 )

    elif fcount == 3:
        r3 = pool.apply_async( get_faces, [ image ] )
        f4, i4 = r4.get()
        draw_frame( i4, f4 )

    elif fcount == 4:
        r4 = pool.apply_async( get_faces, [ image ] )
        f1, i1 = r1.get()
        draw_frame( i1, f1 )

        fcount = 0

    fcount += 1

    rawCapture.truncate( 0 )
           

上述程式用到的相關庫：

1）python基礎：http://www.crifan.com/files/doc/docbook/python_beginner_tutorial/release/html/python_beginner_tutorial.html#one_figure_entry_python

2）picamera庫： http://picamera.readthedocs.io/en/release-1.12/api_array.html

3）Python 多程序 multiprocessing.Pool類詳解：http://blog.csdn.net/seetheworld518/article/details/49639651

4）htop 使用：http://www.open-open.com/lib/view/open1417612210323.html

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