【树莓派】人脸追踪（3）树莓派+OpenCV
http://v.youku.com/v_show/id_XNDQ5MDY1MDIwNA==.html?x&sharefrom=android&sharekey=b7528db30cdcbb34503808752618fb7d0
1、代码
import numpy as np
import cv2
from time import sleep
import RPi.GPIO as GPIO
GPIO.setmode(GPIO.BCM)
GPIO.setwarnings(False)
pan = 27
tilt = 17
GPIO.setup(tilt, GPIO.OUT) # white => TILT
GPIO.setup(pan, GPIO.OUT) # gray ==> PAN
def setServoAngle(servo, angle):
assert angle >=5 and angle <= 175
pwm = GPIO.PWM(servo, 50)
pwm.start(8)
dutyCycle = angle / 18. + 3.
pwm.ChangeDutyCycle(dutyCycle)
sleep(0.1)
pwm.stop()
faceCascade = cv2.CascadeClassifier('Cascades/haarcascade_frontalface_default.xml')
cap = cv2.VideoCapture(0)
cap.set(3,160) # set Width
cap.set(4,120) # set Height
AngleX=90
AngleY=90
setServoAngle(tilt, AngleX)
setServoAngle(pan, AngleY)
while True:
ret, img = cap.read()
#img = cv2.flip(img, -1)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.2,
minNeighbors=3,
minSize=(5, 5)
)
faceX=0
faceY=0
faceW=0
faceH=0
for (x,y,w,h) in faces:
if(w*h>faceW*faceH):
faceX=x
faceY=y
faceW=w
faceH=h
if(faceW*faceH>0):
cv2.rectangle(img,(faceX,faceY),(faceX+faceW,faceY+faceH),(255,0,0),2)
roi_gray = gray
roi_color = img
faceX=faceX+faceW/2
faceY=faceY+faceH/2
if(faceX>90):
AngleX-=1
if(faceX<70):
AngleX+=1
if(AngleX>140):
AngleX=140
if(AngleX<30):
AngleX=30
if(faceY>70):
AngleY-=1
if(faceY<50):
AngleY+=1
if(AngleY>140):
AngleY=140
if(AngleY<30):
AngleY=30
setServoAngle(tilt, AngleX)
setServoAngle(pan, AngleY)
cv2.imshow('video',img)
print(faceX)
print(faceY)
k = cv2.waitKey(30) & 0xff
if k == 27: # press 'ESC' to quit
break
cap.release()
cv2.destroyAllWindows()
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2、CascadeClassifier检测void CascadeClassifier::detectMultiScale( const Mat& image, vector<Rect>& objects,
double scaleFactor, int minNeighbors,
int flags, Size minObjectSize, Size maxObjectSize)
{
vector<int> fakeLevels;
vector<double> fakeWeights;
detectMultiScale( image, objects, fakeLevels, fakeWeights, scaleFactor,
minNeighbors, flags, minObjectSize, maxObjectSize, false );
}
参数意思：
1. const Mat& image：输入图像
2. vector& objects：输出的矩形向量组
3. double scaleFactor=1.1：这个是每次缩小图像的比例，默认是1.1
4. minNeighbors=3：匹配成功所需要的周围矩形框的数目，每一个特征匹配到的区域都是一个矩形框，只有多个矩形框同时存在的时候，才认为是匹配成功，比如人脸，这个默认值是3。
5. flags=0：可以取如下这些值：
CASCADE_DO_CANNY_PRUNING=1, 利用canny边缘检测来排除一些边缘很少或者很多的图像区域
CASCADE_SCALE_IMAGE=2, 正常比例检测
CASCADE_FIND_BIGGEST_OBJECT=4, 只检测最大的物体
CASCADE_DO_ROUGH_SEARCH=8 初略的检测
6. minObjectSize maxObjectSize：匹配物体的大小范围
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多谢分享，学习了。
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