my raspberry pi freezes while face tracking using openCV and servoblaster

Question

I'm trying to track face with Pan and tilt motion, using servoblaster and opencv, i followed this tutorial if anyone is intrested..

it runs perfectly but after few seconds camera freezes and it stops responding and freezes completely. can any one help ? here is the code:

from multiprocessing import Process, Queue
import time
import cv2
# Upper limit
_Servo1UL = 250
_Servo0UL = 230
# Lower Limit
_Servo1LL = 75
_Servo0LL = 70
ServoBlaster = open('/dev/servoblaster', 'w')
webcam = cv2.VideoCapture(0)
webcam.set(cv2.cv.CV_CAP_PROP_FRAME_WIDTH, 320) 
webcam.set(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT, 240) 
frontalface = cv2.CascadeClassifier("haarcascade_frontalface_alt2.xml") 
profileface = cv2.CascadeClassifier("haarcascade_profileface.xml") 
face = [0,0,0,0] 
Cface = [0,0] 
lastface = 0 
Servo0CP = Queue() 
Servo1CP = Queue() 
Servo0DP = Queue() 
Servo1DP = Queue()
Servo0S = Queue()
Servo1S = Queue()
def P0(): 
 speed = .1 
 _Servo0CP = 99 
 _Servo0DP = 100
 while True:
 time.sleep(speed)
 if Servo0CP.empty(): 
 Servo0CP.put(_Servo0CP)
 if not Servo0DP.empty():
 _Servo0DP = Servo0DP.get()
 if not Servo0S.empty():
 _Servo0S = Servo0S.get()
 speed = .1 / _Servo0S
 if _Servo0CP < _Servo0DP:
 _Servo0CP += 1
 Servo0CP.put(_Servo0CP)
 ServoBlaster.write('0=' + str(_Servo0CP) + '\n') #
 ServoBlaster.flush() #
 if not Servo0CP.empty():
 trash = Servo0CP.get()
 if _Servo0CP > _Servo0DP:
 _Servo0CP -= 1
 Servo0CP.put(_Servo0CP)
 ServoBlaster.write('0=' + str(_Servo0CP) + '\n') #
 ServoBlaster.flush() #
 if not Servo0CP.empty():
 trash = Servo0CP.get()
 if _Servo0CP == _Servo0DP:
 _Servo0S = 1
def P1(): 
 speed = .1
 _Servo1CP = 99
 _Servo1DP = 100
 while True:
 time.sleep(speed)
 if Servo1CP.empty():
 Servo1CP.put(_Servo1CP)
 if not Servo1DP.empty():
 _Servo1DP = Servo1DP.get()
 if not Servo1S.empty():
 _Servo1S = Servo1S.get()
 speed = .1 / _Servo1S
 if _Servo1CP < _Servo1DP:
 _Servo1CP += 1
 Servo1CP.put(_Servo1CP)
 ServoBlaster.write('1=' + str(_Servo1CP) + '\n')
 ServoBlaster.flush()
 if not Servo1CP.empty():
 trash = Servo1CP.get()
 if _Servo1CP > _Servo1DP:
 _Servo1CP -= 1
 Servo1CP.put(_Servo1CP)
 ServoBlaster.write('1=' + str(_Servo1CP) + '\n')
 ServoBlaster.flush()
 if not Servo1CP.empty():
 trash = Servo1CP.get()
 if _Servo1CP == _Servo1DP:
 _Servo1S = 1
Process(target=P0, args=()).start() #
Process(target=P1, args=()).start() #
time.sleep(1) 
#====================================================================================================
def CamRight( distance, speed ): .
 global _Servo0CP
 if not Servo0CP.empty():
 _Servo0CP = Servo0CP.get()
 _Servo0DP = _Servo0CP + distance
 if _Servo0DP > _Servo0UL:
 _Servo0DP = _Servo0UL
 Servo0DP.put(_Servo0DP)
 Servo0S.put(speed)
 return;
def CamLeft(distance, speed):
 global _Servo0CP
 if not Servo0CP.empty():
 _Servo0CP = Servo0CP.get()
 _Servo0DP = _Servo0CP - distance
 if _Servo0DP < _Servo0LL:
 _Servo0DP = _Servo0LL
 Servo0DP.put(_Servo0DP)
 Servo0S.put(speed)
 return;
def CamDown(distance, speed): 
 global _Servo1CP
 if not Servo1CP.empty():
 _Servo1CP = Servo1CP.get()
 _Servo1DP = _Servo1CP + distance
 if _Servo1DP > _Servo1UL:
 _Servo1DP = _Servo1UL
 Servo1DP.put(_Servo1DP)
 Servo1S.put(speed)
 return;
def CamUp(distance, speed): 
 global _Servo1CP
 if not Servo1CP.empty():
 _Servo1CP = Servo1CP.get()
 _Servo1DP = _Servo1CP - distance
 if _Servo1DP < _Servo1LL:
 _Servo1DP = _Servo1LL
 Servo1DP.put(_Servo1DP)
 Servo1S.put(speed)
 return;
#============================================================================================================
while True:
 faceFound = False #
 if not faceFound:
 if lastface == 0 or lastface == 1:
 aframe = webcam.read()[1] 
 aframe = webcam.read()[1] 
 aframe = webcam.read()[1] 
 aframe = webcam.read()[1]
 aframe = webcam.read()[1] 
 fface = frontalface.detectMultiScale(aframe,1.3,4,(cv2.cv.CV_HAAR_DO_CANNY_PRUNING + cv2.cv.CV_HAAR_FIND_BIGGEST_OBJECT + cv2.cv.CV_HAAR_DO_ROUGH_SEARCH),(60,60))
 if fface != (): 
 lastface = 1
 for f in fface:
 faceFound = True
 face = f
 if not faceFound:
 if lastface == 0 or lastface == 2: 
 aframe = webcam.read()[1]
 aframe = webcam.read()[1]
 aframe = webcam.read()[1] 
 aframe = webcam.read()[1] 
 aframe = webcam.read()[1]
 pfacer = profileface.detectMultiScale(aframe,1.3,4,(cv2.cv.CV_HAAR_DO_CANNY_PRUNING + cv2.cv.CV_HAAR_FIND_BIGGEST_OBJECT + cv2.cv.CV_HAAR_DO_ROUGH_SEARCH),(80,80))
 if pfacer != (): 
 lastface = 2
 for f in pfacer:
 faceFound = True
 face = f
 if not faceFound: 
 if lastface == 0 or lastface == 3:
 aframe = webcam.read()[1] 
 aframe = webcam.read()[1]
 aframe = webcam.read()[1]
 aframe = webcam.read()[1]
 aframe = webcam.read()[1]
 cv2.flip(aframe,1,aframe) 
 pfacel = profileface.detectMultiScale(aframe,1.3,4,(cv2.cv.CV_HAAR_DO_CANNY_PRUNING + cv2.cv.CV_HAAR_FIND_BIGGEST_OBJECT + cv2.cv.CV_HAAR_DO_ROUGH_SEARCH),(80,80))
 if pfacel != ():
 lastface = 3
 for f in pfacel:
 faceFound = True
 face = f
 if not faceFound: 
 lastface = 0
 face = [0,0,0,0]
 x,y,w,h = face
 Cface = [(w/2+x),(h/2+y)] 
 print str(Cface[0]) + "," + str(Cface[1])
 if Cface[0] != 0: 
 if Cface[0] > 180: 
 CamLeft(5,1)
 if Cface[0] > 190: #
 CamLeft(7,2) #
 if Cface[0] > 200: #
 CamLeft(9,3) #
 if Cface[0] < 140: 
 CamRight(5,1)
 if Cface[0] < 130:
 CamRight(7,2)
 if Cface[0] < 120:
 CamRight(9,3)
 if Cface[1] > 140: 
 CamDown(5,1)
 if Cface[1] > 150:
 CamDown(7,2)
 if Cface[1] > 160:
 CamDown(9,3)
 if Cface[1] < 100:
 CamUp(5,1)
 if Cface[1] < 90:
 CamUp(7,2)
 if Cface[1] < 80:
 CamUp(9,3)

• HeatfanJohn: When you say "freezes completely", do you mean just your python application or the entire Raspberry Pi?

Answer 1

Face tracking with OpenCV requires a ton of calculations, so plain and simple the Pi cannot keep up with it, assuming you are running at 700MHz. I had this problem and fixed this by overclocking the Pi a bit. I now get around 25fps using the RasPi Cam module, but I am only using tracking/color filtering, not face tracking. I would recommend trying it, but be careful because the GPU and CPU will get pretty warm, so a heatsink on each would be prudent here. Hope this helps..

Answer 2

If load on system is high (use "top" command to check) and each detectMultiScale() call is taking too much time (10-100 millisecs is ideal.>500 ms is bad. Use clock_gettime to profile the call), try the following:

1) Introduce a small delay in the while loop

2) Tune the face detection parameters. Increase reduction factor from 1.3 to 3 or higher.

Since face detection doesn't need high resolutions, increasing it will scale down the image by that factor and then perform the classification.

I've got good results even with factor of 5 when face is close (< 3-4 feet) in front of camera.

3) Why acquire 5 frames in every iteration only to discard the first 4? It's unnecessary load on the USB driver.