Extremely low frame rate when using Opencv for face detection

Question

I have just installed opencv and am following this tutorial to detect faces while displaying a stream. The frame rate is horrible - around 1.5 fps. Why?

Code:

from time import sleep
from picamera import PiCamera
from picamera.array import PiRGBArray
import cv2
camera = PiCamera()
camera.resolution = (640, 480)
camera.framerate = 34
rawCapture = PiRGBArray(camera, size = (640, 480))

window = cv2.namedWindow("Faces")
face_cascade = cv2.CascadeClassifier("/home/pi/opencv-3.1.0/data/lbpcascades/lbpcascades_frontalface.xml")

sleep(0.1)

for frame in camera.capture_continuous(rawCapture, format="bgr", use_video_port=True):
    image = frame.array
    grey = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(grey, 1.1, 5)
    for (x,y,w,h) in faces:
        cv2.rectangle(image,(x,y),(x+w,y+h),(255,0,0),2)
    cv2.imshow("Faces", image)
    key = cv2.waitKey(1)

    rawCapture.truncate(0)

    if key == 27:
        camera.close()
        cv2.destroyAllWindows()
        break        

I have updated the code to the faster algorithm suggested in an answer.

video of framerate

Answer 1

The performance of the RPi is very bad for this calculations. The detection with haar-features slows down by the resolution of the image. It is recommended to shrink the image before searching for features.

For private research I experimented with "Local Binary Patterns Histograms". These algorithm is quite faster. Look here for xml files: https://github.com/opencv/opencv/tree/master/data/lbpcascades

Also, you can build OpenCV with OpenGL support on the RPi. But I am not sure which version is currently in the raspbian repository. Maybe it is not neccessary anymore. More: http://www.pyimagesearch.com/2015/10/26/how-to-install-opencv-3-on-raspbian-jessie/