I had some fun with Gary Bishop’s OpenCV Python wrapper this morning. I wanted to try out OpenCV for detecting faces using a web cam. This could be used for instance to see if someone is sitting behind his desk or not. I used Gary’s Python wrapper since I didn’t want to code in C++.
I didn’t know where to start, so I searched for existing OpenCV face detection examples. I found a blog post by Nirav Patel explaining how to use OpenCV’s official Python bindings to perform face detection. Nirav will be working on a webcam module for Pygame for the Google Summer of Code.
I managed to rewrite Nirav’s example to get it working with CVtypes:
Here’s the code. Although it’s just a quick and dirty hack, it might be useful to others. It requires CVtypes and OpenCV, and was tested on Ubuntu Hardy with a Logitech QuickCam Communicate Deluxe webcam. You will need Nirav’s Haar cascade file as well.
from CVtypes import cv
image_size = cv.GetSize(image)
# create grayscale version
grayscale = cv.CreateImage(image_size, 8, 1)
cv.CvtColor(image, grayscale, cv.BGR2GRAY)
# create storage
storage = cv.CreateMemStorage(0)
# equalize histogram
# detect objects
cascade = cv.LoadHaarClassifierCascade('haarcascade_frontalface_alt.xml', cv.Size(1,1))
faces = cv.HaarDetectObjects(grayscale, cascade, storage, 1.2, 2, cv.HAAR_DO_CANNY_PRUNING, cv.Size(50, 50))
print 'face detected!'
for i in faces:
cv.Rectangle(image, cv.Point( int(i.x), int(i.y)),
cv.Point(int(i.x + i.width), int(i.y + i.height)),
cv.RGB(0, 255, 0), 3, 8, 0)
if __name__ == "__main__":
print "OpenCV version: %s (%d, %d, %d)" % (cv.VERSION,
print "Press ESC to exit ..."
# create windows
# create capture device
device = 0 # assume we want first device
capture = cv.CreateCameraCapture(0)
cv.SetCaptureProperty(capture, cv.CAP_PROP_FRAME_WIDTH, 640)
cv.SetCaptureProperty(capture, cv.CAP_PROP_FRAME_HEIGHT, 480)
# check if capture device is OK
if not capture:
print "Error opening capture device"
# do forever
# capture the current frame
frame = cv.QueryFrame(capture)
if frame is None:
cv.Flip(frame, None, 1)
# face detection
# display webcam image
# handle events
k = cv.WaitKey(10)
if k == 0x1b: # ESC
print 'ESC pressed. Exiting ...'
A known problem is that pressing the escape key doesn’t quit the program. Might be something wrong in my use of the cv.WaitKey function. Meanwhile you can just use Ctrl+C. All in all, the face detection works pretty well. It doesn’t recognize multiple faces yet, but that might be due to the training data. It would be interesting to experiment with OpenCV’s support for eye tracking in the future.
Just a quick note on ctypes. I remember when I created PydgetRFID that I tried to use libphidgets’ SWIG-generated Python bindings, but couldn’t get them to work properly. I had read about ctypes, and decided to use it for creating my own wrapper around libphidgets. Within a few hours I had a working prototype. When you’re struggling with SWIG-generated Python bindings, or have some C library without bindings that you would like to use, give ctypes a try. Gary Bishop wrote about a couple of interesting ctypes tricks to make the process easier.