mirror of
https://github.com/opencv/opencv.git
synced 2024-11-27 12:40:05 +08:00
102 lines
3.4 KiB
Python
Executable File
102 lines
3.4 KiB
Python
Executable File
#!/usr/bin/python
|
|
"""
|
|
This program is demonstration for face and object detection using haar-like features.
|
|
The program finds faces in a camera image or video stream and displays a red box around them.
|
|
|
|
Original C implementation by: ?
|
|
Python implementation by: Roman Stanchak, James Bowman
|
|
"""
|
|
import sys
|
|
import cv2.cv as cv
|
|
from optparse import OptionParser
|
|
|
|
# Parameters for haar detection
|
|
# From the API:
|
|
# The default parameters (scale_factor=2, min_neighbors=3, flags=0) are tuned
|
|
# for accurate yet slow object detection. For a faster operation on real video
|
|
# images the settings are:
|
|
# scale_factor=1.2, min_neighbors=2, flags=CV_HAAR_DO_CANNY_PRUNING,
|
|
# min_size=<minimum possible face size
|
|
|
|
min_size = (20, 20)
|
|
image_scale = 2
|
|
haar_scale = 1.2
|
|
min_neighbors = 2
|
|
haar_flags = 0
|
|
|
|
def detect_and_draw(img, cascade):
|
|
# allocate temporary images
|
|
gray = cv.CreateImage((img.width,img.height), 8, 1)
|
|
small_img = cv.CreateImage((cv.Round(img.width / image_scale),
|
|
cv.Round (img.height / image_scale)), 8, 1)
|
|
|
|
# convert color input image to grayscale
|
|
cv.CvtColor(img, gray, cv.CV_BGR2GRAY)
|
|
|
|
# scale input image for faster processing
|
|
cv.Resize(gray, small_img, cv.CV_INTER_LINEAR)
|
|
|
|
cv.EqualizeHist(small_img, small_img)
|
|
|
|
if(cascade):
|
|
t = cv.GetTickCount()
|
|
faces = cv.HaarDetectObjects(small_img, cascade, cv.CreateMemStorage(0),
|
|
haar_scale, min_neighbors, haar_flags, min_size)
|
|
t = cv.GetTickCount() - t
|
|
print "detection time = %gms" % (t/(cv.GetTickFrequency()*1000.))
|
|
if faces:
|
|
for ((x, y, w, h), n) in faces:
|
|
# the input to cv.HaarDetectObjects was resized, so scale the
|
|
# bounding box of each face and convert it to two CvPoints
|
|
pt1 = (int(x * image_scale), int(y * image_scale))
|
|
pt2 = (int((x + w) * image_scale), int((y + h) * image_scale))
|
|
cv.Rectangle(img, pt1, pt2, cv.RGB(255, 0, 0), 3, 8, 0)
|
|
|
|
cv.ShowImage("result", img)
|
|
|
|
if __name__ == '__main__':
|
|
|
|
parser = OptionParser(usage = "usage: %prog [options] [filename|camera_index]")
|
|
parser.add_option("-c", "--cascade", action="store", dest="cascade", type="str", help="Haar cascade file, default %default", default = "../data/haarcascades/haarcascade_frontalface_alt.xml")
|
|
(options, args) = parser.parse_args()
|
|
|
|
cascade = cv.Load(options.cascade)
|
|
|
|
if len(args) != 1:
|
|
parser.print_help()
|
|
sys.exit(1)
|
|
|
|
input_name = args[0]
|
|
if input_name.isdigit():
|
|
capture = cv.CreateCameraCapture(int(input_name))
|
|
else:
|
|
capture = None
|
|
|
|
cv.NamedWindow("result", 1)
|
|
|
|
if capture:
|
|
frame_copy = None
|
|
while True:
|
|
frame = cv.QueryFrame(capture)
|
|
if not frame:
|
|
cv.WaitKey(0)
|
|
break
|
|
if not frame_copy:
|
|
frame_copy = cv.CreateImage((frame.width,frame.height),
|
|
cv.IPL_DEPTH_8U, frame.nChannels)
|
|
if frame.origin == cv.IPL_ORIGIN_TL:
|
|
cv.Copy(frame, frame_copy)
|
|
else:
|
|
cv.Flip(frame, frame_copy, 0)
|
|
|
|
detect_and_draw(frame_copy, cascade)
|
|
|
|
if cv.WaitKey(10) >= 0:
|
|
break
|
|
else:
|
|
image = cv.LoadImage(input_name, 1)
|
|
detect_and_draw(image, cascade)
|
|
cv.WaitKey(0)
|
|
|
|
cv.DestroyWindow("result")
|