def findcontours(iplimage, threshold=100):
srcimage = opencv.cvCloneImage(iplimage)
# create the storage area and bw image
grayscale = opencv.cvCreateImage(opencv.cvGetSize(srcimage), 8, 1)
opencv.cvCvtColor(srcimage, grayscale, opencv.CV_BGR2GRAY)
# threshold
opencv.cvThreshold(grayscale, grayscale, threshold, 255, opencv.CV_THRESH_BINARY)
storage = opencv.cvCreateMemStorage(0)
opencv.cvClearMemStorage(storage)
# find the contours
nb_contours, contours = opencv.cvFindContours(grayscale, storage)
# comment this out if you do not want approximation
contours = opencv.cvApproxPoly(contours, opencv.sizeof_CvContour, storage, opencv.CV_POLY_APPROX_DP, 3, 1)
# next line is for ctypes-opencv
# contours = opencv.cvApproxPoly (contours, opencv.sizeof(opencv.CvContour), storage, opencv.CV_POLY_APPROX_DP, 3, 1)
conts = []
for cont in contours.hrange():
points = []
for pt in cont:
points.append((pt.x, pt.y))
conts.append(points)
opencv.cvReleaseMemStorage(storage)
opencv.cvReleaseImage(srcimage)
opencv.cvReleaseImage(grayscale)
return (nb_contours, conts)
def findcontours(iplimage, threshold=100):
srcimage = opencv.cvCloneImage(iplimage)
# create the storage area and bw image
grayscale = opencv.cvCreateImage(opencv.cvGetSize(srcimage), 8, 1)
opencv.cvCvtColor(srcimage, grayscale, opencv.CV_BGR2GRAY)
#threshold
opencv.cvThreshold(grayscale, grayscale, threshold, 255, opencv.CV_THRESH_BINARY)
storage = opencv.cvCreateMemStorage(0)
opencv.cvClearMemStorage(storage)
# find the contours
nb_contours, contours = opencv.cvFindContours (grayscale, storage)
# comment this out if you do not want approximation
contours = opencv.cvApproxPoly (contours, opencv.sizeof_CvContour, storage, opencv.CV_POLY_APPROX_DP, 3, 1)
# next line is for ctypes-opencv
#contours = opencv.cvApproxPoly (contours, opencv.sizeof(opencv.CvContour), storage, opencv.CV_POLY_APPROX_DP, 3, 1)
conts = []
for cont in contours.hrange():
points=[]
for pt in cont:
points.append((pt.x,pt.y))
conts.append(points)
opencv.cvReleaseMemStorage(storage)
opencv.cvReleaseImage(srcimage)
opencv.cvReleaseImage(grayscale)
return (nb_contours, conts)
def detectHaar(iplimage, classifier):
srcimage = opencv.cvCloneImage(iplimage)
grayscale = opencv.cvCreateImage(opencv.cvGetSize(srcimage), 8, 1)
opencv.cvCvtColor(srcimage, grayscale, opencv.CV_BGR2GRAY)
storage = opencv.cvCreateMemStorage(0)
opencv.cvClearMemStorage(storage)
opencv.cvEqualizeHist(grayscale, grayscale)
try:
cascade = opencv.cvLoadHaarClassifierCascade(os.path.join(os.path.dirname(__file__), classifier + ".xml"), opencv.cvSize(1, 1))
except:
raise AttributeError("could not load classifier file")
objs = opencv.cvHaarDetectObjects(grayscale, cascade, storage, 1.2, 2, opencv.CV_HAAR_DO_CANNY_PRUNING, opencv.cvSize(50, 50))
objects = []
for obj in objs:
objects.append(Haarobj(obj))
opencv.cvReleaseImage(srcimage)
opencv.cvReleaseImage(grayscale)
opencv.cvReleaseMemStorage(storage)
return objects
def detectHaar(iplimage, classifier):
srcimage = opencv.cvCloneImage(iplimage)
grayscale = opencv.cvCreateImage(opencv.cvGetSize(srcimage), 8, 1)
opencv.cvCvtColor(srcimage, grayscale, opencv.CV_BGR2GRAY)
storage = opencv.cvCreateMemStorage(0)
opencv.cvClearMemStorage(storage)
opencv.cvEqualizeHist(grayscale, grayscale)
try:
cascade = opencv.cvLoadHaarClassifierCascade(os.path.join(os.path.dirname(__file__), classifier+".xml"),opencv.cvSize(1,1))
except:
raise AttributeError, "could not load classifier file"
objs = opencv.cvHaarDetectObjects(grayscale, cascade, storage, 1.2, 2, opencv.CV_HAAR_DO_CANNY_PRUNING, opencv.cvSize(50,50))
objects = []
for obj in objs:
objects.append(Haarobj(obj))
opencv.cvReleaseImage(srcimage)
opencv.cvReleaseImage(grayscale)
opencv.cvReleaseMemStorage(storage)
return objects
