def mask_image( im, mask ): if mask.depth == 8: bim = cv.cvCreateImage( cv.cvSize(mask.width, mask.height), cv.IPL_DEPTH_32F, mask.nChannels ) cv.cvConvertScale( mask, bim, 1.0/255.0) if im.depth == 8: newim = cv.cvCreateImage( cv.cvSize(im.width, im.height), cv.IPL_DEPTH_32F, im.nChannels ) cv.cvConvertScale( im, newim, 1.0/255.0) print 'newim.depth = ',newim.depth print 'newim.nChannels = ',newim.nChannels print 'bim.depth = ',bim.depth print 'bim.nChannels = ',bim.nChannels if newim.nChannels == 3 and newim.depth == 32 and bim.nChannels == 3 and bim.depth == 32: outputIm = cv.cvCloneImage( bim ) cv.cvMul( bim, newim, outputIm, 1 ) return outputIm else: print 'oops problem with formats' return mask
def mask_image(im, mask):
if mask.depth == 8:
bim = cv.cvCreateImage(cv.cvSize(mask.width, mask.height),
cv.IPL_DEPTH_32F, mask.nChannels)
cv.cvConvertScale(mask, bim, 1.0 / 255.0)
if im.depth == 8:
newim = cv.cvCreateImage(cv.cvSize(im.width, im.height),
cv.IPL_DEPTH_32F, im.nChannels)
cv.cvConvertScale(im, newim, 1.0 / 255.0)
print 'newim.depth = ', newim.depth
print 'newim.nChannels = ', newim.nChannels
print 'bim.depth = ', bim.depth
print 'bim.nChannels = ', bim.nChannels
if newim.nChannels == 3 and newim.depth == 32 and bim.nChannels == 3 and bim.depth == 32:
outputIm = cv.cvCloneImage(bim)
cv.cvMul(bim, newim, outputIm, 1)
return outputIm
else:
print 'oops problem with formats'
return mask
def _multiply_frames(self,frame1,frame2,scale=1.) : cv_mult = cv.cvCreateImage(cv.cvSize(frame1.width,frame1.height),frame1.depth,frame1.nChannels) cv.cvMul(frame1,frame2,cv_mult,scale) return cv_mult
while 1:
# do forever
# capture the current image
frame = highgui.cvQueryFrame(capture)
highgui.cvShowImage('Originale', frame)
if frame is None:
# no image captured... end the processing
break
################ traitement de l'image ################
cv.cvCvtColor(frame, frameGray, cv.CV_BGR2GRAY)
# niveau de gris
cv.cvSub(frameGray, frameGrayBg, framewithoutbg)
# soustraction du background
cv.cvMul(framewithoutbg, framewithoutbg, framemul, get_gain())
# amplification
cv.cvSmooth(framemul, framelisser1, cv.CV_BLUR, param_liss[0],
param2_liss[0])
# lissage
if first == 0: # "moyenne" sur deux image
cv.cvAnd(framelisser1, framelisser2, framelisser)
if first == 1:
framelisser = cv.cvCloneImage(framelisser1)
framelisser2 = cv.cvCloneImage(framelisser1)
cv.cvThreshold(framelisser, frameBin, get_seuil(), float(255),
cv.CV_THRESH_BINARY) # binaristaion de l image
################ run detection ################