def hue_histogram_as_image(self, hist):
""" Returns a nice representation of a hue histogram """
histimg_hsv = cv.CreateImage((320, 200), 8, 3)
mybins = cv.CloneMatND(hist.bins) #Contain all values
cv.Log(mybins, mybins
) #Calculate logarithm of all values (so there are all above 0)
(_, hi, _, _) = cv.MinMaxLoc(mybins)
cv.ConvertScale(mybins, mybins, 255. /
hi) #Rescale all element to get the highest at 255
w, h = cv.GetSize(histimg_hsv)
hdims = cv.GetDims(mybins)[0]
for x in range(w):
xh = (180 * x) / (w - 1) # hue sweeps from 0-180 across the image
val = int(mybins[int(hdims * x / w)] * h / 255)
cv.Rectangle(histimg_hsv, (x, 0), (x, h - val), (xh, 255, 64), -1)
cv.Rectangle(histimg_hsv, (x, h - val), (x, h), (xh, 255, 255), -1)
histimg = cv.CreateImage((320, 200), 8,
3) #Convert image from hsv to RGB
cv.CvtColor(histimg_hsv, histimg, cv.CV_HSV2BGR)
return histimg
def hue_histogram_as_image(self,hist): # Return a nice representation of a hue histogram histimg_hsv = cv.CreateImage((320,200),8,3) mybins = cv.CloneMatND(hist.bins) cv.Log(mybins,mybins) (_,hi,_,_) = cv.MinMaxLoc(mybins) cv.ConvertScale(mybins,mybins,255./hi) w,h = cv.GetSize(histing_hsv) hdims = cv.GetDims(mybins)[0] for x in range(w): xh = (180*x)/(w-1) # hue sweeps from 0-180 across the image val = int(mybins[int(hdims*x/w)]*h/255) cv2.rectangle(histimg_hsv,(x,0),(x,h-val),(xh,255,64),-1) cv2.rectangle(histimg_hsv,(x,h-val),(x,h),(xh,255,255),-1) histimg = cv2.cvtColor(histing_hsv,cv.CV_HSV2BGR) return histimg
def hue_histogram_as_image(self, hist):
""" Returns a nice representation of a hue histogram """
histimg_hsv = cv.CreateImage((320, 200), cv.IPL_DEPTH_8U, 3)
mybins = cv.CloneMatND(hist.bins)
cv.Log(mybins, mybins)
(_, hi, _, _) = cv.MinMaxLoc(mybins)
cv.ConvertScale(mybins, mybins, 255. / hi)
w, h = cv.GetSize(histimg_hsv)
hdims = cv.GetDims(mybins)[0]
for x in range(w):
xh = (180 * x) / (w - 1)
val = int(mybins[int(hdims * x) / w] * h / 255)
cv.Rectangle(histimg_hsv, (x, 0), (x, h - val), (xh, 255, 64), -1)
cv.Rectangle(histimg_hsv, (x, h - val), (x, h), (xh, 255, 255), -1)
histimg = cv.CreateImage((320, 200), 8, 3)
cv.CvtColor(histimg_hsv, histimg, cv.CV_HSV2BGR)
return histimg
cv.DFT( dft_A, dft_A, cv.CV_DXT_FORWARD, complexInput.height )
cv.NamedWindow("win", 0)
cv.NamedWindow("magnitude", 0)
cv.ShowImage("win", im)
# Split Fourier in real and imaginary parts
cv.Split( dft_A, image_Re, image_Im, None, None )
# Compute the magnitude of the spectrum Mag = sqrt(Re^2 + Im^2)
cv.Pow( image_Re, image_Re, 2.0)
cv.Pow( image_Im, image_Im, 2.0)
cv.Add( image_Re, image_Im, image_Re, None)
cv.Pow( image_Re, image_Re, 0.5 )
# Compute log(1 + Mag)
cv.AddS( image_Re, cv.ScalarAll(1.0), image_Re, None ) # 1 + Mag
cv.Log( image_Re, image_Re ) # log(1 + Mag)
# Rearrange the quadrants of Fourier image so that the origin is at
# the image center
cvShiftDFT( image_Re, image_Re )
min, max, pt1, pt2 = cv.MinMaxLoc(image_Re)
cv.Scale(image_Re, image_Re, 1.0/(max-min), 1.0*(-min)/(max-min))
cv.ShowImage("magnitude", image_Re)
cv.WaitKey(0)
cv.DestroyAllWindows()
