def __init__(self, image, bands=0): data=[] if isinstance(image, pil.Image): try: data = image.histogram() bands = min(3, len(image.mode)) # cut A band of RGBA images # scale, normalize # only if data is extracted from actual image while len(data) > bands*32: data = scaledown(data) # normalize: 255 means entire image is of colors of a bin h,w = image.size maxx = h*w data = [bin * 255. / maxx for bin in data] except: data = [10]*96 # if hostogram is given as a list, guess number of color bands elif type(image) is list: data = image[:] if bands < 1: bands=1 if len(data)>64: bands=3 # struct band hists self.data = [] self.bands = bands # split array into color histograms size=max(len(data)/bands, 32) for b in range(0,len(data), size): self.data.append(data[b:b+size]) # prepare median values self.mediane = [stats.median_histogram(band) for band in self.data] self._hex=''
def image_histmediane(p):
mediane=[]
for offset,channel in enumerate('RGB'):
off=offset*32%len(p.histogram)
band=p.histogram[off:off+32]
#median=sum([i*v for (i,v) in enumerate(band)])/sum(band)
median=stats.median_histogram(band)
mediane.append(median)
return mediane
