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Não é um dos melhores métodos científicos, mas tem funcionando bem (verifiquei nas imagens já adquiridas e salvas).

Os tempos de aquisição de imagem mudaram de até 1 minuto pra em torno de 10 minutos. import Image def brightness(filename): """ source: """ img = Image.open(filename) #Convert the image te RGB if it is a for example img = img.convert (' RGB') RANK = #coordinates of the pixel X_i, Y_i = 0,0 (X_f, Y_f) = #Get RGB for i in xrange(X_i, X_f): for j in xrange(Y_i, Y_f): #print "i:", i,",j:", j pixel RGB = img.getpixel((i,j)) R, G, B = pixel RGB br = sum([R, G, B])/ 3 ## 0 is dark (black) and 255 is bright (white) if RANK.has_key(br): RANK[br] = 1 else: RANK[br] = 1 color_order = [] pic_size = X_f * Y_f print "Picture size:", pic_size for k in sorted(RANK, key=RANK.get, reverse=True): amount = RANK[k] # if low than 15%, ignore if amount O código todo está disponível no meu Git Hub.

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