leveler.py 文件源码

def _auto_color(self, url:str, ranks):
        phrases = ["Calculating colors..."] # in case I want more
        #try:
        await self.bot.say("**{}**".format(random.choice(phrases)))
        clusters = 10

        async with self.session.get(url) as r:
            image = await r.content.read()
        with open('data/leveler/temp_auto.png','wb') as f:
            f.write(image)

        im = Image.open('data/leveler/temp_auto.png').convert('RGBA')
        im = im.resize((290, 290)) # resized to reduce time
        ar = scipy.misc.fromimage(im)
        shape = ar.shape
        ar = ar.reshape(scipy.product(shape[:2]), shape[2])

        codes, dist = scipy.cluster.vq.kmeans(ar.astype(float), clusters)
        vecs, dist = scipy.cluster.vq.vq(ar, codes)         # assign codes
        counts, bins = scipy.histogram(vecs, len(codes))    # count occurrences

        # sort counts
        freq_index = []
        index = 0
        for count in counts:
            freq_index.append((index, count))
            index += 1
        sorted_list = sorted(freq_index, key=operator.itemgetter(1), reverse=True)

        colors = []
        for rank in ranks:
            color_index = min(rank, len(codes))
            peak = codes[sorted_list[color_index][0]] # gets the original index
            peak = peak.astype(int)

            colors.append(''.join(format(c, '02x') for c in peak))
        return colors # returns array
        #except:
            #await self.bot.say("```Error or no scipy. Install scipy doing 'pip3 install numpy' and 'pip3 install scipy' or read here: https://github.com/AznStevy/Maybe-Useful-Cogs/blob/master/README.md```")

    # converts hex to rgb