class ColorThief(object):
    def __init__(self, file):
        """Create one color thief for one image.

        :param file: A filename (string) or a file object. The file object
                     must implement `read()`, `seek()`, and `tell()` methods,
                     and be opened in binary mode.
        """
        pass

    def get_color(self, quality=10):
        """Get the dominant color.

        :param quality: quality settings, 1 is the highest quality, the bigger
                        the number, the faster a color will be returned but
                        the greater the likelihood that it will not be the
                        visually most dominant color
        :return tuple: (r, g, b)
        """
        pass

    def get_palette(self, color_count=10, quality=10):
        """Build a color palette.  We are using the median cut algorithm to
        cluster similar colors.

        :param color_count: the size of the palette, max number of colors
        :param quality: quality settings, 1 is the highest quality, the bigger
                        the number, the faster the palette generation, but the
                        greater the likelihood that colors will be missed.
        :return list: a list of tuple in the form (r, g, b)
        """
        pass
class ColorThiefArray(object):
    """Color thief from numpy array."""
    def __init__(self, array):
        """Create one color thief for one image.

        :param array: A numpy array of an image.
        """
        self.image = Image.fromarray(file)

    def get_color(self, quality=10):
        """Get the dominant color.

        :param quality: quality settings, 1 is the highest quality, the bigger
                        the number, the faster a color will be returned but
                        the greater the likelihood that it will not be the
                        visually most dominant color
        :return tuple: (r, g, b)
        """
        palette = self.get_palette(5, quality)
        return palette[0]

    def get_palette(self, color_count=10, quality=10):
        """Build a color palette.  We are using the median cut algorithm to
        cluster similar colors.

        :param color_count: the size of the palette, max number of colors
        :param quality: quality settings, 1 is the highest quality, the bigger
                        the number, the faster the palette generation, but the
                        greater the likelihood that colors will be missed.
        :return list: a list of tuple in the form (r, g, b)
        """
        image = self.image.convert('RGBA')
        width, height = image.size
        pixels = image.getdata()
        pixel_count = width * height
        valid_pixels = []
        for i in range(0, pixel_count, quality):
            r, g, b, a = pixels[i]
            # If pixel is mostly opaque and not white
            if a >= 125:
                if not (r > 250 and g > 250 and b > 250):
                    valid_pixels.append((r, g, b))

        # Send array to quantize function which clusters values
        # using median cut algorithm
        cmap = MMCQ.quantize(valid_pixels, color_count)
        return cmap.palette