import colorsys

def get_dominant_color(image):

#顏色模式轉(zhuǎn)換，以便輸出rgb顏色值
  image = image.convert('RGBA')

#生成縮略圖，減少計算量，減小cpu壓力
  image.thumbnail((200, 200))

  max_score = None
  dominant_color = None

  for count, (r, g, b, a) in image.getcolors(image.size[0] * image.size[1]):
    # 跳過純黑色
    if a == 0:
      continue

    saturation = colorsys.rgb_to_hsv(r / 255.0, g / 255.0, b / 255.0)[1]

    y = min(abs(r * 2104 + g * 4130 + b * 802 + 4096 + 131072) >> 13, 235)

    y = (y - 16.0) / (235 - 16)

    # 忽略高亮色
    if y > 0.9:
      continue

    # Calculate the score, preferring highly saturated colors.
    # Add 0.1 to the saturation so we don't completely ignore grayscale
    # colors by multiplying the count by zero, but still give them a low
    # weight.
    score = (saturation + 0.1) * count

    if score > max_score:
      max_score = score
      dominant_color = (r, g, b)

  return dominant_color

from PIL import Image

print get_dominant_color(Image.open('logo.jpg'))

from PIL import Image
img = Image.open('sharejs.jpg')
img = img.resize((250, 156), Image.ANTIALIAS)
img.save('sharejs_small.jpg')