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使用Python的PIL模块来进行图片对比

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Release: 2016-06-10 15:06:02
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在使用google或者baidu搜图的时候会发现有一个图片颜色选项,感觉非常有意思,有人可能会想这肯定是人为的去划分的,呵呵,有这种可能,但是估计人会累死, 开个玩笑,当然是通过机器识别的,海量的图片只有机器识别才能做到。
那用python能不能实现这种功能呢?答案是:能

利用python的PIL模块的强大的图像处理功能就可以做到,下面上代码:

import colorsys

def get_dominant_color(image):

#颜色模式转换,以便输出rgb颜色值
  image = image.convert('RGBA')

#生成缩略图,减少计算量,减小cpu压力
  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]):
    # 跳过纯黑色
    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

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如何使用:

from PIL import Image

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

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这样就会返回一个rgb颜色,但是这个值是很精确的范围,那我们如何实现百度图片那样的色域呢??
其实方法很简单,r/g/b都是0-255的值,我们只要把这三个值分别划分相等的区间,然后组合,取近似值。例如:划分为0-127,和128-255,然后自由组 合,可以出现八种组合,然后从中挑出比较有代表性的颜色即可。
当然我只是举一个例子,你也可以划分的更细,那样显示的颜色就会更准确~~大家赶快试试吧

PS:通过pil生成缩略图的简单代码

如果是单纯地生成缩略图,我们可以通过pil很简单地办到,这段代码会强行将图片大小修改成250x156:

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