您好,欢迎来到学长源码!
热门推荐: html模板 网站模板 magento主题 织梦模板 微信小程序 h5小游戏 Linux教程 源码教程 数据库教程 Magento 2文档 android教程 IOS教程 DedeCMS文档 微信开发

JSP源码

C#源码

企业网站

python自动剪切掉图片的边缘空白区域实例

分类:Python教程 来源:网络收集 发布:学长源码 时间:2017-11-26

python自动剪切掉图片的边缘空白区域实例,如果你的图片有大片空白区域(只要是同一颜色形成一定的面积就认为是空白区域),下面的python代码可以帮你自动切除,如果是透明图像,会自动剪切大片的透明部分。

本代码需要PIL模块

pil相关介绍

PIL:Python Imaging Library,已经是Python平台事实上的图像处理标准库了。PIL功能非常强大,但API却非常简单易用。

由于PIL仅支持到Python 2.7,加上年久失修,于是一群志愿者在PIL的基础上创建了兼容的版本,名字叫Pillow,支持最新Python 3.x,又加入了许多新特性,因此,我们可以直接安装使用Pillow。

import Image, ImageChops
 
def autoCrop(image,backgroundColor=None):
  '''Intelligent automatic image cropping.
    This functions removes the usless "white" space around an image.
    
    If the image has an alpha (tranparency) channel, it will be used
    to choose what to crop.
    
    Otherwise, this function will try to find the most popular color
    on the edges of the image and consider this color "whitespace".
    (You can override this color with the backgroundColor parameter) 
 
    Input:
      image (a PIL Image object): The image to crop.
      backgroundColor (3 integers tuple): eg. (0,0,255)
         The color to consider "background to crop".
         If the image is transparent, this parameters will be ignored.
         If the image is not transparent and this parameter is not
         provided, it will be automatically calculated.
 
    Output:
      a PIL Image object : The cropped image.
  '''
   
  def mostPopularEdgeColor(image):
    ''' Compute who's the most popular color on the edges of an image.
      (left,right,top,bottom)
       
      Input:
        image: a PIL Image object
       
      Ouput:
        The most popular color (A tuple of integers (R,G,B))
    '''
    im = image
    if im.mode != 'RGB':
      im = image.convert("RGB")
     
    # Get pixels from the edges of the image:
    width,height = im.size
    left  = im.crop((0,1,1,height-1))
    right = im.crop((width-1,1,width,height-1))
    top  = im.crop((0,0,width,1))
    bottom = im.crop((0,height-1,width,height))
    pixels = left.tostring() + right.tostring() + top.tostring() + bottom.tostring()
 
    # Compute who's the most popular RGB triplet
    counts = {}
    for i in range(0,len(pixels),3):
      RGB = pixels[i]+pixels[i+1]+pixels[i+2]
      if RGB in counts:
        counts[RGB] += 1
      else:
        counts[RGB] = 1  
     
    # Get the colour which is the most popular:    
    mostPopularColor = sorted([(count,rgba) for (rgba,count) in counts.items()],reverse=True)[0][1]
    return ord(mostPopularColor[0]),ord(mostPopularColor[1]),ord(mostPopularColor[2])
   
  bbox = None
   
  # If the image has an alpha (tranparency) layer, we use it to crop the image.
  # Otherwise, we look at the pixels around the image (top, left, bottom and right)
  # and use the most used color as the color to crop.
   
  # --- For transparent images -----------------------------------------------
  if 'A' in image.getbands(): # If the image has a transparency layer, use it.
    # This works for all modes which have transparency layer
    bbox = image.split()[list(image.getbands()).index('A')].getbbox()
  # --- For non-transparent images -------------------------------------------
  elif image.mode=='RGB':
    if not backgroundColor:
      backgroundColor = mostPopularEdgeColor(image)
    # Crop a non-transparent image.
    # .getbbox() always crops the black color.
    # So we need to substract the "background" color from our image.
    bg = Image.new("RGB", image.size, backgroundColor)
    diff = ImageChops.difference(image, bg) # Substract background color from image
    bbox = diff.getbbox() # Try to find the real bounding box of the image.
  else:
    raise NotImplementedError, "Sorry, this function is not implemented yet for images in mode '%s'." % image.mode
     
  if bbox:
    image = image.crop(bbox)
     
  return image
 
 
 
#范例:裁剪透明图片:
im = Image.open('myTransparentImage.png')
cropped = autoCrop(im)
cropped.show()
 
#范例:裁剪非透明图片
im = Image.open('myImage.png')
cropped = autoCrop(im)
cropped.show()

转载请注明:学长源码 » python自动剪切掉图片的边缘空白区域实例

上一篇 下一篇

图文推荐