Python PIL图像处理：核心概念解析与等比例压缩裁剪实战

>>>from PIL import Image
>>>im = Image.open('*.jpg')   # 打开一张RGB图像
>>>im_bands = im.g
etbands() # 获取RGB三个波段
>>>len(im_bands)
>>>print im_bands[0,1,2]     # 输出RGB三个值

>>> im.mode

① 1：1位像素，表示黑和白，但是存储的时候每个像素存储为8bit。
② L：8位像素，表示黑和白。
③ P：8位像素，使用调色板映射到其他模式。
④ RGB：3x8位像素，为真彩色。
⑤ RGBA：4x8位像素，有透明通道的真彩色。
⑥ CMYK：4x8位像素，颜色分离。
⑦ YCbCr：3x8位像素，彩色视频格式。
⑧ I：32位整型像素。
⑨ F：32位浮点型像素。

>>> im.size()

>>> im.info() # 返回值为字典对象

>>> from PIL import Image 
>>> im = Image.open('*.jpg')
>>> im.size
>>> im_resize = im.resize((256,256)) #default 情况下是NEAREST插值方法
>>> im_resize0 = im.resize((256,256), Image.BILINEAR)
>>> im_resize0.size
>>> im_resize1 = im.resize((256,256), Image.BICUBIC)
>>> im_resize2 = im.resize((256,256), Image.ANTIALIAS)

#coding:utf-8
'''
  python图片处理
  @author:fc_lamp
  @blog:http://fc-lamp.blog.163.com/
'''
import Image as image
#等比例压缩图片
def resizeImg(**args):
  args_key = {'ori_img':'','dst_img':'','dst_w':'','dst_h':'','save_q':75}
  arg = {}
  for key in args_key:
    if key in args:
      arg[key] = args[key]
  im = image.open(arg['ori_img'])
  ori_w,ori_h = im.size
  widthRatio = heightRatio = None
  ratio = 1
  if (ori_w and ori_w > arg['dst_w']) or (ori_h and ori_h > arg['dst_h']):
    if arg['dst_w'] and ori_w > arg['dst_w']:
      widthRatio = float(arg['dst_w']) / ori_w #正确获取小数的方式
    if arg['dst_h'] and ori_h > arg['dst_h']:
      heightRatio = float(arg['dst_h']) / ori_h
    if widthRatio and heightRatio:
      if widthRatio < heightRatio:
        ratio = widthRatio
      else:
        ratio = heightRatio
    if widthRatio and not heightRatio:
      ratio = widthRatio
    if heightRatio and not widthRatio:
      ratio = heightRatio
    newWidth = int(ori_w * ratio)
    newHeight = int(ori_h * ratio)
  else:
    newWidth = ori_w
    newHeight = ori_h
  im.resize((newWidth,newHeight),image.ANTIALIAS).save(arg['dst_img'],quality=arg['save_q'])
  '''
  image.ANTIALIAS还有如下值：
  NEAREST: use nearest neighbour
  BILINEAR: linear interpolation in a 2x2 environment
  BICUBIC:cubic spline interpolation in a 4x4 environment
  ANTIALIAS:best down-sizing filter
  '''
#裁剪压缩图片
def clipResizeImg(**args):
  args_key = {'ori_img':'','dst_img':'','dst_w':'','dst_h':'','save_q':75}
  arg = {}
  for key in args_key:
    if key in args:
      arg[key] = args[key]
  im = image.open(arg['ori_img'])
  ori_w,ori_h = im.size
  dst_scale = float(arg['dst_h']) / arg['dst_w'] #目标高宽比
  ori_scale = float(ori_h) / ori_w #原高宽比
  if ori_scale >= dst_scale:
    #过高
    width = ori_w
    height = int(width*dst_scale)
    x = 0
    y = (ori_h - height) / 3
  else:
    #过宽
    height = ori_h
    width = int(height*dst_scale)
    x = (ori_w - width) / 2
    y = 0
  #裁剪
  box = (x,y,width+x,height+y)
  #这里的参数可以这么认为：从某图的(x,y)坐标开始截，截到(width+x,height+y)坐标
  #所包围的图像，crop方法与php中的imagecopy方法大为不一样
  newIm = im.crop(box)
  im = None
  #压缩
  ratio = float(arg['dst_w']) / width
  newWidth = int(width * ratio)
  newHeight = int(height * ratio)
  newIm.resize((newWidth,newHeight),image.ANTIALIAS).save(arg['dst_img'],quality=arg['save_q'])
#水印(这里仅为图片水印)
def waterMark(**args):
  args_key = {'ori_img':'','dst_img':'','mark_img':'','water_opt':''}
  arg = {}
  for key in args_key:
    if key in args:
      arg[key] = args[key]
  im = image.open(arg['ori_img'])
  ori_w,ori_h = im.size
  mark_im = image.open(arg['mark_img'])
  mark_w,mark_h = mark_im.size
  option ={'leftup':(0,0),'rightup':(ori_w-mark_w,0),'leftlow':(0,ori_h-mark_h),
       'rightlow':(ori_w-mark_w,ori_h-mark_h)
       }
  im.paste(mark_im,option[arg['water_opt']],mark_im.convert('RGBA'))
  im.save(arg['dst_img'])
#Demon
#源图片
ori_img = 'D:/tt.jpg'
#水印标
mark_img = 'D:/mark.png'
#水印位置(右下)
water_opt = 'rightlow'
#目标图片
dst_img = 'D:/python_2.jpg'
#目标图片大小
dst_w = 94
dst_h = 94
#保存的图片质量
save_q = 35
#裁剪压缩
clipResizeImg(ori_img=ori_img,dst_img=dst_img,dst_w=dst_w,dst_h=dst_h,save_q = save_q)
#等比例压缩
#resizeImg(ori_img=ori_img,dst_img=dst_img,dst_w=dst_w,dst_h=dst_h,save_q=save_q)
#水印
#waterMark(ori_img=ori_img,dst_img=dst_img,mark_img=mark_img,water_opt=water_opt)