Python图像处理之gif动态图的解析与合成操作详解

走进景山公园,抬头望去,高大的万春亭红柱黄瓦,在茂密的翠林映衬下,像一幅美丽的图画。

本文实例讲述了Python图像处理之gif动态图的解析与合成操作。分享给大家供大家参考,具体如下:

gif动态图是在现在已经司空见惯,朋友圈里也经常是一言不合就斗图。这里,就介绍下如何使用python来解析和生成gif图像。

一、gif动态图的合成

如下图,是一个gif动态图。

gif动态图的解析可以使用PIL图像模块即可,具体代码如下:

#-*- coding: UTF-8 -*-
import os
from PIL import Image
def analyseImage(path):
  '''
  Pre-process pass over the image to determine the mode (full or additive).
  Necessary as assessing single frames isn't reliable. Need to know the mode
  before processing all frames.
  '''
  im = Image.open(path)
  results = {
    'size': im.size,
    'mode': 'full',
  }
  try:
    while True:
      if im.tile:
        tile = im.tile[0]
        update_region = tile[1]
        update_region_dimensions = update_region[2:]
        if update_region_dimensions != im.size:
          results['mode'] = 'partial'
          break
      im.seek(im.tell() + 1)
  except EOFError:
    pass
  return results
def processImage(path):
  '''
  Iterate the GIF, extracting each frame.
  '''
  mode = analyseImage(path)['mode']
  im = Image.open(path)
  i = 0
  p = im.getpalette()
  last_frame = im.convert('RGBA')
  try:
    while True:
      print "saving %s (%s) frame %d, %s %s" % (path, mode, i, im.size, im.tile)
      '''
      If the GIF uses local colour tables, each frame will have its own palette.
      If not, we need to apply the global palette to the new frame.
      '''
      if not im.getpalette():
        im.putpalette(p)
      new_frame = Image.new('RGBA', im.size)
      '''
      Is this file a "partial"-mode GIF where frames update a region of a different size to the entire image?
      If so, we need to construct the new frame by pasting it on top of the preceding frames.
      '''
      if mode == 'partial':
        new_frame.paste(last_frame)
      new_frame.paste(im, (0,0), im.convert('RGBA'))
      new_frame.save('%s-%d.png' % (''.join(os.path.basename(path).split('.')[:-1]), i), 'PNG')
      i += 1
      last_frame = new_frame
      im.seek(im.tell() + 1)
  except EOFError:
    pass
def main():
  processImage('test_gif.gif')
if __name__ == "__main__":
  main()

解析结果如下,由此可见改动态图实际上是由14张相同分辨率的静态图组合而成

二、gif动态图的合成

gif图像的合成,使用imageio库(https://pypi.python.org/pypi/imageio)

代码如下:

#-*- coding: UTF-8 -*-
import imageio
def create_gif(image_list, gif_name):
  frames = []
  for image_name in image_list:
    frames.append(imageio.imread(image_name))
  # Save them as frames into a gif
  imageio.mimsave(gif_name, frames, 'GIF', duration = 0.1)
  return
def main():
  image_list = ['test_gif-0.png', 'test_gif-2.png', 'test_gif-4.png',
         'test_gif-6.png', 'test_gif-8.png', 'test_gif-10.png']
  gif_name = 'created_gif.gif'
  create_gif(image_list, gif_name)
if __name__ == "__main__":
  main()

这里,使用第一步解析出来的图像中的8幅图,间副的间隔时间为0.1s,合成新的gif动态图如下:

希望本文所述对大家Python程序设计有所帮助。

以上就是Python图像处理之gif动态图的解析与合成操作详解。高标准,精细化,零缺陷。更多关于Python图像处理之gif动态图的解析与合成操作详解请关注haodaima.com其它相关文章!