本文实例为大家分享了python实现图片批量压缩程序的具体代码,供大家参考,具体内容如下
说明
- 运行环境:Win10 Pycharm
- 程序没有用到面向对象编程方法,只是简单的面向过程设计
- 用到的模块:PIL、os、sys
- 使用方法: 在Pycharm的terminal中输入”python xxx.py source_dir dest_dir”就可以把source_dir中的图片文件进行压缩并保存到dest_dir中
源码
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from PIL import Image
import os
import sys
# 定义可以识别的图片文件类型,可以自行扩充
valid_file_type = [ '.jpg' , '.png' ]
# 定义压缩比,数值越大,压缩越小
SIZE_normal = 1.0
SIZE_small = 1.5
SIZE_more_small = 2.0
def make_directory(directory):
"""创建目录"""
os.makedirs(directory)
def directory_exists(directory):
"""判断目录是否存在"""
if os.path.exists(directory):
return True
else :
return False
def list_img_file(directory):
"""列出目录下所有文件,并筛选出图片文件列表返回"""
old_list = os.listdir(directory)
# print old_list
new_list = []
for filename in old_list:
if os.path.isfile(filename):
f, e = os.path.splitext(filename)
if e in valid_file_type:
new_list.append(filename)
else :
pass
else :
pass
# print new_list
return new_list
def print_help():
print """
This program helps compress many image files
you can choose which scale you want to compress your img(jpg/png/etc)
1) normal compress(4M to 1M around)
2) small compress(4M to 500K around)
3) smaller compress(4M to 300K around)
"""
def compress(choose, des_dir, file_list):
"""压缩算法,img.thumbnail对图片进行压缩,还可以改变宽高数值进行压缩"""
if choose = = '1' :
scale = SIZE_normal
if choose = = '2' :
scale = SIZE_small
if choose = = '3' :
scale = SIZE_more_small
for infile in file_list:
img = Image. open (infile)
# size_of_file = os.path.getsize(infile)
w, h = img.size
img.thumbnail(( int (w / scale), int (h / scale)))
img.save(des_dir + '/' + infile)
if __name__ = = "__main__" :
src_dir, des_dir = sys.argv[ 1 ], sys.argv[ 2 ]
if directory_exists(src_dir):
if not directory_exists(des_dir):
make_directory(des_dir)
# business logic
file_list = list_img_file(src_dir)
# print file_list
if file_list:
print_help()
choose = raw_input ( "enter your choice:" )
compress(choose, des_dir, file_list)
else :
pass
else :
print "source directory not exist!"
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以上就是本文的全部内容,希望对大家的学习有所帮助,也希望大家多多支持服务器之家。
原文链接:https://blog.csdn.net/qq_22187919/article/details/52551526