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本篇内容主要讲解“Python怎么实现图像尺寸和格式转换处理”,感兴趣的朋友不妨来看看。本文介绍的方法操作简单快捷,实用性强。下面就让小编来带大家学习“Python怎么实现图像尺寸和格式转换处理”吧!
实现代码
# batch_handle_image.py import argparse import glob import os from PIL import Image def main(args): limit_shortest = int(args.limitshortest) shortest_edge = int(args.shortestedge) longest_edge = int(args.longestedge) limit_width_or_height = int(args.limitwidthorheight) limit_width = int(args.limitwidth) limit_height = int(args.limitheight) to_webp = int(args.towebp) path_list = sorted(glob.glob(os.path.join(args.input, '*'))) for path in path_list: print(path) basename = os.path.splitext(os.path.basename(path))[0] img = Image.open(path) width, height = img.size # 限制最长边或最短边 if limit_shortest == 1: # save the smallest image which the shortest edge is shortest_edge if width < height: ratio = height / width width = shortest_edge height = int(width * ratio) else: ratio = width / height height = shortest_edge width = int(height * ratio) elif limit_shortest == 0: # save the smallest image which the longest edge is longest_edge if width < height: ratio = width / height height = longest_edge width = int(height * ratio) else: ratio = height / width width = longest_edge height = int(width * ratio) # 限制宽或高 if limit_width_or_height == 0: # 限宽 ratio = height / width width = limit_width height = int(width * ratio) elif limit_width_or_height == 1: # 限高 ratio = width / height height = limit_height width = int(height * ratio) idx = 0 rlt = img.resize((int(width), int(height)), resample=Image.ANTIALIAS) rlt = rlt.convert('RGB') rlt.save(os.path.join(args.output, f'{basename}T{idx+1}.png'), 'PNG') if to_webp == 1: os.makedirs(os.path.join(args.output, 'to_webp'), exist_ok=True) # 转换为 webp 格式图片 rlt.save(os.path.join(args.output, 'to_webp', f'{basename}T{idx+1}.webp'), 'WEBP') if __name__ == '__main__': """batch modify image size, and convert to webp """ parser = argparse.ArgumentParser() parser.add_argument('--input', type=str, default='datasets/MY/YT', help='Input folder') parser.add_argument('--output', type=str, default='datasets/MY/YT_smallsize', help='Output folder') # 是否限制最短边开关:0-限制最长边;1-限制最短边;2-不限制 parser.add_argument('--limitshortest', type=str, default='2', help='0-limit longest; 1-limit shortest; 2-not limit') # 设置最短边数值 parser.add_argument('--shortestedge', type=str, default='500', help='shortest edge size') # 设置最长边数值 parser.add_argument('--longestedge', type=str, default='2000', help='longest edge size') # 是否转换 webp 格式图像开关:0-不转换;1-转换 parser.add_argument('--towebp', type=str, default='0', help='is convert to webp, 0-false, 1-true') # 是否限制宽度或高度数值开关 parser.add_argument( '--limitwidthorheight', type=str, default='2', help='is limit width or height; 0-limit width; 1-limit height; 2-not limit') # 限制宽度数值,高度按比例计算 parser.add_argument('--limitwidth', type=str, default='1080', help='limit width') # 限制高度数值,宽度按比例计算 parser.add_argument('--limitheight', type=str, default='1080', help='limit height') args = parser.parse_args() os.makedirs(args.output, exist_ok=True) main(args)
使用命令
# 限最长边 2000px,并将格式转换为 webp 格式 python batch_handle_image.py --input /input_image --output /output_image --limitshortest 0 --longestedge 2000 --towebp 1
到此,相信大家对“Python怎么实现图像尺寸和格式转换处理”有了更深的了解,不妨来实际操作一番吧!这里是亿速云网站,更多相关内容可以进入相关频道进行查询,关注我们,继续学习!
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