前情提要
了解我的小伙伴可能都知道，经常给大家送书，不算联合抽奖送书，单独我自购+出版社赞助已累计送出几百本书籍。
如果是自购的话，还需要自己联系快速小哥寄出书籍。
寄出后快递小哥会给我截图来反馈，然而我想要单号的时候就遇到问题了。
每次寄完书，我都只能得到n个截图（内含快递信息）。
为了及时反馈大家物流信息，我需要尽快将快递单号提取出来。
思考解决办法
每次大概都有十几到几十张截图，手动去识别真的太麻烦。
不如先看看每张截图大概是什么样子，再去想想批量处理的办法吧。
主要是为了批量获取图片中的快递单号，我想到了两个解决办法：
-
用python识别条形码来直接获得准确快递单号
-
用python调用ocr，识别截图中的快递单号文字
大家觉得哪个更简单更准确呢？
今天我先聊聊第一种方法的流程和踩坑经历。
遍历图片
首先，第一步需要先获取文件夹中的所有截图，再依次进行条形码识别。
具体操作可以参考注释
上面的代码中除了遍历筛选图片，还涉及了改名的操作。
这是因为我在后面使用 opencv 时，打开的路径只要含有中文就会一直报错，于是我就干脆把截图名称里的中文去除。
执行构建的get_jpg()函数，得到
这些就是演示文件中的四个截图文件，下面开始对他们进行识别。
识别条形码
python的第三方模块 pyzbar 可以很方便地处理二维码的识别。我们这次用它来识别一维条形码的话，用法也大致一样。不过还要搭配 cv2 使用，主要是为了利用cv2.imread()来读取图片文件。
注意：对于cv2模块，安装时需要输入
pip3 install opencv-python，但在导入的时候采用import cv2。
识别条形码的具体语句如下所示：
上面构建的get_barcode()函数可以实现识别条形码，并返回结果数据。
我们可以用for循环遍历前文获取的所有图片，再依次使用get_barcode()函数来识别条形码。
可以发现，成功识别了四张截图里的条形码，并获取了对应的快递单号。
小结
回顾今天的问题案例，我先通过思考想出了两种解决办法。第一种的优点是识别条形码比OCR更准确，但是其只获取了快递单号。后续在给获得赠书的同学反馈时，我还需要手动将名字和单号对应，不够偷懒。后续将给大家介绍第二种方法的流程和优缺点。
如果想看更多python改变生活的真实问题案例，给本文右下角点个赞吧👍
如果你也有一直想用python解决的问题，欢迎在评论区告诉我🚀
我们的文章到此就结束啦，如果你喜欢今天的Python实战教程，请持续关注菜鸟学Python。
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data-darkmode-original-color-15900529136199="rgb(51, 51, 51)" data-darkmode-bgimage-15900529136199="1" style="max-width: 100%;font-size: 14px;color: rgb(51, 51, 51);text-align: left;box-sizing: border-box !important;overflow-wrap: break-word !important;"><span style="max-width: 100%;font-family: 楷体, 楷体_GB2312, SimKai;white-space: pre-wrap;font-size: 12px;box-sizing: border-box !important;overflow-wrap: break-word !important;">点阅读原文,领AI全套资料！</span></section></section></section></section></section></section></section>本篇文章来源于: 菜鸟学Python
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