Xuanyu Zhu's Blog

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先简单介绍一下。
直接使用腾讯云或者百度云的接口的方法我就不过多赘述了，我觉得他们的开发文档写的蛮好，直接对着做就行了。我的工作主要就是将腾讯云的 api 接口进行了简单的封装，免去了环境配置和身份认证过程，只需要密钥和图片就能直接进行识别，甚至密钥也可以不用，大大方便了同学们的操作。
同时也在刘同学的帮助下实现了 paddlepaddle 模型的接口，后续还会再加上其他更多的预训练模型，提供更多的选择，同时后续我们还会将各个模型性能对比进行分析，为选择提供参考。
一些常用语言的 demo 在下方有具体实例，复制粘贴就能用了。

具体实例中是核心代码，在https://github.com/zhuzil/ocrDemo.git 中有各个语言的demo工程文件，clone下来就能用了，不过不是很推荐吧，我的具体实例中的核心代码已经写的比较清楚了，复制过去比较好，下载的demo我感觉可能环境版本什么的出问题在你们的电脑上不一定能跑通。

腾讯云 api 封装接口

URL：https://www.7-an.com:5000/api/ocr
Method：POST

请求参数

参数 类型 必填 说明
SecretID String 否 无
SecretKey String 否 无
ImageBase64 String 必填 暂时不支持 URL，后续会补充
IsCorrection Int 否 数字 1 或 0，1 使用校正，0 不使用，图片校准默认为 0
💡 注意，`SecretID` 和 `SecretKey` 字段为腾讯云文字识别服务的个人密钥，在这个接口中我把我的密钥做成了默认密钥，如果用户没有输入密钥的话则会使用默认密钥，因为腾讯云只有免费的1000次额度所以希望同学们谨慎使用，同时我也对接口使用做了一些限制，每个IP每10秒只能获取一次。希望同学们尽量使用自己的密钥。

密钥获取方式

IsCorrection 参数说明

感谢刘同学友情赞助的校正代码，github 地址https://github.com/evibhm/ImageCorrection，欢迎 fork 和 star
校正效果如下：
原图：

test.jpg

校正后：

test1_cor.jpg

请求示例

json 格式请求

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{
    "ImageBase64":ImageBase64Data,
    "IsCorrection":1,
    "SecretId":"xxxxx",
    "SecretKey":"xxxxx"
}

成功响应

条件：请求参数合法，并且用户身份校验通过。
状态码：200 OK
响应示例：如果成功识别最会返回一个JSON格式的串，结果存在data值中：

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{
    "code": 200,
    "message": "Your SecretId or SecretKey is wrong, the default SecretId and SecretKey are already used",
    "data": "{\"TableDetections\": [{\"Cells\": [{\"ColTl\": 0, \"RowTl\": 0, \"ColBr\": 9, \"RowBr\": 1, \"Text\": \"五(1) 班卫生值日表\", \"Type\": \"body\", \"Confidence\": 99.982088804245, \"Polygon\": [{\"X\": 26, \"Y\": 193}, {\"X\": 774, \"Y\": 193}, {\"X\": 774, \"Y\": 282}, {\"X\": 26, \"Y\": 282}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 25}]}, {\"ColTl\": 0, \"RowTl\": 1, \"ColBr\": 1, \"RowBr\": 2, \"Text\": \"星期一\", \"Type\": \"body\", \"Confidence\": 99.96871948242188, \"Polygon\": [{\"X\": 26, \"Y\": 282}, {\"X\": 107, \"Y\": 282}, {\"X\": 107, \"Y\": 326}, {\"X\": 26, \"Y\": 326}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 1, \"RowTl\": 1, \"ColBr\": 2, \"RowBr\": 2, \"Text\": \"梅亚婷\", \"Type\": \"body\", \"Confidence\": 99.99997615814209, \"Polygon\": [{\"X\": 107, \"Y\": 282}, {\"X\": 191, \"Y\": 282}, {\"X\": 191, \"Y\": 326}, {\"X\": 107, \"Y\": 326}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 2, \"RowTl\": 1, \"ColBr\": 3, \"RowBr\": 2, \"Text\": \"潘林峰\", \"Type\": \"body\", \"Confidence\": 99.99949336051941, \"Polygon\": [{\"X\": 191, \"Y\": 282}, {\"X\": 275, \"Y\": 282}, {\"X\": 275, \"Y\": 326}, {\"X\": 191, \"Y\": 326}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 3, \"RowTl\": 1, \"ColBr\": 4, \"RowBr\": 2, \"Text\": \"余校凯\", \"Type\": \"body\", \"Confidence\": 99.98820424079895, \"Polygon\": [{\"X\": 275, \"Y\": 282}, {\"X\": 359, \"Y\": 282}, {\"X\": 359, \"Y\": 326}, {\"X\": 275, \"Y\": 326}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 4, \"RowTl\": 1, \"ColBr\": 5, \"RowBr\": 2, \"Text\": \"郑江豪\", \"Type\": \"body\", \"Confidence\": 99.99780654907227, \"Polygon\": [{\"X\": 359, \"Y\": 282}, {\"X\": 442, \"Y\": 282}, {\"X\": 442, \"Y\": 326}, {\"X\": 359, \"Y\": 326}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 5, \"RowTl\": 1, \"ColBr\": 6, \"RowBr\": 2, \"Text\": \"范立新\", \"Type\": \"body\", \"Confidence\": 100, \"Polygon\": [{\"X\": 442, \"Y\": 282}, {\"X\": 526, \"Y\": 282}, {\"X\": 526, \"Y\": 326}, {\"X\": 442, \"Y\": 326}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 6, \"RowTl\": 1, \"ColBr\": 7, \"RowBr\": 2, \"Text\": \"柯志生\", \"Type\": \"body\", \"Confidence\": 99.99997019767761, \"Polygon\": [{\"X\": 526, \"Y\": 282}, {\"X\": 610, \"Y\": 282}, {\"X\": 610, \"Y\": 326}, {\"X\": 526, \"Y\": 326}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 7, \"RowTl\": 1, \"ColBr\": 8, \"RowBr\": 2, \"Text\": \"周于\", \"Type\": \"body\", \"Confidence\": 99.9976396560669, \"Polygon\": [{\"X\": 610, \"Y\": 282}, {\"X\": 694, \"Y\": 282}, {\"X\": 694, \"Y\": 326}, {\"X\": 610, \"Y\": 326}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 14}]}, {\"ColTl\": 8, \"RowTl\": 1, \"ColBr\": 9, \"RowBr\": 2, \"Text\": \"李慧得\", \"Type\": \"body\", \"Confidence\": 99.99997019767761, \"Polygon\": [{\"X\": 694, \"Y\": 282}, {\"X\": 774, \"Y\": 282}, {\"X\": 774, \"Y\": 326}, {\"X\": 694, \"Y\": 326}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 0, \"RowTl\": 2, \"ColBr\": 1, \"RowBr\": 3, \"Text\": \"星期二\", \"Type\": \"body\", \"Confidence\": 99.99971389770508, \"Polygon\": [{\"X\": 26, \"Y\": 326}, {\"X\": 107, \"Y\": 326}, {\"X\": 107, \"Y\": 373}, {\"X\": 26, \"Y\": 373}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 14}]}, {\"ColTl\": 1, \"RowTl\": 2, \"ColBr\": 2, \"RowBr\": 3, \"Text\": \"郑江尧\", \"Type\": \"body\", \"Confidence\": 99.99954104423523, \"Polygon\": [{\"X\": 107, \"Y\": 326}, {\"X\": 191, \"Y\": 326}, {\"X\": 191, \"Y\": 373}, {\"X\": 107, \"Y\": 373}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 14}]}, {\"ColTl\": 2, \"RowTl\": 2, \"ColBr\": 3, \"RowBr\": 3, \"Text\": \"郑锦证\", \"Type\": \"body\", \"Confidence\": 99.99963641166687, \"Polygon\": [{\"X\": 191, \"Y\": 326}, {\"X\": 275, \"Y\": 326}, {\"X\": 275, \"Y\": 373}, {\"X\": 191, \"Y\": 373}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 14}]}, {\"ColTl\": 3, \"RowTl\": 2, \"ColBr\": 4, \"RowBr\": 3, \"Text\": \"虞志峰\", \"Type\": \"body\", \"Confidence\": 99.98536109924316, \"Polygon\": [{\"X\": 275, \"Y\": 326}, {\"X\": 359, \"Y\": 326}, {\"X\": 359, \"Y\": 373}, {\"X\": 275, \"Y\": 373}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 4, \"RowTl\": 2, \"ColBr\": 5, \"RowBr\": 3, \"Text\": \"虞雨清\", \"Type\": \"body\", \"Confidence\": 98.66757988929749, \"Polygon\": [{\"X\": 359, \"Y\": 326}, {\"X\": 442, \"Y\": 326}, {\"X\": 442, \"Y\": 373}, {\"X\": 359, \"Y\": 373}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 5, \"RowTl\": 2, \"ColBr\": 6, \"RowBr\": 3, \"Text\": \"郑小伟\", \"Type\": \"body\", \"Confidence\": 100, \"Polygon\": [{\"X\": 442, \"Y\": 326}, {\"X\": 526, \"Y\": 326}, {\"X\": 526, \"Y\": 373}, {\"X\": 442, \"Y\": 373}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 6, \"RowTl\": 2, \"ColBr\": 7, \"RowBr\": 3, \"Text\": \"桂堂豪\", \"Type\": \"body\", \"Confidence\": 99.99939799308777, \"Polygon\": [{\"X\": 526, \"Y\": 326}, {\"X\": 610, \"Y\": 326}, {\"X\": 610, \"Y\": 373}, {\"X\": 526, \"Y\": 373}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 7, \"RowTl\": 2, \"ColBr\": 8, \"RowBr\": 3, \"Text\": \"何志勇\", \"Type\": \"body\", \"Confidence\": 99.99999403953552, \"Polygon\": [{\"X\": 610, \"Y\": 326}, {\"X\": 694, \"Y\": 326}, {\"X\": 694, \"Y\": 373}, {\"X\": 610, \"Y\": 373}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 14}]}, {\"ColTl\": 8, \"RowTl\": 2, \"ColBr\": 9, \"RowBr\": 3, \"Text\": \"张志霞\", \"Type\": \"body\", \"Confidence\": 99.99999403953552, \"Polygon\": [{\"X\": 694, \"Y\": 326}, {\"X\": 774, \"Y\": 326}, {\"X\": 774, \"Y\": 373}, {\"X\": 694, \"Y\": 373}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 14}]}, {\"ColTl\": 0, \"RowTl\": 3, \"ColBr\": 1, \"RowBr\": 4, \"Text\": \"星期三\", \"Type\": \"body\", \"Confidence\": 99.99997019767761, \"Polygon\": [{\"X\": 26, \"Y\": 373}, {\"X\": 107, \"Y\": 373}, {\"X\": 107, \"Y\": 418}, {\"X\": 26, \"Y\": 418}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 1, \"RowTl\": 3, \"ColBr\": 2, \"RowBr\": 4, \"Text\": \"桂小敏\", \"Type\": \"body\", \"Confidence\": 99.99976754188538, \"Polygon\": [{\"X\": 107, \"Y\": 373}, {\"X\": 191, \"Y\": 373}, {\"X\": 191, \"Y\": 418}, {\"X\": 107, \"Y\": 418}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 2, \"RowTl\": 3, \"ColBr\": 3, \"RowBr\": 4, \"Text\": \"雷玉婷\", \"Type\": \"body\", \"Confidence\": 99.99997019767761, \"Polygon\": [{\"X\": 191, \"Y\": 373}, {\"X\": 275, \"Y\": 373}, {\"X\": 275, \"Y\": 418}, {\"X\": 191, \"Y\": 418}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 3, \"RowTl\": 3, \"ColBr\": 4, \"RowBr\": 4, \"Text\": \"李洁\", \"Type\": \"body\", \"Confidence\": 99.9998688697815, \"Polygon\": [{\"X\": 275, \"Y\": 373}, {\"X\": 359, \"Y\": 373}, {\"X\": 359, \"Y\": 418}, {\"X\": 275, \"Y\": 418}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 4, \"RowTl\": 3, \"ColBr\": 5, \"RowBr\": 4, \"Text\": \"雷可丽\", \"Type\": \"body\", \"Confidence\": 99.99987483024597, \"Polygon\": [{\"X\": 359, \"Y\": 373}, {\"X\": 442, \"Y\": 373}, {\"X\": 442, \"Y\": 418}, {\"X\": 359, \"Y\": 418}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 5, \"RowTl\": 3, \"ColBr\": 6, \"RowBr\": 4, \"Text\": \"李爱兰\", \"Type\": \"body\", \"Confidence\": 99.99998211860657, \"Polygon\": [{\"X\": 442, \"Y\": 373}, {\"X\": 526, \"Y\": 373}, {\"X\": 526, \"Y\": 418}, {\"X\": 442, \"Y\": 418}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 6, \"RowTl\": 3, \"ColBr\": 7, \"RowBr\": 4, \"Text\": \"桂喻霞\", \"Type\": \"body\", \"Confidence\": 99.99707341194153, \"Polygon\": [{\"X\": 526, \"Y\": 373}, {\"X\": 610, \"Y\": 373}, {\"X\": 610, \"Y\": 418}, {\"X\": 526, \"Y\": 418}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 7, \"RowTl\": 3, \"ColBr\": 8, \"RowBr\": 4, \"Text\": \"郭培润\", \"Type\": \"body\", \"Confidence\": 99.99442100524902, \"Polygon\": [{\"X\": 610, \"Y\": 373}, {\"X\": 694, \"Y\": 373}, {\"X\": 694, \"Y\": 418}, {\"X\": 610, \"Y\": 418}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 8, \"RowTl\": 3, \"ColBr\": 9, \"RowBr\": 4, \"Text\": \"范亚妮\", \"Type\": \"body\", \"Confidence\": 99.99880194664001, \"Polygon\": [{\"X\": 694, \"Y\": 373}, {\"X\": 774, \"Y\": 373}, {\"X\": 774, \"Y\": 418}, {\"X\": 694, \"Y\": 418}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 0, \"RowTl\": 4, \"ColBr\": 1, \"RowBr\": 5, \"Text\": \"星期四\", \"Type\": \"body\", \"Confidence\": 99.99974370002747, \"Polygon\": [{\"X\": 26, \"Y\": 418}, {\"X\": 107, \"Y\": 418}, {\"X\": 107, \"Y\": 464}, {\"X\": 26, \"Y\": 464}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 1, \"RowTl\": 4, \"ColBr\": 2, \"RowBr\": 5, \"Text\": \"桂宗宙\", \"Type\": \"body\", \"Confidence\": 99.99898076057434, \"Polygon\": [{\"X\": 107, \"Y\": 418}, {\"X\": 191, \"Y\": 418}, {\"X\": 191, \"Y\": 464}, {\"X\": 107, \"Y\": 464}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 2, \"RowTl\": 4, \"ColBr\": 3, \"RowBr\": 5, \"Text\": \"李谓志\", \"Type\": \"body\", \"Confidence\": 99.9998390674591, \"Polygon\": [{\"X\": 191, \"Y\": 418}, {\"X\": 275, \"Y\": 418}, {\"X\": 275, \"Y\": 464}, {\"X\": 191, \"Y\": 464}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 3, \"RowTl\": 4, \"ColBr\": 4, \"RowBr\": 5, \"Text\": \"雷彩霞\", \"Type\": \"body\", \"Confidence\": 99.99995231628418, \"Polygon\": [{\"X\": 275, \"Y\": 418}, {\"X\": 359, \"Y\": 418}, {\"X\": 359, \"Y\": 464}, {\"X\": 275, \"Y\": 464}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 4, \"RowTl\": 4, \"ColBr\": 5, \"RowBr\": 5, \"Text\": \"郑佳勇\", \"Type\": \"body\", \"Confidence\": 99.99539256095886, \"Polygon\": [{\"X\": 359, \"Y\": 418}, {\"X\": 442, \"Y\": 418}, {\"X\": 442, \"Y\": 464}, {\"X\": 359, \"Y\": 464}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 5, \"RowTl\": 4, \"ColBr\": 6, \"RowBr\": 5, \"Text\": \"马佳辉\", \"Type\": \"body\", \"Confidence\": 99.99973773956299, \"Polygon\": [{\"X\": 442, \"Y\": 418}, {\"X\": 526, \"Y\": 418}, {\"X\": 526, \"Y\": 464}, {\"X\": 442, \"Y\": 464}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 6, \"RowTl\": 4, \"ColBr\": 7, \"RowBr\": 5, \"Text\": \"郭培建\", \"Type\": \"body\", \"Confidence\": 99.99993443489075, \"Polygon\": [{\"X\": 526, \"Y\": 418}, {\"X\": 610, \"Y\": 418}, {\"X\": 610, \"Y\": 464}, {\"X\": 526, \"Y\": 464}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 7, \"RowTl\": 4, \"ColBr\": 8, \"RowBr\": 5, \"Text\": \"李智政\", \"Type\": \"body\", \"Confidence\": 99.99950528144836, \"Polygon\": [{\"X\": 610, \"Y\": 418}, {\"X\": 694, \"Y\": 418}, {\"X\": 694, \"Y\": 464}, {\"X\": 610, \"Y\": 464}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 8, \"RowTl\": 4, \"ColBr\": 9, \"RowBr\": 5, \"Text\": \"范成龙\", \"Type\": \"body\", \"Confidence\": 100, \"Polygon\": [{\"X\": 694, \"Y\": 418}, {\"X\": 774, \"Y\": 418}, {\"X\": 774, \"Y\": 464}, {\"X\": 694, \"Y\": 464}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 14}]}, {\"ColTl\": 0, \"RowTl\": 5, \"ColBr\": 1, \"RowBr\": 6, \"Text\": \"星期五\", \"Type\": \"body\", \"Confidence\": 99.99926090240479, \"Polygon\": [{\"X\": 26, \"Y\": 464}, {\"X\": 107, \"Y\": 464}, {\"X\": 107, \"Y\": 510}, {\"X\": 26, \"Y\": 510}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 1, \"RowTl\": 5, \"ColBr\": 2, \"RowBr\": 6, \"Text\": \"朱凯鹏\", \"Type\": \"body\", \"Confidence\": 99.99980926513672, \"Polygon\": [{\"X\": 107, \"Y\": 464}, {\"X\": 191, \"Y\": 464}, {\"X\": 191, \"Y\": 510}, {\"X\": 107, \"Y\": 510}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 2, \"RowTl\": 5, \"ColBr\": 3, \"RowBr\": 6, \"Text\": \"虞校水\", \"Type\": \"body\", \"Confidence\": 99.98979568481445, \"Polygon\": [{\"X\": 191, \"Y\": 464}, {\"X\": 275, \"Y\": 464}, {\"X\": 275, \"Y\": 510}, {\"X\": 191, \"Y\": 510}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 3, \"RowTl\": 5, \"ColBr\": 4, \"RowBr\": 6, \"Text\": \"郑雯丽\", \"Type\": \"body\", \"Confidence\": 99.99974370002747, \"Polygon\": [{\"X\": 275, \"Y\": 464}, {\"X\": 359, \"Y\": 464}, {\"X\": 359, \"Y\": 510}, {\"X\": 275, \"Y\": 510}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 4, \"RowTl\": 5, \"ColBr\": 5, \"RowBr\": 6, \"Text\": \"郑琳\", \"Type\": \"body\", \"Confidence\": 100, \"Polygon\": [{\"X\": 359, \"Y\": 464}, {\"X\": 442, \"Y\": 464}, {\"X\": 442, \"Y\": 510}, {\"X\": 359, \"Y\": 510}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 14}]}, {\"ColTl\": 5, \"RowTl\": 5, \"ColBr\": 6, \"RowBr\": 6, \"Text\": \"范越\", \"Type\": \"body\", \"Confidence\": 99.99940991401672, \"Polygon\": [{\"X\": 442, \"Y\": 464}, {\"X\": 526, \"Y\": 464}, {\"X\": 526, \"Y\": 510}, {\"X\": 442, \"Y\": 510}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 6, \"RowTl\": 5, \"ColBr\": 7, \"RowBr\": 6, \"Text\": \"张鑫涛\", \"Type\": \"body\", \"Confidence\": 99.99998211860657, \"Polygon\": [{\"X\": 526, \"Y\": 464}, {\"X\": 610, \"Y\": 464}, {\"X\": 610, \"Y\": 510}, {\"X\": 526, \"Y\": 510}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 7, \"RowTl\": 5, \"ColBr\": 8, \"RowBr\": 6, \"Text\": \"雷万林\", \"Type\": \"body\", \"Confidence\": 99.99470114707947, \"Polygon\": [{\"X\": 610, \"Y\": 464}, {\"X\": 694, \"Y\": 464}, {\"X\": 694, \"Y\": 511}, {\"X\": 610, \"Y\": 510}], \"AdvancedInfo\": \"\", \"Contents\": [{\"ParagNo\": 0, \"WordSize\": 15}]}, {\"ColTl\": 8, \"RowTl\": 5, \"ColBr\": 9, \"RowBr\": 6, \"Text\": \"雷建国\", \"Type\": \"body\", \"Confidence\": 100, \"Polygon\": [{\"X\": 694, \"Y\": 464}, {\"X\": 774, \"Y\": 464}, {\"X\": 774, \"Y\": 510}, {\"X\": 694, \"Y\": 511}], \"AdvancedInfo\": \"\", 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\", \"PdfPageSize\": 0, \"Angle\": 0, \"RequestId\": \"b127722b-d3d6-45c6-b622-85332916a526\"}"
}

data 中的参数介绍

参数名称 类型 描述
TableDetections Array of TableDetectInfo 检测到的文本信息，具体内容请点击左侧链接。
Data String Base64 编码后的 Excel 数据。
PdfPageSize Integer 图片为 PDF 时，返回 PDF 的总页数，默认为 0
Angle Float 图片旋转角度（角度制），文本的水平方向为 0°，统一以逆时针方向旋转，逆时针为负，角度范围为-360° 至 0°。
RequestId String 唯一请求 ID，每次请求都会返回。定位问题时需要提供该次请求的 RequestId。

错误响应

条件：ImageBase64和ImageUrl都没有传入。
状态码：500 BAD REQUEST

响应示例:

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<!doctype html>
<html lang=en>
<title>500 Internal Server Error</title>
<h1>Internal Server Error</h1>
<p>The server encountered an internal error and was unable to complete your request. Either the server is overloaded or
	there is an error in the application.</p>

密钥获取

  1. 开通文字识别服务：进入 文字识别控制台，注册腾讯云账号并通过实名认证，阅读《文字识别服务条款》后勾选同意并单击立即开通；
    image.png

  2. 获取个人密钥：单击 查看密钥，进入控制台的 API 密钥管理界面，可查看您的个人密钥，若是新用户可单击【新建密钥】按钮创建个人密钥。
    image2.png

paddle 预训练模型接口

  • URL：https://www.7-an.com:5000/api/paddle
  • Method：POST

请求参数

参数 类型 必填 说明
ImageBase64 String 必填 暂时不支持 URL，后续会补充
IsCorrection Int 否 数字 1 或 0，1 使用校正，0 不使用，图片校准默认为 0

请求示例

json 格式请求

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{
    "ImageBase64":ImageBase64Data,
    "IsCorrection":1,
}

响应的结果与使用腾讯云 api 封装的接口相同。

具体实例

Python 示例

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import base64
import requests
#image转base64
def encode_base64(file):
    with open(file,'rb') as f:
        img_data = f.read()
        base64_data = base64.b64encode(img_data)
        return base64_data
# 读取图片
file = "./test.jpg"
base64_data = encode_base64(file)
img_str = base64_data.decode()   #img_str是字符串类型变量，decode()对字节类型变量进行解码，bytes->str
Data = {
    "ImageBase64":img_str,
    "IsCorrection":1,
    "SecretId":"xxx",
    "SecretKey":"xxx"
}
#访问服务
result = requests.post('http://www.7-an.com:5000/api/paddle',data=Data)
print(result.text)

Python 实现如上，主要是参数以及图片转 base64，对于其他语言来说也是一样，都是在代码中设置好参数之后，将读取的图片转为 base64 再用 POST 请求我们的接口，获得返回结果。

Java 示例

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import java.io.*;
import java.net.HttpURLConnection;
import java.net.URL;
import java.util.Base64;
import com.alibaba.fastjson2.JSONObject;

public class demo {
    public static String img2base64(String path) throws IOException {
        File file = new File(path);
        InputStream inputStream = new FileInputStream(file);
        byte[] buffer = new byte[(int) file.length()];
        inputStream.read(buffer);
        inputStream.close();

        // 将图片转换为 Base64 编码的字符串
        String imageBase64 = Base64.getEncoder().encodeToString(buffer);
        return imageBase64;
    }
    public static void main(String[] args) throws Exception  {
        // 创建 URL 对象
        URL url = new URL("http://www.7-an.com:5000/api/paddle");

        // 打开连接
        HttpURLConnection connection = (HttpURLConnection) url.openConnection();
        connection.setRequestMethod("POST");

        // 设置请求头信息
        connection.setRequestProperty("Content-Type", "application/json");
        connection.setRequestProperty("Accept", "application/json");

        // 启用输出流，向服务器发送数据
        connection.setDoOutput(true);

        String imgPath = "test.jpg";
        String base64Img = img2base64(imgPath);
        // 创建 JSON 请求数据
        JSONObject jsonObject = new JSONObject();
        jsonObject.put("ImageBase64", base64Img);
        jsonObject.put("IsCorrection", 1);

        String requestBody = jsonObject.toJSONString();

        // 发送请求数据
        try(OutputStream os = connection.getOutputStream()) {
            byte[] input = requestBody.getBytes("utf-8");
            os.write(input, 0, input.length);
        }

        // 读取响应
        try(BufferedReader br = new BufferedReader(
                new InputStreamReader(connection.getInputStream(), "utf-8"))) {
            StringBuilder response = new StringBuilder();
            String responseLine = null;
            while ((responseLine = br.readLine()) != null) {
                response.append(responseLine.trim());
            }
            System.out.println(response.toString());
        }
    }
}

java 需要装一个 com.alibaba.fastjson2.JSONObject 包。

Nodejs 示例

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const axios = require("axios");
const fs = require("fs");
// Base64编码
let img_raw = fs.readFileSync("../test.jpg");
let img_b64 = img_raw.toString("base64");

// 发送请求
axios
  .post("http://www.7-an.com:5000/api/paddle", {
    ImageBase64: img_b64,
    IsCorrection: 1,
  })
  .then((res) => {
    console.log(res.data);
  });

.NET 示例

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using System.Net.Http;

HttpClient client = new HttpClient();
byte[] imgBytes = File.ReadAllBytes("../test.jpg");
string imgBase64 = Convert.ToBase64String(imgBytes);
var values = new Dictionary<string, string>
{
{ "ImageBase64", imgBase64 },
{ "IsCorrection", "1" }
};

string url = "http://www.7-an.com:5000/api/paddle";

var data = new FormUrlEncodedContent(values);
var response = await client.PostAsync(url, data);
string responseString = await response.Content.ReadAsStringAsync();
Console.WriteLine(responseString);

在 visual studio 上或者其他地方创建一个 donet 框架的项目，把代码复制过去就能使用了。

Go 示例

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package main

import (
    "bytes"
    "encoding/base64"
    "encoding/json"
    "fmt"
    "io/ioutil"
    "net/http"
    "unsafe"
)

func main() {
    // 读取本地图片文件
    fileData, err := ioutil.ReadFile("../test.jpg")
    if err != nil {
        panic(err)
    }
    // 将图片文件转换成base64编码
    imageBase64 := base64.StdEncoding.EncodeToString(fileData)

    //在这里编辑Json串
    song := make(map[string]string)
    song["ImageBase64"] = imageBase64
    song["IsCorrection"] = "1"
    bytesData, _ := json.Marshal(song)

    res, err := http.Post("http://www.7-an.com:5000/api/paddle",
                          "application/json;charset=utf-8", bytes.NewBuffer([]byte(bytesData)))
    if err != nil {
        fmt.Println("Fatal error ", err.Error())
    }

    defer res.Body.Close()

    content, err := ioutil.ReadAll(res.Body)
    if err != nil {
        fmt.Println("Fatal error ", err.Error())
    }

    str := (*string)(unsafe.Pointer(&content)) //转化为string,优化内存
    fmt.Println(*str)

}

本地配置好环境之后，代码复制过去之后，命令行运行：

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go run demo.go

Cpp 示例

需要引入库的 HTTP 函数

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#include <iostream>
#include <string>
#include <vector>
#include <sstream>
#include <fstream>
#include <malloc.h>
#include "HTTPRequest.hpp"

using namespace std;


static const std::string base64_chars =
"ABCDEFGHIJKLMNOPQRSTUVWXYZ"
"abcdefghijklmnopqrstuvwxyz"
"0123456789+/";

static inline bool is_base64(unsigned char c) {
    return (isalnum(c) || (c == '+') || (c == '/'));
}

std::string base64_encode(const char* bytes_to_encode, unsigned int in_len)
{
    std::string ret;
    int i = 0;
    int j = 0;
    unsigned char char_array_3[3];
    unsigned char char_array_4[4];

    while (in_len--)
        {
            char_array_3[i++] = *(bytes_to_encode++);
            if (i == 3)
            {
                char_array_4[0] = (char_array_3[0] & 0xfc) >> 2;
                char_array_4[1] = ((char_array_3[0] & 0x03) << 4) + ((char_array_3[1] & 0xf0) >> 4);
                char_array_4[2] = ((char_array_3[1] & 0x0f) << 2) + ((char_array_3[2] & 0xc0) >> 6);
                char_array_4[3] = char_array_3[2] & 0x3f;
                for (i = 0; (i < 4); i++)
                    {
                        ret += base64_chars[char_array_4[i]];
                    }
                i = 0;
            }
        }
    if (i)
    {
        for (j = i; j < 3; j++)
            {
                char_array_3[j] = '\0';
            }

        char_array_4[0] = (char_array_3[0] & 0xfc) >> 2;
        char_array_4[1] = ((char_array_3[0] & 0x03) << 4) + ((char_array_3[1] & 0xf0) >> 4);
        char_array_4[2] = ((char_array_3[1] & 0x0f) << 2) + ((char_array_3[2] & 0xc0) >> 6);
        char_array_4[3] = char_array_3[2] & 0x3f;

        for (j = 0; (j < i + 1); j++)
            {
                ret += base64_chars[char_array_4[j]];
            }

        while ((i++ < 3))
            {
                ret += '=';
            }

    }
    return ret;
}



int main() {
    fstream f;
    f.open("test.jpg", ios::in | ios::binary);
    f.seekg(0, std::ios_base::end);     //设置偏移量至文件结尾
    std::streampos sp = f.tellg();      //获取文件大小
    int size = sp;

    char* buffer = (char*)malloc(sizeof(char) * size);
    f.seekg(0, std::ios_base::beg);     //设置偏移量至文件开头
    f.read(buffer, size);                //将文件内容读入buffer
    cout << "file size:" << size << endl;

    string imgBase64 = base64_encode(buffer, size);         //编码
    cout << "img base64 encode size:" << imgBase64.size() << endl;

    try
    {
        http::Request request{ "http://www.7-an.com:5000/api/paddle" };
        // c++的Json比较复杂，没有使用网上的Json相关库，而是用的字符串拼接，用起来比较麻烦。
        const std::string body = "{\"IsCorrection\": 1, \"ImageBase64\": \"" + imgBase64 + "\"}";
        const auto response = request.send("POST", body, {
        {"Content-Type", "application/json"}
    });
        std::cout << std::string{ response.body.begin(), response.body.end() } << '\n'; // print the result
    }
    catch (const std::exception& e)
    {
        std::cerr << "Request failed, error: " << e.what() << '\n';
    }

    return 0;
}

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