人工智能助力复工复产，模版 OCR 轻松搞定健康码识别

{"value":"### **背景介绍**\n在有序推进复工复产过程中，公司为完成常态化核酸筛查工作，北京和上海两地办公室的员工需要每天提交本人所在地的健康宝/随申码和行程码。有关部门收到上传图片后，要核查每位员工的核酸状态，并确认是否去过高风险地区，审核工作需要花费大量的时间和人力，目前急需寻求一种既能高效采集员工健康信息，又能保证员工个人健康数据隐私的人工智能解决方案来应对繁重的健康数据审核工作。\n\n### **目前该公司遇到的难点可以归结为如下方面：**\n- 图片数量暴增：需要审核的健康码/行程码等图片每天都在大量增加。\n- 传统文字识别无法满足需求：由于图片来源不固定，可能为手机截屏（分辨率不固定），或者手机屏幕翻拍（拍摄角度随机），传统文字识别技术无法通过固定位置来准确获取文字内容。\n\n待处理图片示例\n\n\n\n- 机器学习方面研发能力弱：如果针对三码识别单独研发新功能，开发周期过长，无法满足当下需求。\n- 个人健康数据安全：健康信息属于员工个人隐私数据，要最大程度保证这些数据的安全。\n- 服务器运维成本高，预算有限：图片上传会随时随地发生，需要有稳定的计算资源支持，如果采用传统架构会加大运维成本。\n\n### **员工健康信息文字识别需求分析**\n针对三码（健康码/随申码/行程码）内需要提取的文字信息分别为：\n\n\n\n如图所示，三码中要提取的文字信息分别位于图片中相对固定的区域，所以可以使用通用模版文字识别功能来通过预定义模版实现文字内容提取。\n\n亚马逊云科技的 AI Solution Kit 解决方案中的文本识别类功能包括：通用文字识别 OCR（支持简体/繁体），自定义模版文字识别 OCR 和车牌识别，其中自定义模版文字识别功能（Custom OCR）可以基于预定义的模版信息，针对固定版式的票据或表格，自动识别其中的文字内容并返回结果，可以满足健康信息提取的需求。\n\n所以，只需要针对三类截图创建好对应的模版，就可以提取截图中的健康信息了。在使用上只需在亚马逊云平台上部署该解决方案，就可以马上调用模版文字识别功能对应的 URL 发送图片请求，从而获得所需的健康信息，不需要任何额外的机器学习知识，开发量极少，非常符合现有的公司需求。\n\n### **利用模版 OCR 解决方案识别健康信息**\n具体操作可以分为四个步骤：部署解决方案，创建自定义模版，开发调用逻辑完成文字识别并结构化输出结果。\n\n\n\n首先是部署 AI Solution Kit 解决方案，通过 AI solution kit 解决方案的部署链接与实施手册（[https://awslabs.github.io/aws-ai-solution-kit/zh/](https://awslabs.github.io/aws-ai-solution-kit/zh/) ），可以在10分钟内将方案部署完成。由于方案整体设计是基于无服务器架构的，所以只会按调用量付费，不用担心会有额外的支出(成本预估：[https://awslabs.github.io/aws-ai-solution-kit/zh/deploy-custom-ocr/#_7 ](https://awslabs.github.io/aws-ai-solution-kit/zh/deploy-custom-ocr/#_7 ))，在 Amazon CloudFormation 堆栈（Stack）创建成功后，就可以在 Amazon CloudFormation 的输出（Outputs）页面看到基于 Amazon API Gateway 的调用 URL，对应 URL 名称（Key）为 CustomOCR。\n\n\n\n接下来我们可以测试一下生成的 API 调用 URL，首先需要新建一个行程码识别模版。这里我们使用开源图像处理软件 [GIMP](https://www.gimp.org/downloads/ ) （[https://www.gimp.org/downloads/ ](https://www.gimp.org/downloads/ )）来获取坐标点。如下图所示，先在在电脑上用 GIMP 打开行程码手机截图后，再把鼠标移动到图片上，就可以看到指定位置坐标点X，Y值，请按照**左上，右上，右下，左下**的顺时针顺序创建矩形框四个坐标点序列。\n\n先把鼠标移动到行程卡中日期的四个角上（下图中矩形框位置），分别记录下四角对应坐标（坐标值显示在 GIMP 窗口的左下角区域）并指定该识别区域名称为“更新时间”。\n\n\n\n用同样的方式，继续标注“手机号码”与“途径地区”的文字识别区域，标注好后的完整 JSON 数据如下：\n```\n[[[116, 335], [410, 335], [410, 374], [116, 374]], \"手机号码\"],\n[[[176, 387], [452, 384], [452, 429], [176, 429]], \"更新时间\"],\n[[[53, 710], [465, 710], [465, 837], [54, 837]], \"途经地区\"]\n```\n接下来需要把图片转码成模版OCR能够处理的 Base64 格式，我们可以使用 Base64Guru （[https://base64.guru/converter/encode/image](https://base64.guru/converter/encode/image)） 在线上传图片，即可将图片转换为 Base64 编码的格式，转换完成后，与刚才标注的识别区域 JSON 合并成完整的 JSON 数据，如下：\n```\n{\n \"type\" : \"add\",\n \"img\": \"行程码图片的Base64编码\",\n \"template\": [\n [[[116, 335], [410, 335], [410, 374], [116, 374]], \"手机号码\"],\n [[[176, 387], [452, 384], [452, 429], [176, 429]], \"更新时间\"],\n [[[53, 710], [465, 710], [465, 837], [54, 837]], \"途经地区\"]\n ]\n}\n```\n然后我们通过如下 Python 代码，把创建模版的请求发送到模版 OCR 调用 URL，完成行程码模版的创建。\n```\nimport json\nimport requests\nimport base64\n\njkb_img = open('jkb-template.png', 'rb')\nbase64_data = base64.b64encode(jkb_img.read())\npayload = json.dumps({\n \"type\" : \"add\",\n\"img\": str(base64_data, encoding=\"utf-8\"),\n\"template\": [\n [[[116, 335], [410, 335], [410, 374], [116, 374]], \"手机号码\"],\n [[[176, 387], [452, 384], [452, 429], [176, 429]], \"更新时间\"],\n [[[53, 710], [465, 710], [465, 837], [54, 837]], \"途经地区\"]\n ]\n})\nurl = \"https://[API-ID].execute-api.[REGION-ID].amazonaws.com.cn/prod/custom-ocr/\"\nresponse = requests.request(\"POST\", url, data=payload)\njson.loads(response.text)\n```\n输出结果：\n```\n{'template_id': '3e2183c63b139f6870c7d0ac53ffdc138bd21c95'}\n```\n在输出中里我们看到模版已经创建好了，对应的模版 ID（template_id）为‘3e2183c63b139f6870c7d0ac53ffdc138bd21c95’，请记下模版 ID 用于后面的文字识别。\n\n我们找来另一张翻拍格式的行程码图片，用来测试识别效果\n\n\n\n我们用了短短12行代码，就完成了行程码健康信息的提取任务。\n```\nimport base64\nimport json\nimport requests\nimport pandas as pd\n\njkb_img = open('scan-xjm-1.jpeg', 'rb')\nbase64_data = base64.b64encode(jkb_img.read())\npayload = json.dumps({\n \"template_id\": \"3e2183c63b139f6870c7d0ac53ffdc138bd21c95\",\n \"img\": str(base64_data, encoding=\"utf-8\")\n})\nurl = \"https://gqi4z1k9fl.execute-api.cn-northwest-1.amazonaws.com.cn/prod/custom-ocr/\"\nresponse = requests.request(\"POST\", url, data=payload)\ndf = pd.DataFrame.from_dict(json.loads(response.text))\n```\n::: hljs-center\n\n\n\n:::\n可以看出，AI Solution Kit 的模版文字识别功能能够自动将不同手机分辨率截图甚至是翻拍的图像，准确检测识别区域，并进行精准文字识别，提取到所需的行程码信息。\n\n接下来，我们用与创建行程码模版相同的方法，创建健康宝模版，创建健康宝模版的 JSON 数据如下：\n```\n{\n \"type\" : \"add\",\n \"img\": \"健康宝图像的Base64编码\",\n \"template\": [\n [[[173, 177], [364, 173], [364, 210], [173, 210]], \"日期\"],\n [[[211, 206], [319, 210], [319, 233], [208, 231]], \"时间\"],\n [[[190, 575], [361, 575], [361, 628], [191, 629]], \"状态\"],\n [[[217, 668], [317, 671], [309, 709], [205, 710]], \"核酸\"],\n [[[386, 658], [424, 660], [424, 708], [386, 708]], \"核酸时间\"],\n [[[263, 810], [483, 828], [483, 864], [289, 867]], \"姓名\"],\n [[[220, 876], [482, 870], [479, 909], [222, 908]], \"身份证号\"],\n [[[277, 917], [478, 909], [482, 954], [272, 950]], \"查询时间\"],\n [[[272, 955], [483, 956], [475, 990], [269, 992]], \"失效时间\"]\n ]\n}\n```\n::: hljs-center\n\n\n\n:::\n进行测试验证后，输出结果如下：\n```\nimport base64\nimport json\nimport requests\nimport pandas as pd\n\njkb_img = open('jkb-1.png', 'rb')\nbase64_data = base64.b64encode(jkb_img.read())\npayload = json.dumps({\n \"template_id\": \"158ad1b39a4cba9ce4a1cade1fae2bb0740ccb10\",\n \"img\": str(base64_data, encoding=\"utf-8\")\n})\nurl = \"https://[API-ID].execute-api.[REGION-ID].amazonaws.com.cn/prod/custom-ocr/\"\nresponse = requests.request(\"POST\", url, data=payload)\ndf = pd.DataFrame.from_dict(json.loads(response.text))\n```\n输出结果：\n\n::: hljs-center\n\n\n\n:::\n可见，模版 OCR 同样可以完成较复杂的北京健康宝的识别任务。最后，让我们来创建随申码的模版，创建随申码模版的 JSON 数据如下：\n```\n\n{\n \"type\" : \"add\",\n \"img\": \"随申码参考样图的Base64编码\"\n \"template\": [\n [[[189, 256], [257, 261], [261, 293], [192, 296]], \"姓名\"],\n [[[140,366], [356,369], [350,406], [138,402]], \"查询时间\"],\n [[[208,673], [285,675], [284,713], [211,712]], \"状态\"],\n [[[108,774], [181,777], [181,838], [114,839]], \"天数\"]\n ]\n}\n```\n::: hljs-center\n\n\n\n:::\n随申码识别结果如下：\n```\nimport base64\nimport json\nimport requests\nimport pandas as pd\n\njkb_img = open('xsm_1.png', 'rb')\nbase64_data = base64.b64encode(jkb_img.read())\npayload = json.dumps({\n \"template_id\": \"531030f86c071571e54c19c9ac5c63751e97cddf\",\n \"img\": str(base64_data, encoding=\"utf-8\")\n})\nurl = \"https://[API-ID].execute-api.[REGION-ID].amazonaws.com.cn/prod/custom-ocr/\"\nresponse = requests.request(\"POST\", url, data=payload)\ndf = pd.DataFrame.from_dict(json.loads(response.text))\n```\n输出结果：\n\n::: hljs-center\n\n\n\n:::\n### **示例代码**\n文中示例代码请参考如下链接：\n\n[https://github.com/awslabs/aws-ai-solution-kit/tree/main/samples/custom-ocr-healthy-code](https://github.com/awslabs/aws-ai-solution-kit/tree/main/samples/custom-ocr-healthy-code)\n\n### **总结**\nAI Solution Kit 解决方案中的模版文本识别功能通过自动部署预训练的文本识别模型，结合大词库，增强了对中文语言的处理与识别能力，能够通过预定义模版自动校正并识别结构化信息，从而提高了输入转化效率。基于亚马逊云科技的 Amazon CloudFormation 自动在 Amazon API Gateway 中创建调用 RESTful API ，用户在部署解决方案后只需将 HTTP（s） 请求参数提交到 Amazon API Gateway 自动创建的 URL 即可实现文本识别功能。该解决方案基于 Amazon Lambda 等无服务架构，用户无需运维任何基础设施，只需按实际使用量支付费用。用户数据全程不做持久化存储，计算和存储资源在 API 执行完毕后即销毁。AI Solution Kit 开源解决方案中更多更有意思的功能等待您去探索。[https://github.com/awslabs/aws-ai-solution-kit](https://github.com/awslabs/aws-ai-solution-kit)\n\n### **本篇作者**\n\n\n\n**严一**\n亚马逊 Amazon 创新解决方案架构师，负责基于 Amazon 的云计算方案的架构设计，在应用开发, Serverless, 大数据方向有丰富的实践经验。\n\n\n\n**何孝霆**\n亚马逊 Amazon 创新解决方案架构师，负责基于 Amazon 的云计算方案的架构设计，在应用开发, 人智能，Serverless 方向有丰富的实践经验。","render":"<h3><a id=\"_0\"></a><strong>背景介绍</strong></h3>\n<p>在有序推进复工复产过程中，公司为完成常态化核酸筛查工作，北京和上海两地办公室的员工需要每天提交本人所在地的健康宝/随申码和行程码。有关部门收到上传图片后，要核查每位员工的核酸状态，并确认是否去过高风险地区，审核工作需要花费大量的时间和人力，目前急需寻求一种既能高效采集员工健康信息，又能保证员工个人健康数据隐私的人工智能解决方案来应对繁重的健康数据审核工作。</p>\n<h3><a id=\"_3\"></a><strong>目前该公司遇到的难点可以归结为如下方面：</strong></h3>\n<ul>\n<li>图片数量暴增：需要审核的健康码/行程码等图片每天都在大量增加。</li>\n<li>传统文字识别无法满足需求：由于图片来源不固定，可能为手机截屏（分辨率不固定），或者手机屏幕翻拍（拍摄角度随机），传统文字识别技术无法通过固定位置来准确获取文字内容。</li>\n</ul>\n<p>待处理图片示例</p>\n<p><img src=\"https://dev-media.amazoncloud.cn/a43a7dbc28824c8291b3809eee789ba0_image.png\" alt=\"image.png\" /></p>\n<ul>\n<li>机器学习方面研发能力弱：如果针对三码识别单独研发新功能，开发周期过长，无法满足当下需求。</li>\n<li>个人健康数据安全：健康信息属于员工个人隐私数据，要最大程度保证这些数据的安全。</li>\n<li>服务器运维成本高，预算有限：图片上传会随时随地发生，需要有稳定的计算资源支持，如果采用传统架构会加大运维成本。</li>\n</ul>\n<h3><a id=\"_15\"></a><strong>员工健康信息文字识别需求分析</strong></h3>\n<p>针对三码（健康码/随申码/行程码）内需要提取的文字信息分别为：</p>\n<p><img src=\"https://dev-media.amazoncloud.cn/7ad2eb817bf9490795ee17c149edc821_image.png\" alt=\"image.png\" /></p>\n<p>如图所示，三码中要提取的文字信息分别位于图片中相对固定的区域，所以可以使用通用模版文字识别功能来通过预定义模版实现文字内容提取。</p>\n<p>亚马逊云科技的 AI Solution Kit 解决方案中的文本识别类功能包括：通用文字识别 OCR（支持简体/繁体），自定义模版文字识别 OCR 和车牌识别，其中自定义模版文字识别功能（Custom OCR）可以基于预定义的模版信息，针对固定版式的票据或表格，自动识别其中的文字内容并返回结果，可以满足健康信息提取的需求。</p>\n<p>所以，只需要针对三类截图创建好对应的模版，就可以提取截图中的健康信息了。在使用上只需在亚马逊云平台上部署该解决方案，就可以马上调用模版文字识别功能对应的 URL 发送图片请求，从而获得所需的健康信息，不需要任何额外的机器学习知识，开发量极少，非常符合现有的公司需求。</p>\n<h3><a id=\"_OCR__26\"></a><strong>利用模版 OCR 解决方案识别健康信息</strong></h3>\n<p>具体操作可以分为四个步骤：部署解决方案，创建自定义模版，开发调用逻辑完成文字识别并结构化输出结果。</p>\n<p><img src=\"https://dev-media.amazoncloud.cn/f17c372edb57436888bd4a659372f22b_image.png\" alt=\"image.png\" /></p>\n<p>首先是部署 AI Solution Kit 解决方案，通过 AI solution kit 解决方案的部署链接与实施手册（<a href=\"https://awslabs.github.io/aws-ai-solution-kit/zh/\" target=\"_blank\">https://awslabs.github.io/aws-ai-solution-kit/zh/</a> ），可以在10分钟内将方案部署完成。由于方案整体设计是基于无服务器架构的，所以只会按调用量付费，不用担心会有额外的支出(成本预估：<a href=\"https://awslabs.github.io/aws-ai-solution-kit/zh/deploy-custom-ocr/#_7\" target=\"_blank\">https://awslabs.github.io/aws-ai-solution-kit/zh/deploy-custom-ocr/#_7 </a>)，在 Amazon CloudFormation 堆栈（Stack）创建成功后，就可以在 Amazon CloudFormation 的输出（Outputs）页面看到基于 Amazon API Gateway 的调用 URL，对应 URL 名称（Key）为 CustomOCR。</p>\n<p><img src=\"https://dev-media.amazoncloud.cn/626ce7a770404d6290ffaf8f8b1f0384_image.png\" alt=\"image.png\" /></p>\n<p>接下来我们可以测试一下生成的 API 调用 URL，首先需要新建一个行程码识别模版。这里我们使用开源图像处理软件 <a href=\"https://www.gimp.org/downloads/\" target=\"_blank\">GIMP</a> （<a href=\"https://www.gimp.org/downloads/\" target=\"_blank\">https://www.gimp.org/downloads/ </a>）来获取坐标点。如下图所示，先在在电脑上用 GIMP 打开行程码手机截图后，再把鼠标移动到图片上，就可以看到指定位置坐标点X，Y值，请按照<strong>左上，右上，右下，左下</strong>的顺时针顺序创建矩形框四个坐标点序列。</p>\n<p>先把鼠标移动到行程卡中日期的四个角上（下图中矩形框位置），分别记录下四角对应坐标（坐标值显示在 GIMP 窗口的左下角区域）并指定该识别区域名称为“更新时间”。</p>\n<p><img src=\"https://dev-media.amazoncloud.cn/4fb7f5507a0047058afc8922a1529a18_image.png\" alt=\"image.png\" /></p>\n<p>用同样的方式，继续标注“手机号码”与“途径地区”的文字识别区域，标注好后的完整 JSON 数据如下：</p>\n<pre><code class=\"lang-\">[[[116, 335], [410, 335], [410, 374], [116, 374]], &quot;手机号码&quot;],\n[[[176, 387], [452, 384], [452, 429], [176, 429]], &quot;更新时间&quot;],\n[[[53, 710], [465, 710], [465, 837], [54, 837]], &quot;途经地区&quot;]\n</code></pre>\n<p>接下来需要把图片转码成模版OCR能够处理的 Base64 格式，我们可以使用 Base64Guru （<a href=\"https://base64.guru/converter/encode/image\" target=\"_blank\">https://base64.guru/converter/encode/image</a>） 在线上传图片，即可将图片转换为 Base64 编码的格式，转换完成后，与刚才标注的识别区域 JSON 合并成完整的 JSON 数据，如下：</p>\n<pre><code class=\"lang-\">{\n &quot;type&quot; : &quot;add&quot;,\n &quot;img&quot;: &quot;行程码图片的Base64编码&quot;,\n &quot;template&quot;: [\n [[[116, 335], [410, 335], [410, 374], [116, 374]], &quot;手机号码&quot;],\n [[[176, 387], [452, 384], [452, 429], [176, 429]], &quot;更新时间&quot;],\n [[[53, 710], [465, 710], [465, 837], [54, 837]], &quot;途经地区&quot;]\n ]\n}\n</code></pre>\n<p>然后我们通过如下 Python 代码，把创建模版的请求发送到模版 OCR 调用 URL，完成行程码模版的创建。</p>\n<pre><code class=\"lang-\">import json\nimport requests\nimport base64\n\njkb_img = open('jkb-template.png', 'rb')\nbase64_data = base64.b64encode(jkb_img.read())\npayload = json.dumps({\n &quot;type&quot; : &quot;add&quot;,\n&quot;img&quot;: str(base64_data, encoding=&quot;utf-8&quot;),\n&quot;template&quot;: [\n [[[116, 335], [410, 335], [410, 374], [116, 374]], &quot;手机号码&quot;],\n [[[176, 387], [452, 384], [452, 429], [176, 429]], &quot;更新时间&quot;],\n [[[53, 710], [465, 710], [465, 837], [54, 837]], &quot;途经地区&quot;]\n ]\n})\nurl = &quot;https://[API-ID].execute-api.[REGION-ID].amazonaws.com.cn/prod/custom-ocr/&quot;\nresponse = requests.request(&quot;POST&quot;, url, data=payload)\njson.loads(response.text)\n</code></pre>\n<p>输出结果：</p>\n<pre><code class=\"lang-\">{'template_id': '3e2183c63b139f6870c7d0ac53ffdc138bd21c95'}\n</code></pre>\n<p>在输出中里我们看到模版已经创建好了，对应的模版 ID（template_id）为‘3e2183c63b139f6870c7d0ac53ffdc138bd21c95’，请记下模版 ID 用于后面的文字识别。</p>\n<p>我们找来另一张翻拍格式的行程码图片，用来测试识别效果</p>\n<p><img src=\"https://dev-media.amazoncloud.cn/b7d1a163655f46b8bb0b66852fd506c8_image.png\" alt=\"image.png\" /></p>\n<p>我们用了短短12行代码，就完成了行程码健康信息的提取任务。</p>\n<pre><code class=\"lang-\">import base64\nimport json\nimport requests\nimport pandas as pd\n\njkb_img = open('scan-xjm-1.jpeg', 'rb')\nbase64_data = base64.b64encode(jkb_img.read())\npayload = json.dumps({\n &quot;template_id&quot;: &quot;3e2183c63b139f6870c7d0ac53ffdc138bd21c95&quot;,\n &quot;img&quot;: str(base64_data, encoding=&quot;utf-8&quot;)\n})\nurl = &quot;https://gqi4z1k9fl.execute-api.cn-northwest-1.amazonaws.com.cn/prod/custom-ocr/&quot;\nresponse = requests.request(&quot;POST&quot;, url, data=payload)\ndf = pd.DataFrame.from_dict(json.loads(response.text))\n</code></pre>\n<div class=\"hljs-center\">\n<p><img src=\"https://dev-media.amazoncloud.cn/58b1682fde0449a0a5c16b3ea27d4741_image.png\" alt=\"image.png\" /></p>\n</div>\n<p>可以看出，AI Solution Kit 的模版文字识别功能能够自动将不同手机分辨率截图甚至是翻拍的图像，准确检测识别区域，并进行精准文字识别，提取到所需的行程码信息。</p>\n<p>接下来，我们用与创建行程码模版相同的方法，创建健康宝模版，创建健康宝模版的 JSON 数据如下：</p>\n<pre><code class=\"lang-\">{\n &quot;type&quot; : &quot;add&quot;,\n &quot;img&quot;: &quot;健康宝图像的Base64编码&quot;,\n &quot;template&quot;: [\n [[[173, 177], [364, 173], [364, 210], [173, 210]], &quot;日期&quot;],\n [[[211, 206], [319, 210], [319, 233], [208, 231]], &quot;时间&quot;],\n [[[190, 575], [361, 575], [361, 628], [191, 629]], &quot;状态&quot;],\n [[[217, 668], [317, 671], [309, 709], [205, 710]], &quot;核酸&quot;],\n [[[386, 658], [424, 660], [424, 708], [386, 708]], &quot;核酸时间&quot;],\n [[[263, 810], [483, 828], [483, 864], [289, 867]], &quot;姓名&quot;],\n [[[220, 876], [482, 870], [479, 909], [222, 908]], &quot;身份证号&quot;],\n [[[277, 917], [478, 909], [482, 954], [272, 950]], &quot;查询时间&quot;],\n [[[272, 955], [483, 956], [475, 990], [269, 992]], &quot;失效时间&quot;]\n ]\n}\n</code></pre>\n<div class=\"hljs-center\">\n<p><img src=\"https://dev-media.amazoncloud.cn/748735ed6d444d059dedc2670493aa9b_image.png\" alt=\"image.png\" /></p>\n</div>\n<p>进行测试验证后，输出结果如下：</p>\n<pre><code class=\"lang-\">import base64\nimport json\nimport requests\nimport pandas as pd\n\njkb_img = open('jkb-1.png', 'rb')\nbase64_data = base64.b64encode(jkb_img.read())\npayload = json.dumps({\n &quot;template_id&quot;: &quot;158ad1b39a4cba9ce4a1cade1fae2bb0740ccb10&quot;,\n &quot;img&quot;: str(base64_data, encoding=&quot;utf-8&quot;)\n})\nurl = &quot;https://[API-ID].execute-api.[REGION-ID].amazonaws.com.cn/prod/custom-ocr/&quot;\nresponse = requests.request(&quot;POST&quot;, url, data=payload)\ndf = pd.DataFrame.from_dict(json.loads(response.text))\n</code></pre>\n<p>输出结果：</p>\n<div class=\"hljs-center\">\n<p><img src=\"https://dev-media.amazoncloud.cn/fc0cee38ab0646099403c3571172d6d1_image.png\" alt=\"image.png\" /></p>\n</div>\n<p>可见，模版 OCR 同样可以完成较复杂的北京健康宝的识别任务。最后，让我们来创建随申码的模版，创建随申码模版的 JSON 数据如下：</p>\n<pre><code class=\"lang-\">\n{\n &quot;type&quot; : &quot;add&quot;,\n &quot;img&quot;: &quot;随申码参考样图的Base64编码&quot;\n &quot;template&quot;: [\n [[[189, 256], [257, 261], [261, 293], [192, 296]], &quot;姓名&quot;],\n [[[140,366], [356,369], [350,406], [138,402]], &quot;查询时间&quot;],\n [[[208,673], [285,675], [284,713], [211,712]], &quot;状态&quot;],\n [[[108,774], [181,777], [181,838], [114,839]], &quot;天数&quot;]\n ]\n}\n</code></pre>\n<div class=\"hljs-center\">\n<p><img src=\"https://dev-media.amazoncloud.cn/9b460cb2055a409e96c395a473f202bb_image.png\" alt=\"image.png\" /></p>\n</div>\n<p>随申码识别结果如下：</p>\n<pre><code class=\"lang-\">import base64\nimport json\nimport requests\nimport pandas as pd\n\njkb_img = open('xsm_1.png', 'rb')\nbase64_data = base64.b64encode(jkb_img.read())\npayload = json.dumps({\n &quot;template_id&quot;: &quot;531030f86c071571e54c19c9ac5c63751e97cddf&quot;,\n &quot;img&quot;: str(base64_data, encoding=&quot;utf-8&quot;)\n})\nurl = &quot;https://[API-ID].execute-api.[REGION-ID].amazonaws.com.cn/prod/custom-ocr/&quot;\nresponse = requests.request(&quot;POST&quot;, url, data=payload)\ndf = pd.DataFrame.from_dict(json.loads(response.text))\n</code></pre>\n<p>输出结果：</p>\n<div class=\"hljs-center\">\n<p><img src=\"https://dev-media.amazoncloud.cn/e21ad18a7e2e4e66b3106509bf6c7473_image.png\" alt=\"image.png\" /></p>\n</div>\n<h3><a id=\"_204\"></a><strong>示例代码</strong></h3>\n<p>文中示例代码请参考如下链接：</p>\n<p><a href=\"https://github.com/awslabs/aws-ai-solution-kit/tree/main/samples/custom-ocr-healthy-code\" target=\"_blank\">https://github.com/awslabs/aws-ai-solution-kit/tree/main/samples/custom-ocr-healthy-code</a></p>\n<h3><a id=\"_209\"></a><strong>总结</strong></h3>\n<p>AI Solution Kit 解决方案中的模版文本识别功能通过自动部署预训练的文本识别模型，结合大词库，增强了对中文语言的处理与识别能力，能够通过预定义模版自动校正并识别结构化信息，从而提高了输入转化效率。基于亚马逊云科技的 Amazon CloudFormation 自动在 Amazon API Gateway 中创建调用 RESTful API ，用户在部署解决方案后只需将 HTTP（s） 请求参数提交到 Amazon API Gateway 自动创建的 URL 即可实现文本识别功能。该解决方案基于 Amazon Lambda 等无服务架构，用户无需运维任何基础设施，只需按实际使用量支付费用。用户数据全程不做持久化存储，计算和存储资源在 API 执行完毕后即销毁。AI Solution Kit 开源解决方案中更多更有意思的功能等待您去探索。<a href=\"https://github.com/awslabs/aws-ai-solution-kit\" target=\"_blank\">https://github.com/awslabs/aws-ai-solution-kit</a></p>\n<h3><a id=\"_212\"></a><strong>本篇作者</strong></h3>\n<p><img src=\"data:image/png;base64,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\" alt=\"ede37752c5c941dabf7344801109e496_image1.png\" rel=\"1\" /></p>\n<p><strong>严一</strong><br />\n亚马逊 Amazon 创新解决方案架构师，负责基于 Amazon 的云计算方案的架构设计，在应用开发, Serverless, 大数据方向有丰富的实践经验。</p>\n<p><img src=\"https://dev-media.amazoncloud.cn/a070fc3cb508470f9e9b6a6eb2a84f53_image.png\" alt=\"image.png\" /></p>\n<p><strong>何孝霆</strong><br />\n亚马逊 Amazon 创新解决方案架构师，负责基于 Amazon 的云计算方案的架构设计，在应用开发, 人智能，Serverless 方向有丰富的实践经验。</p>\n"}