腾讯云OCR助力完成快速录入工单
原创腾讯云OCR助力完成快速录入工单
原创
半月无霜
修改于 2025-01-03 19:21:53
修改于 2025-01-03 19:21:53
代码可运行
运行总次数：0
代码可运行
一、业务需求背景
先说业务场景，公司在运营过程中，总会因为各种各样的原因，导致客户投诉。
有一部分是线上小程序投诉，这点没什么，数据直接落库，后续很容易进行追踪问题并解决。
难的是另外一部分客户投诉，由于是门店POS点单，往往客户只有一张小票。
在这种情况下，客户投诉只能提供小票，门店只能拍照或者截图，将问题上报，再由总店运营人员将问题录入系统。
简单问题，运营人员录入后自己能够解决；复杂问题需要开发介入解决，这一来二去，简单问题都可能拖到第二天才能解决，更别提需要开发介入的复杂客诉了。
如何解决这种问题？我们分析下来，一大部分时间都在于，各门店收到投诉录入的这一步。
门店人员一方面要服务下单出餐，一方面要接收小票截图上报，而这上报的一步，要输入一大长串的订单号，并描述出现了什么问题。
所以一旦在高峰期，这种客诉的单子就只能积压，而这一等就等到了深夜，往往只能等到第二天才能在系统上看到客诉情况。
餐饮这一块，最注重客户体验，门店需要及时响应解决；如果总店想要及时发现分店情况，那就需要另一种更为快捷的上报方式。
但公司在这一块，采用了其他方案进行录入，但我个人推荐更优秀成熟的产品来完成这一步操作，腾讯云OCR完美匹配我的需求。
二、入门腾讯云OCR
腾讯云OCR是腾讯云推出的一款强大的图像识别服务，可以精准快速的将图片中的文字内容提取出来。它提供有不同种类的预识别场景，能够处理多种不同场景下的图片，适用于政务处理、票据核销、行业表单填写、国际物流管理、人寿保险理赔、A在线问诊、律师事务所合同审查及供应链合同审核等多种应用场景。
在代码的开发编写前，可以使用OCR Demo试用一下
image-20250103134408234
可以看到效果非常好，能精准的识别票据中的title、content
而且还可以返回文字识别区域的坐标，这对于我们录入后续的内容非常有帮助，也就是可操作性非常大
三、助力快速录入
在编码开始前，需要一定的Java基础，当然腾讯云OCR有其他语言的SDK及接口文档，由于本人是Java开发，首选当然是Java
好的，引入两个maven依赖
<dependency>
<groupId>com.tencentcloudapi</groupId>
<artifactId>tencentcloud-sdk-java</artifactId>
<version>3.1.1165</version>
</dependency>
<dependency>
<groupId>com.tencentcloudapi</groupId>
<artifactId>tencentcloud-sdk-java-ocr</artifactId>
<version>3.1.1162</version>
</dependency>在java开发首选，还是SpringBoot主导的web项目，相关的依赖我就不列了
我们将主要的认证抽取出bean，将secretId和secretKey放到我们的配置文件中
tencent-api:
secret-id: xxxxxxxxxxxx
secret-key: xxxxxxxxxxx package com.banmoon.config;
import lombok.Data;
import org.springframework.boot.context.properties.ConfigurationProperties;
import org.springframework.context.annotation.Configuration;
@Data
@Configuration
@ConfigurationProperties("tencent-api")
public class TencentApiProperties {
/**
* 腾讯云SecretId
*/
private String secretId;
/**
* 腾讯云SecretKey
*/
private String secretKey;
} package com.banmoon.config;
import com.tencentcloudapi.common.Credential;
import com.tencentcloudapi.common.profile.ClientProfile;
import com.tencentcloudapi.common.profile.HttpProfile;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import javax.annotation.Resource;
@Configuration
public class TencentApiConfig {
public static final String OCR_CLIENT_PROFILE = "ocrClientProfile";
@Resource
private TencentApiProperties tencentApiProperties;
@Bean
public Credential credential() {
return new Credential(tencentApiProperties.getSecretId(), tencentApiProperties.getSecretKey());
}
@Bean(OCR_CLIENT_PROFILE)
public ClientProfile ocrClientProfile() {
HttpProfile httpProfile = new HttpProfile();
httpProfile.setEndpoint("ocr.tencentcloudapi.com");
ClientProfile clientProfile = new ClientProfile();
clientProfile.setHttpProfile(httpProfile);
return clientProfile;
}
}配置这一块就好了，接下来就是调用腾讯云OCR接口了
package com.banmoon.controller;
import cn.hutool.core.codec.Base64;
import com.banmoon.business.obj.dto.ResultData;
import com.banmoon.obj.request.GeneralAccurateOcrRequest;
import com.tencentcloudapi.common.Credential;
import com.tencentcloudapi.common.exception.TencentCloudSDKException;
import com.tencentcloudapi.common.profile.ClientProfile;
import com.tencentcloudapi.ocr.v20181119.OcrClient;
import com.tencentcloudapi.ocr.v20181119.models.GeneralAccurateOCRRequest;
import com.tencentcloudapi.ocr.v20181119.models.GeneralAccurateOCRResponse;
import io.swagger.annotations.Api;
import io.swagger.annotations.ApiOperation;
import lombok.RequiredArgsConstructor;
import lombok.extern.slf4j.Slf4j;
import org.springframework.validation.annotation.Validated;
import org.springframework.web.bind.annotation.ModelAttribute;
import org.springframework.web.bind.annotation.PostMapping;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RestController;
import org.springframework.web.multipart.MultipartFile;
import java.io.IOException;
import java.util.Objects;
@Slf4j
@Api(tags = "ocr测试")
@Validated
@RestController
@RequestMapping("/ocr")
@RequiredArgsConstructor
public class OcrController {
private final Credential credential;
private final ClientProfile clientProfile;
@ApiOperation("精准OCR识别")
@PostMapping("/generalAccurateOcr")
public ResultData<?> generalAccurateOcr(@ModelAttribute GeneralAccurateOcrRequest request) throws TencentCloudSDKException, IOException {
MultipartFile file = request.getFile();
String imgUrl = request.getImgUrl();
OcrClient client = new OcrClient(credential, "", clientProfile);
GeneralAccurateOCRRequest ocrReq = new GeneralAccurateOCRRequest();
ocrReq.setImageUrl(imgUrl);
if (Objects.nonNull(file)) {
byte[] bytes = file.getBytes();
String base64 = Base64.encode(bytes);
ocrReq.setImageBase64(base64);
}
GeneralAccurateOCRResponse resp = client.GeneralAccurateOCR(ocrReq);
return ResultData.success(resp);
}
}简单的代码，先简单看看精准识别OCR返回了啥内容，我找了业务上的一张小票，避免泄露公司相关信息，下面这张图片会马赛克处理
image-20250103183329074
我们识别一下这张图片，看看响应结果
/*
* 提示：该行代码过长，系统自动注释不进行高亮。一键复制会移除系统注释
* 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*/这边我们主要看这一个结果，detectedText就能获取到订单编号
{
"header": {},
"skipSign": false,
"wordCoordPoint": [],
"detectedText": "订单编号:14Q46AEK9KEM8",
"confidence": 100,
"polygon": [
{
"header": {},
"skipSign": false,
"x": 418,
"y": 655,
"stream": false
},
{
"header": {},
"skipSign": false,
"x": 692,
"y": 695,
"stream": false
},
{
"header": {},
"skipSign": false,
"x": 688,
"y": 726,
"stream": false
},
{
"header": {},
"skipSign": false,
"x": 413,
"y": 686,
"stream": false
}
],
"words": [],
"advancedInfo": "{\"Parag\":{\"ParagNo\":20}}",
"itemPolygon": {
"header": {},
"skipSign": false,
"x": 519,
"y": 781,
"width": 279,
"height": 37,
"stream": false
},
"stream": false
}所以，只要确定了位置，就能准确的识别出订单编号，有了订单编号，我们就能快速的进行上报问题
再写一个接口，这个接口将图片识别之后，抽取出指定的订单编号；
我们主要是对TextDetection数据进行过滤清洗，我这边比较简单判断一下
@ApiOperation("精准OCR识别-抽取订单编号")
@PostMapping("/generalAccurateOcrReturnOrderNumber")
public ResultData<String> generalAccurateOcrReturnOrderNumber(GeneralAccurateOcrRequest request) throws TencentCloudSDKException, IOException {
ResultData<?> resultData = this.generalAccurateOcr(request);
if (resultData.isSuccess()) {
GeneralAccurateOCRResponse resp = (GeneralAccurateOCRResponse) resultData.getData();
String orderNumber = Arrays.stream(resp.getTextDetections())
.map(TextDetection::getDetectedText)
.filter(detectedText -> detectedText.startsWith("订单编号"))
.findFirst()
.map(text -> StrUtil.subSuf(text, 5))
.orElse(null);
return ResultData.success(orderNumber);
}
return ResultData.fail();
} {
"errCode": 0,
"errMsg": "成功",
"data": "14Q46AEK9KEM8"
}针对更复杂的场景，最好通过ItemPolygon来确定目标位置，还有文本结合处理的情况，也需要坐标固定
image-20250103185627146
四、最后
在上面的示例中，仅仅只需要简单的代码，就能完成对腾讯云OCR的调用。
我这边的代码比较简单，后续的功能涉及业务，就不再展示了。
最后介绍一下腾讯云OCR产品优势
- 高精度
- 支持任意版式的卡证票据识别，各字段精度均处于业界领先水平，文本基础识别准确率达到98%以上，文本结构化准确率达到85%以上。
- 完备性
- 支持多种常见版式的数据结构化提取，如警察证、教师资格证、道路运输证等，适用于多行业场景。
- 易用性
- 用户仅需简单的几步配置，即可定制个性化需求模板，快速提取结构化数据，实现高效录入。
原创声明：本文系作者授权腾讯云开发者社区发表，未经许可，不得转载。
如有侵权，请联系 cloudcommunity@tencent.com 删除。
原创声明：本文系作者授权腾讯云开发者社区发表，未经许可，不得转载。
如有侵权，请联系 cloudcommunity@tencent.com 删除。
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