使用Java SDK图片OCR识别接口识别图片中的文字或卡证信息,并同步返回识别出来的结果。

说明 通用OCR除了能够识别普通图片中的文字,还能识别结构化的卡证上的文字,具体请参见图片OCR检测API说明

准备工作

在进行具体的服务调用之前,请参见以下步骤,完成准备工作:
  1. 创建阿里云AccessKeyId和AccessKeySecret。具体请参见创建AccessKey
  2. 安装Java依赖。具体请参见安装Java依赖
  3. 下载并在项目工程中引入Extension.Uploader工具类

提交图片同步检测任务

接口描述
接口 功能 支持的Region 描述
ImageSyncScanRequest 同步图片OCR识别。
  • cn-shanghai
  • cn-beijing
  • cn-shenzhen
  • ap-southeast-1
对图片中的文字进行识别(scene=ocr)。
示例代码
  • 传图片url进行检测
    import com.alibaba.fastjson.JSON;
    import com.alibaba.fastjson.JSONArray;
    import com.alibaba.fastjson.JSONObject;
    import com.aliyuncs.DefaultAcsClient;
    import com.aliyuncs.IAcsClient;
    import com.aliyuncs.exceptions.ClientException;
    import com.aliyuncs.exceptions.ServerException;
    import com.aliyuncs.green.model.v20180509.ImageSyncScanRequest;
    import com.aliyuncs.http.FormatType;
    import com.aliyuncs.http.HttpResponse;
    import com.aliyuncs.http.MethodType;
    import com.aliyuncs.http.ProtocolType;
    import com.aliyuncs.profile.DefaultProfile;
    import com.aliyuncs.profile.IClientProfile;
    
    import java.util.*;
    
    public class Main {
    
        public static void main(String[] args) throws Exception {
            IClientProfile profile = DefaultProfile
                .getProfile("cn-shanghai", "请填写您的accessKeyId", "请填写您的accessKeySecret");
            DefaultProfile
                .addEndpoint("cn-shanghai", "cn-shanghai", "Green", "green.cn-shanghai.aliyuncs.com");
            IAcsClient client = new DefaultAcsClient(profile);
    
            ImageSyncScanRequest imageSyncScanRequest = new ImageSyncScanRequest();
            // 指定api返回格式
            imageSyncScanRequest.setAcceptFormat(FormatType.JSON);
            // 指定请求方法
            imageSyncScanRequest.setMethod(MethodType.POST);
            imageSyncScanRequest.setEncoding("utf-8");
            //支持http和https
            imageSyncScanRequest.setProtocol(ProtocolType.HTTP);
    
            JSONObject httpBody = new JSONObject();
            /**
             * 设置要检测的场景
             * ocr: ocr或者ocr卡证识别
             */
            httpBody.put("scenes", Arrays.asList("ocr"));
    
            /**
             * 设置待检测图片, 一张图片一个task
             * 多张图片同时检测时,处理的时间由最后一个处理完的图片决定
             * 因此通常情况下批量检测的平均rt比单张检测的要长, 一次批量提交的图片数越多,rt被拉长的概率越高
             * 这里以单张图片检测作为示例, 如果是批量图片检测,请自行构建多个task
             */
            JSONObject task = new JSONObject();
            task.put("dataId", UUID.randomUUID().toString());
    
            //设置图片链接
            task.put("url", "https://xxx.jpg");
            task.put("time", new Date());
            httpBody.put("tasks", Arrays.asList(task));
    
            //ocr卡证识别,设置识别卡证类型
            JSONObject cardExtras = new JSONObject();
            //身份证正面识别
            cardExtras.put("card", "id-card-front");
            //身份证反面
            //cardExtras.put("card", "id-card-back");
            httpBody.put("extras", cardExtras);
            imageSyncScanRequest.setHttpContent(org.apache.commons.codec.binary.StringUtils.getBytesUtf8(httpBody.toJSONString()), "UTF-8", FormatType.JSON);
            /**
             * 请设置超时时间, 服务端全链路处理超时时间为10秒,请做相应设置
             * 如果您设置的ReadTimeout小于服务端处理的时间,程序中会获得一个read timeout异常
             */
            imageSyncScanRequest.setConnectTimeout(3000);
            imageSyncScanRequest.setReadTimeout(10000);
            HttpResponse httpResponse = null;
            try {
                httpResponse = client.doAction(imageSyncScanRequest);
            } catch (ServerException e) {
                e.printStackTrace();
            } catch (ClientException e) {
                e.printStackTrace();
            } catch (Exception e){
                e.printStackTrace();
            }
    
            //服务端接收到请求,并完成处理返回的结果
            if(httpResponse != null && httpResponse.isSuccess()){
                JSONObject scrResponse = JSON.parseObject(org.apache.commons.codec.binary.StringUtils.newStringUtf8(httpResponse.getHttpContent()));
                System.out.println(JSON.toJSONString(scrResponse));
                int requestCode = scrResponse.getIntValue("code");
                //每一张图片的检测结果
                JSONArray taskResults = scrResponse.getJSONArray("data");
                if (200 == requestCode) {
                    for (Object taskResult : taskResults) {
                        //单张图片的处理结果
                        int taskCode = ((JSONObject)taskResult).getIntValue("code");
                        //图片要检测的场景的处理结果, 如果是多个场景,则会有每个场景的结果
                        JSONArray sceneResults = ((JSONObject)taskResult).getJSONArray("results");
                        if(200 == taskCode){
                            for (Object sceneResult : sceneResults) {
                                String scene = ((JSONObject)sceneResult).getString("scene");
                                String suggestion = ((JSONObject)sceneResult).getString("suggestion");
                                //do something
                                //有识别出身份证信息
                                if("review" .equals(suggestion) && "ocr".equals(scene)){
                                    JSONObject idCardInfo =  ((JSONObject) sceneResult).getJSONObject("idCardInfo");
                                    System.out.println(idCardInfo.toJSONString());
                                }
                            }
                        }else{
                            //单张图片处理失败, 原因视具体的情况详细分析
                            System.out.println("task process fail. task response:" + JSON.toJSONString(taskResult));
                         }
                    }
                } else {
                    /**
                     * 表明请求整体处理失败,原因视具体的情况详细分析
                     */
                    System.out.println("the whole image scan request failed. response:" + JSON.toJSONString(scrResponse));
                 }
            }
        }
    }
  • 传本地图片文件进行检测
    import com.alibaba.fastjson.JSON;
    import com.alibaba.fastjson.JSONArray;
    import com.alibaba.fastjson.JSONObject;
    import com.aliyuncs.DefaultAcsClient;
    import com.aliyuncs.IAcsClient;
    import com.aliyuncs.exceptions.ClientException;
    import com.aliyuncs.exceptions.ServerException;
    import com.aliyuncs.green.extension.uploader.ClientUploader;
    import com.aliyuncs.green.model.v20180509.ImageSyncScanRequest;
    import com.aliyuncs.http.FormatType;
    import com.aliyuncs.http.HttpResponse;
    import com.aliyuncs.http.MethodType;
    import com.aliyuncs.http.ProtocolType;
    import com.aliyuncs.profile.DefaultProfile;
    import com.aliyuncs.profile.IClientProfile;
    
    import java.util.*;
    
    public class Main {
    
        public static void main(String[] args) throws Exception {
            IClientProfile profile = DefaultProfile
                .getProfile("cn-shanghai", "请填写您的accessKeyId", "请填写您的accessKeySecret");
            DefaultProfile
                .addEndpoint("cn-shanghai", "cn-shanghai", "Green", "green.cn-shanghai.aliyuncs.com");
            IAcsClient client = new DefaultAcsClient(profile);
    
            ImageSyncScanRequest imageSyncScanRequest = new ImageSyncScanRequest();
            // 指定api返回格式
            imageSyncScanRequest.setAcceptFormat(FormatType.JSON);
            // 指定请求方法
            imageSyncScanRequest.setMethod(MethodType.POST);
            imageSyncScanRequest.setEncoding("utf-8");
            //支持http和https
            imageSyncScanRequest.setProtocol(ProtocolType.HTTP);
    
            JSONObject httpBody = new JSONObject();
            /**
             * 设置要检测的场景
             * ocr: ocr或者ocr卡证识别
             */
            httpBody.put("scenes", Arrays.asList("ocr"));
    
            /**
             * 设置待检测图片, 一张图片一个task,最多支持100张图片同时检测,即需要构建100个task
             * 多张图片同时检测时,处理的时间由最后一个处理完的图片决定。因此通常情况下批量检测的平均rt比单张检测的要长, 一次批量提交的图片数越多,rt被拉长的概率越高
             * 这里以单张图片检测作为示例, 如果是批量图片检测,请自行构建多个task
             * 本地图片相对于互联网图片链接来说,多了一个上传步骤,上传后取返回的链接进行检测
             */
            ClientUploader clientUploader = ClientUploader.getImageClientUploader(profile, false);
            String url = null;
            try{
                url = clientUploader.uploadFile("/Users/test/Pictures/idfront-data-1536747400633.jpg");
            }catch (Exception e){
                System.out.println("upload file to server fail."); 
            }
            JSONObject task = new JSONObject();
            task.put("dataId", UUID.randomUUID().toString());
            task.put("url", url);
            task.put("time", new Date());
            httpBody.put("tasks", Arrays.asList(task));
    
            //ocr卡证识别,设置识别卡证类型
            JSONObject cardExtras = new JSONObject();
            //身份证正面识别
            cardExtras.put("card", "id-card-front");
            //身份证反面
            //cardExtras.put("card", "id-card-back");
            httpBody.put("extras", cardExtras);
    
            imageSyncScanRequest.setHttpContent(org.apache.commons.codec.binary.StringUtils.getBytesUtf8(httpBody.toJSONString()), "UTF-8", FormatType.JSON);
            /**
             * 请设置超时时间, 服务端全链路处理超时时间为10秒,请做相应设置
             * 如果您设置的ReadTimeout小于服务端处理的时间,程序中会获得一个read timeout异常
             */
            imageSyncScanRequest.setConnectTimeout(3000);
            imageSyncScanRequest.setReadTimeout(10000);
            HttpResponse httpResponse = null;
            try {
                httpResponse = client.doAction(imageSyncScanRequest);
            } catch (ServerException e) {
                e.printStackTrace();
            } catch (ClientException e) {
                e.printStackTrace();
            } catch (Exception e){
                e.printStackTrace();
            }
    
            //服务端接收到请求,并完成处理返回的结果
            if(httpResponse != null && httpResponse.isSuccess()){
                JSONObject scrResponse = JSON.parseObject(org.apache.commons.codec.binary.StringUtils.newStringUtf8(httpResponse.getHttpContent()));
                System.out.println(JSON.toJSONString(scrResponse));
                int requestCode = scrResponse.getIntValue("code");
                //每一张图片的检测结果
                JSONArray taskResults = scrResponse.getJSONArray("data");
                if (200 == requestCode) {
                    for (Object taskResult : taskResults) {
                        //单张图片的处理结果
                        int taskCode = ((JSONObject)taskResult).getIntValue("code");
                        //图片要检测的场景的处理结果, 如果是多个场景,则会有每个场景的结果
                        JSONArray sceneResults = ((JSONObject)taskResult).getJSONArray("results");
                        if(200 == taskCode){
                            for (Object sceneResult : sceneResults) {
                                String scene = ((JSONObject)sceneResult).getString("scene");
                                String suggestion = ((JSONObject)sceneResult).getString("suggestion");
                                //do something
                                //有识别出卡证信息
                                if("review" .equals(suggestion) && "ocr".equals(scene)){
                                    JSONObject idCardInfo =  ((JSONObject) sceneResult).getJSONObject("idCardInfo");
                                    System.out.println(idCardInfo.toJSONString());
                                }
                            }
                        }else{
                            //单张图片处理失败, 原因视具体的情况详细分析
                            System.out.println("task process fail. task response:" + JSON.toJSONString(taskResult));
                        }
                    }
                } else {
                    /**
                     * 表明请求整体处理失败,原因视具体的情况详细分析
                     */
                    System.out.println("the whole image scan request failed. response:" + JSON.toJSONString(scrResponse));
                }
            }
        }
    }
  • 传图片二进制字节组数据进行检测
    import com.alibaba.fastjson.JSON;
    import com.alibaba.fastjson.JSONArray;
    import com.alibaba.fastjson.JSONObject;
    import com.aliyuncs.DefaultAcsClient;
    import com.aliyuncs.IAcsClient;
    import com.aliyuncs.exceptions.ClientException;
    import com.aliyuncs.exceptions.ServerException;
    import com.aliyuncs.green.extension.uploader.ClientUploader;
    import com.aliyuncs.green.model.v20180509.ImageSyncScanRequest;
    import com.aliyuncs.http.FormatType;
    import com.aliyuncs.http.HttpResponse;
    import com.aliyuncs.http.MethodType;
    import com.aliyuncs.http.ProtocolType;
    import com.aliyuncs.profile.DefaultProfile;
    import com.aliyuncs.profile.IClientProfile;
    import org.apache.commons.io.FileUtils;
    
    import java.io.File;
    import java.util.*;
    
    public class Main {
    
        public static void main(String[] args) throws Exception {
            IClientProfile profile = DefaultProfile
                .getProfile("cn-shanghai", "请填写您的accessKeyId", "请填写您的accessKeySecret");
            DefaultProfile
                .addEndpoint("cn-shanghai", "cn-shanghai", "Green", "green.cn-shanghai.aliyuncs.com");
            IAcsClient client = new DefaultAcsClient(profile);
    
            ImageSyncScanRequest imageSyncScanRequest = new ImageSyncScanRequest();
            // 指定api返回格式
            imageSyncScanRequest.setAcceptFormat(FormatType.JSON);
            // 指定请求方法
            imageSyncScanRequest.setMethod(MethodType.POST);
            imageSyncScanRequest.setEncoding("utf-8");
            //支持http和https
            imageSyncScanRequest.setProtocol(ProtocolType.HTTP);
    
            JSONObject httpBody = new JSONObject();
            /**
             * 设置要检测的场景
             * ocr: ocr或者ocr卡证识别
             */
            httpBody.put("scenes", Arrays.asList("ocr"));
            /**
             * 设置待检测图片, 一张图片一个task,最多支持100张图片同时检测,即需要构建100个task
             * 多张图片同时检测时,处理的时间由最后一个处理完的图片决定。因此通常情况下批量检测的平均rt比单张检测的要长, 一次批量提交的图片数越多,rt被拉长的概率越高
             * 这里以单张图片检测作为示例, 如果是批量图片检测,请自行构建多个task
             * 图片二进制数据检测相对于互联网图片链接来说,多了一个上传步骤,上传后取返回的链接进行检测
             */
            ClientUploader clientUploader = ClientUploader.getImageClientUploader(profile, false);
            byte[] imageBytes = null;
            String url = null;
            try{
                //这里读取本地文件作为二进制数据,当做输入做为示例, 实际使用中请直接替换成您的图片二进制数据
                imageBytes = FileUtils.readFileToByteArray(new File("/Users/01fb4ab6420b5f34623e13b82b51ef87.jpg"));
                //上传到服务端
                url = clientUploader.uploadBytes(imageBytes);
            }catch (Exception e){
                System.out.println(("upload file to server fail.");
            }
    
            JSONObject task = new JSONObject();
            task.put("dataId", UUID.randomUUID().toString());
            task.put("url", url);
            task.put("time", new Date());
            httpBody.put("tasks", Arrays.asList(task));
    
            //ocr卡证识别,设置识别卡证类型
            JSONObject cardExtras = new JSONObject();
            //身份证正面识别
            cardExtras.put("card", "id-card-front");
            //身份证反面
            //cardExtras.put("card", "id-card-back");
            httpBody.put("extras", cardExtras);
            imageSyncScanRequest.setHttpContent(org.apache.commons.codec.binary.StringUtils.getBytesUtf8(httpBody.toJSONString()), "UTF-8", FormatType.JSON);
            /**
             * 请设置超时时间, 服务端全链路处理超时时间为10秒,请做相应设置
             * 如果您设置的ReadTimeout小于服务端处理的时间,程序中会获得一个read timeout 异常
             */
            imageSyncScanRequest.setConnectTimeout(3000);
            imageSyncScanRequest.setReadTimeout(10000);
            HttpResponse httpResponse = null;
            try {
                httpResponse = client.doAction(imageSyncScanRequest);
            } catch (ServerException e) {
                e.printStackTrace();
            } catch (ClientException e) {
                e.printStackTrace();
            } catch (Exception e){
                e.printStackTrace();
            }
    
            //服务端接收到请求,并完成处理返回的结果
            if(httpResponse != null && httpResponse.isSuccess()){
                JSONObject scrResponse = JSON.parseObject(org.apache.commons.codec.binary.StringUtils.newStringUtf8(httpResponse.getHttpContent()));
                System.out.println(JSON.toJSONString(scrResponse));
                int requestCode = scrResponse.getIntValue("code");
                //每一张图片的检测结果
                JSONArray taskResults = scrResponse.getJSONArray("data");
                if (200 == requestCode) {
                    for (Object taskResult : taskResults) {
                        //单张图片的处理结果
                        int taskCode = ((JSONObject)taskResult).getIntValue("code");
                        //图片要检测的场景的处理结果, 如果是多个场景,则会有每个场景的结果
                        JSONArray sceneResults = ((JSONObject)taskResult).getJSONArray("results");
                        if(200 == taskCode){
                            for (Object sceneResult : sceneResults) {
                                String scene = ((JSONObject)sceneResult).getString("scene");
                                String suggestion = ((JSONObject)sceneResult).getString("suggestion");
                                //do something
                                //有识别出卡证信息
                                if("review" .equals(suggestion) && "ocr".equals(scene)){
                                    JSONObject idCardInfo =  ((JSONObject) sceneResult).getJSONObject("idCardInfo");
                                    System.out.println(idCardInfo.toJSONString());
                                }
                            }
                        }else{
                            //单张图片处理失败, 原因视具体的情况详细分析
                            System.out.println("task process fail. task response:" + JSON.toJSONString(taskResult));
                        }
                    }
                } else {
                    /**
                     * 表明请求整体处理失败,原因视具体的情况详细分析
                     */
                    System.out.println("the whole image scan request failed. response:" + JSON.toJSONString(scrResponse));
                }
            }
        }
    }