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第三方工具---阿里云内容安全

作者:互联网

第三方阿里云内容安全工具

1 依赖引入

在leadnews-common中引入阿里云sdk依赖

<dependency>
    <groupId>com.aliyun</groupId>
    <artifactId>aliyun-java-sdk-core</artifactId>
</dependency>
<dependency>
    <groupId>com.aliyun</groupId>
    <artifactId>aliyun-java-sdk-green</artifactId>
</dependency>

2 新建阿里云的配置文件 properties

在leadnews-common中的resources中新建aliyun.properties

aliyun.accessKeyId=LTAI4FmKL2EKYCGgN2az5M57  //-修改成自己阿里云服务的ak
aliyun.secret=XjgvRoAGzM3rWQxKWDJx98VWOmO0Hz  //修改成自己阿里云服务的sk
aliyun.scenes=porn,terrorism,ad,qrcode,live,logo  //内容检测场景

scenes,当前的这个场景设置,只有在图片审核的时候会用到,可以根据实际情况自由组合

3 引入图片上传工具类

从之前测试阿里云服务的工程拷贝到leadnews-common中,结构如下:

4改造后的文本内容审核

4.1审核文本内容的工具类方法:

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.TextScanRequest;
import com.aliyuncs.http.FormatType;
import com.aliyuncs.http.HttpResponse;
import com.aliyuncs.profile.DefaultProfile;
import com.aliyuncs.profile.IClientProfile;
import lombok.Getter;
import lombok.Setter;
import org.jcodings.util.Hash;
import org.springframework.boot.context.properties.ConfigurationProperties;
import org.springframework.context.annotation.PropertySource;
import org.springframework.stereotype.Component;

import java.util.*;

@Getter
@Setter
@Component
@PropertySource("classpath:aliyun.properties")
@ConfigurationProperties(prefix = "aliyun")
public class GreeTextScan {

    private String accessKeyId;
    private String secret;

    public Map greeTextScan(String content) throws Exception {
        IClientProfile profile = DefaultProfile
                .getProfile("cn-shanghai", accessKeyId, secret);
        DefaultProfile
                .addEndpoint("cn-shanghai", "cn-shanghai", "Green", "green.cn-shanghai.aliyuncs.com");
        IAcsClient client = new DefaultAcsClient(profile);
        TextScanRequest textScanRequest = new TextScanRequest();
        textScanRequest.setAcceptFormat(FormatType.JSON); // 指定api返回格式
        textScanRequest.setHttpContentType(FormatType.JSON);
        textScanRequest.setMethod(com.aliyuncs.http.MethodType.POST); // 指定请求方法
        textScanRequest.setEncoding("UTF-8");
        textScanRequest.setRegionId("cn-shanghai");
        List<Map<String, Object>> tasks = new ArrayList<Map<String, Object>>();
        Map<String, Object> task1 = new LinkedHashMap<String, Object>();
        task1.put("dataId", UUID.randomUUID().toString());
        /**
         * 待检测的文本,长度不超过10000个字符
         */
        task1.put("content", content);
        tasks.add(task1);
        JSONObject data = new JSONObject();

        /**
         * 检测场景,文本垃圾检测传递:antispam
         **/
        data.put("scenes", Arrays.asList("antispam"));
        data.put("tasks", tasks);
        System.out.println(JSON.toJSONString(data, true));
        textScanRequest.setHttpContent(data.toJSONString().getBytes("UTF-8"), "UTF-8", FormatType.JSON);
        // 请务必设置超时时间
        textScanRequest.setConnectTimeout(3000);
        textScanRequest.setReadTimeout(6000);

        Map<String, String> resultMap = new HashMap<>();
        try {
            HttpResponse httpResponse = client.doAction(textScanRequest);
            if (httpResponse.isSuccess()) {
                JSONObject scrResponse = JSON.parseObject(new String(httpResponse.getHttpContent(), "UTF-8"));
                System.out.println(JSON.toJSONString(scrResponse, true));
                if (200 == scrResponse.getInteger("code")) {
                    JSONArray taskResults = scrResponse.getJSONArray("data");
                    for (Object taskResult : taskResults) {
                        if (200 == ((JSONObject) taskResult).getInteger("code")) {
                            JSONArray sceneResults = ((JSONObject) taskResult).getJSONArray("results");
                            for (Object sceneResult : sceneResults) {
                                String scene = ((JSONObject) sceneResult).getString("scene");
                                String label = ((JSONObject) sceneResult).getString("label");
                                String suggestion = ((JSONObject) sceneResult).getString("suggestion");
                                System.out.println("suggestion = [" + label + "]");
                                if (!suggestion.equals("pass")) {
                                    resultMap.put("suggestion", suggestion);
                                    resultMap.put("label", label);
                                    return resultMap;
                                }

                            }
                        } else {
                            return null;
                        }
                    }
                    resultMap.put("suggestion", "pass");
                    return resultMap;
                } else {
                    return null;
                }
            } else {
                return null;
            }
        } catch (ServerException e) {
            e.printStackTrace();
        } catch (ClientException e) {
            e.printStackTrace();
        } catch (Exception e) {
            e.printStackTrace();
        }
        return null;
    }

}

3.5 改造后的图片审核

审核文本内容的工具类方法:
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.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 com.heima.common.aliyun.util.ClientUploader;
import lombok.Getter;
import lombok.Setter;
import org.springframework.boot.context.properties.ConfigurationProperties;
import org.springframework.context.annotation.PropertySource;
import org.springframework.stereotype.Component;

import java.util.*;

@Getter
@Setter
@Component
@PropertySource("classpath:aliyun.properties")
@ConfigurationProperties(prefix = "aliyun")
public class GreenImageScan {

    private String accessKeyId;
    private String secret;
    private String scenes;

    public Map imageScan(List<byte[]> imageList) throws Exception {
        IClientProfile profile = DefaultProfile
            .getProfile("cn-shanghai", accessKeyId, secret);
        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, 计费是按照该处传递的场景进行
         * 一次请求中可以同时检测多张图片,每张图片可以同时检测多个风险场景,计费按照场景计算
         * 例如:检测2张图片,场景传递porn、terrorism,计费会按照2张图片鉴黄,2张图片暴恐检测计算
         * porn: porn表示色情场景检测
         */
        
        httpBody.put("scenes", Arrays.asList(scenes.split(",")));

        /**
         * 如果您要检测的文件存于本地服务器上,可以通过下述代码片生成url
         * 再将返回的url作为图片地址传递到服务端进行检测
         */
        /**
         * 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
         * 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
         */
        ClientUploader clientUploader = ClientUploader.getImageClientUploader(profile, false);
        String url = null;
        List<JSONObject> urlList = new ArrayList<JSONObject>();
        for (byte[] bytes : imageList) {
            url = clientUploader.uploadBytes(bytes);
            JSONObject task = new JSONObject();
            task.put("dataId", UUID.randomUUID().toString());
            //设置图片链接为上传后的url
            task.put("url", url);
            task.put("time", new Date());
            urlList.add(task);
        }
        httpBody.put("tasks", urlList);
        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 (Exception e) {
            e.printStackTrace();
        }

        Map<String, String> resultMap = new HashMap<>();

        //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, true));
            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 label = ((JSONObject) sceneResult).getString("label");
                            String suggestion = ((JSONObject) sceneResult).getString("suggestion");
                            //根据scene和suggetion做相关处理
                            //do something
                            System.out.println("scene = [" + scene + "]");
                            System.out.println("suggestion = [" + suggestion + "]");
                            System.out.println("suggestion = [" + label + "]");
                            if (!suggestion.equals("pass")) {
                                resultMap.put("suggestion", suggestion);
                                resultMap.put("label", label);
                                return resultMap;
                            }
                        }

                    } 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));
                        return null;
                    }
                }
                resultMap.put("suggestion","pass");
                return resultMap;
            } 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));
                return null;
            }
        }
        return null;
    }
}

3.6 测试

在测试过程中引入阿里云项目的依赖:

在启动类或者配置类包扫描aliyun和fastdfs

代码测试:

//测试方法
@SpringBootTest(classes = AdminApplication.class)
@RunWith(SpringRunner.class)
public class AliyunTest {

    @Autowired
    private GreeTextScan greeTextScan;

    @Autowired
    private GreenImageScan greenImageScan;

    @Autowired
    private FastDFSClient fastDFSClient;

    @Test //测试文本安全
    public void testText() throws Exception{
        Map map = greeTextScan.greeTextScan("我是一个文本,冰毒买卖是违法的");
        System.out.println(map);
    }

    @Test  //测试图片安全
    public void testImage() throws Exception {
        byte[] image1 = fastDFSClient.download("group1", "M00/00/00/wKjIgl892suAAHHxAACr_szTy3c449.jpg");
        List<byte[]> images = new ArrayList<>();
        images.add(image1);
        Map map = greenImageScan.imageScan(images);
        System.out.println(map);
    }
}
注意:

错误1:

​ 如果报以下错误,是因为spring boot会默认加载org.springframework.boot.autoconfigure.jdbc.DataSourceAutoConfiguration类使用了@Configuration注解向spring注入了dataSource bean,因为工程中没有关于dataSource相关的配置信息,当spring创建dataSource bean因缺少相关的信息就会报错

[外链图片转存失败,源站可能有防盗链机制,建议将图片保存下来直接上传(img-QX0YryRp-1611052928062)(D:/种子文件/黑马头条/黑马头条md备课讲义/day06/assets/image-20201201103311501.png)]

解决办法:

在入口类@SpringBootApplication注解之上排除datasource即可

@SpringBootApplication(exclude={DataSourceAutoConfiguration.class})

错误2:

​ 是因为注入bean中的名称重复了。

Caused by: org.springframework.context.annotation.ConflictingBeanDefinitionException: Annotation-specified bean name 'fdfsConfiguration' for bean class [com.heima.common.fastdfs.config.FdfsConfiguration] conflicts with existing, non-compatible bean definition of same name and class [com.heima.common.fastdfs.FdfsConfiguration]

解决方案:

​ 第一种,重启一下。

​ 第二种方案:在application.yml中加入一个bean名称允许重复并覆盖的配置

spring:  
  main:
    allow-bean-definition-overriding: true

错误3:

​ 是因为在IOC容器中找不到bean的名称FastDFSClientUtil

Caused by: org.springframework.beans.factory.NoSuchBeanDefinitionException: No qualifying bean of type 'com.heima.common.fastdfs.config.FastDFSClientUtil' available: expected at least 1 bean which qualifies as autowire candidate. Dependency annotations: {@org.springframework.beans.factory.annotation.Autowired(required=true)}

原因是没有注入到IOC容器中,要把当前配置包要扫描在当前工程中

astDFSClientUtil

Caused by: org.springframework.beans.factory.NoSuchBeanDefinitionException: No qualifying bean of type 'com.heima.common.fastdfs.config.FastDFSClientUtil' available: expected at least 1 bean which qualifies as autowire candidate. Dependency annotations: {@org.springframework.beans.factory.annotation.Autowired(required=true)}

原因是没有注入到IOC容器中,要把当前配置包要扫描在当前工程中

标签:aliyuncs,JSONObject,---,阿里,suggestion,new,import,com,第三方
来源: https://blog.csdn.net/m0_52000057/article/details/112849569