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README.md
MulanPSL-2.0

📢 请注意!由于腾讯AI原有免费API已关闭,该项目目前已属于不可用状态

Version Download License JDK 1.7 WiKi 作者

文档请移步:http://taip.mydoc.io/

腾讯AI 基本已经转到腾讯云了。此SDK已经不适用。腾讯云官方有封装SDK的。转到腾讯云接口基本都需要付费使用哦~

APPID APPKEY 是腾讯AI创建应用后得到。请移步腾讯AI官网获取哦。https://ai.qq.com/

QQ:783021975

关注码小帅获取最新功能更新

码小帅

TAip Java SDK目录结构

cn.xsshome.taip
       ├── base                                //基类
       ├── http                                //Http通信相关类
       ├── error                                //SDK错误类
       ├── imageclassify
       │       └── TAipImageClassify           //TAipImageClassify类
       ├── sign                                //签名公用类
       ├── ocr
       │       └── TAipOcr                      //TAipOcr类
       ├── speech
       │       └── TAipSpeech                   //TAipSpeech类
       ├── face
       │       └── TAipFace                   //TAipFace类
       ├── ptu
       │       └── TAipPtu                   //TAipPtu类
       ├── nlp
       │       └── TAipNlp                   //TAipNlp类
       ├── vision
       │       └── TAipVision                   //TAipVision类
       └── util                                //工具类

支持 JAVA版本:1.7+

直接使用JAR包步骤如下:

1.在腾讯AIQQ群下载Java SDK压缩工具包或点击download图标进行下载最新jar。

2.将下载的tai-java-sdk-version.zip解压后,复制到工程文件夹中。

3.在Eclipse右键“工程 -> Properties -> Java Build Path -> Add JARs”。

4.添加SDK工具包tai-java-sdk-version.jar。

其中,version为版本号,添加完成后,用户就可以在工程中使用腾讯AIJava SDK。


安装

Maven

在项目的pom.xml的dependencies中加入以下内容:

<dependency>
  <groupId>cn.xsshome</groupId>
  <artifactId>taip</artifactId>
  <version>4.3.5</version>
</dependency>

Gradle

compile 'cn.xsshome:taip:4.3.5'

非Maven项目

点击以下任一链接,下载taip-x.x.x.jar即可:


使用示例代码

网络设置示例代码

public class Sample {
    //设置APPID/APP_KEY
    public static final String APP_ID = "你的 App ID";
    public static final String APP_KEY = "你的 Api Key";

    public static void main(String[] args) {
        // 初始化一个TAip[xxx] xxx代表具体的模块名称
        TAip[xxx] client = new TAip[xxx](APP_ID,APP_KEY);
        // 可选:设置网络连接参数
        client.setConnectionTimeoutInMillis(2000);
        client.setSocketTimeoutInMillis(60000);
         // 可选:设置代理服务器地址, http和socket二选一,或者均不设置
        client.setHttpProxy("proxy_host", proxy_port);  // 设置http代理
        client.setSocketProxy("proxy_host", proxy_port);  // 设置socket代理
        //调用接口
        client.[xxxxx]("图片路径");
    }
}

OCR示例代码

新建TAipOcr TAipOcr是调用腾讯AI中OCR的Java客户端,为调用腾讯AI中OCR功能的开发人员提供了一系列的交互方法。

用户可以参考如下代码新建一个TAipOcr,初始化完成后建议单例使用:

public class Sample {
    //设置APPID/APP_KEY
    public static final String APP_ID = "你的 App ID";
    public static final String APP_KEY = "你的 Api Key";

    public static void main(String[] args) {
        // 初始化一个TAipOcr
       TAipOcr aipOcr = new TAipOcr(APP_ID,APP_KEY);
        // 调用接口
        String result = aipOcr.idcardOcr("./idcard.jpg", 0);//身份证正面(图片)识别
        String result = aipOcr.idcardOcr("./idcard2.jpg", 1);//身份证反面(国徽)识别
        String result = aipOcr.bcOcr("./juli2.jpg");//名片识别
        String result = aipOcr.driverlicenseOcr("./driver.jpg",0);//行驶证OCR识别
        String result = aipOcr.driverlicenseOcr("./driver2.jpg",1);//驾驶证OCR识别
        String result = aipOcr.bizlicenseOcr("./biz.jpg");//营业执照OCR识别
        String result = aipOcr.creditcardOcr("./bank2.jpg");//银行卡OCR识别
        String result = aipOcr.generalOcr("./biz.jpg");//通用OCR识别
        String result = aipOcr.handWritingOcrByImage("./biz.jpg");//手写体识别 选取本地图片文件识别
        String result = aipOcr.handWritingOcrByUrl("https://yyb.gtimg.com/ai/assets/ai-demo/small/hd-1-sm.jpg");//手写体识别 选取网络图片URL识别 
        String result = aipOcr.plateOcrByImage("./biz.jpg");//车牌识别 选取本地图片文件识别
        String result = aipOcr.plateOcrByUrl("https://yyb.gtimg.com/ai/assets/ai-demo/large/plate-1-lg.jpg");//车牌识别 选取网络图片URL识别                               
    }
}

ASR、TTS示例代码

新建TAipSpeech TAipSpeech是调用腾讯AI中语音识别、合成的Java客户端,为调用腾讯AI中语音识别、合成功能的开发人员提供了一系列的交互方法。

用户可以参考如下代码新建一个TAipSpeech,初始化完成后建议单例使用:

public class Sample {
    //设置APPID/APP_KEY
    public static final String APP_ID = "你的 App ID";
    public static final String APP_KEY = "你的 Api Key";

    public static void main(String[] args) {
        // 初始化一个TAipSpeech
        TAipSpeech aipSpeech = new TAipSpeech(APP_ID, APP_KEY);
        // 调用接口
        String filePath ="./VOICE1513237078.pcm";//本地文件路径
        byte[] audio = FileUtil.readFileByBytes(filePath);//获取文件的byte数据
        String result = aipSpeech.asrEcho(filePath, 1);//语音识别-echo版
        String result = aipSpeech.asrLab(1, 16000, 0, 1024, 1, audio);//语音识别-流式版(AI Lab)
        String result = aipSpeech.asrWx(filePath, 1, 16000, 16, 0, 1024, 1, 1);//语音识别-流式版(WeChat AI)
        String text = "小帅封装代码";
        String result = aipSpeech.TtaSynthesis(text);//语音合成(优图)     默认参数
        String result = aipSpeech.TtaSynthesis(text,2,1);//语音合成(优图)     全部参数
        String result = aipSpeech.TtsSynthesis(text, 1, 3);//语音合成(AI Lab) 默认参数
        String result = aipSpeech.TtsSynthesis(text,1,3,0,100,0,58);//语音合成(AI Lab) 全部参数
        String result = aipSpeech.asrLong("G:/16.pcm", 1, "http://yourwebsitename.com/methodname");//长语音识别
        String result = aipSpeech.aaiDetectkeywordBySpeech(filePath, 1, "http://www.xxxxx.com//txnotify", "小",8000);//关键词检索基于本地语音文件
        String result = aipSpeech.aaiDetectkeywordBySpeechURL("http://www.xxxxx.com/audio.pcm", 1, "http://www.xxxxx.com//txnotify", "小",8000);//关键词检索基于语音URL文件
        System.out.println(result);
    }
}

图像识别 示例代码

TAipImageClassify是调用腾讯AI中图像识别的Java客户端,为调用腾讯AI中图像识别功能的开发人员提供了一系列的交互方法。

用户可以参考如下代码新建一个 TAipImageClassify,初始化完成后建议单例使用:

public class Sample {
    //设置APPID/APP_KEY
    public static final String APP_ID = "你的 App ID";
    public static final String APP_KEY = "你的 Api Key";
    public static void main(String[] args) throws Exception {
        // 初始化一个TAipImageClassify
        TAipImageClassify aipImageClassify = new TAipImageClassify(APP_ID, APP_KEY);
        String filePath = "G:/x5.jpg";//本地文件路径
        byte[] image = FileUtil.readFileByBytes(filePath);//获取文件的byte数据
        String result = aipImageClassify.visionScener(image, 1, 5);//场景识别
        String result = aipImageClassify.visionObjectr(image, 1, 5);//物体识别
        String result = aipImageClassify.imageTag(image);//图像标签识别
        String result = aipImageClassify.visionImgidentify(image, 1);//车辆识别
        String result = aipImageClassify.visionImgidentify(image, 2);//花草识别
        String result = aipImageClassify.flowersAndPlant(image);//花草识别
        String result = aipImageClassify.vehicle(image);//车辆识别
        String result = aipImageClassify.visionImgtotext(image,RandomNonceStrUtil.getRandomString());//看图说话
        String result = aipImageClassify.imageFuzzy(image);//模糊图片检测
        String result = aipImageClassify.imageFood(image);//美食图片识别
        System.out.println(result);

    }
}

图片特效

TAipPtu是调用腾讯AI中图片特效的Java客户端,为调用腾讯AI中图片特效功能的开发人员提供了一系列的交互方法。

用户可以参考如下代码新建一个 TAipPtu,初始化完成后建议单例使用:


public class Sample{
     //设置APPID/APP_KEY
    public static final String APP_ID = "你的 App ID";
    public static final String APP_KEY = "你的 Api Key";
    public static void main(String[] args) throws Exception {
        // 初始化一个TAipPtu
        TAipPtu aipPtu = new TAipPtu(APP_ID, APP_KEY);
        String imagePath = "G:/test2.jpg";
        String result = aipPtu.faceCosmetic(imagePath, 23);//人脸美妆     
        String result = aipPtu.faceDecoration(imagePath, 8);//人脸变妆     
        String result = aipPtu.imgFilter(imagePath, 20);//滤镜 天天P图     
        String result = aipPtu.visionImgfilter(imagePath, 32, String.valueOf(new Date().getTime()));//滤镜 AI Lab
        String result = aipPtu.faceMerge(imagePath, 12);//人脸融合
        String result = aipPtu.faceSticker(imagePath, 27);//大头贴
        String result = aipPtu.faceAge(imagePath);//颜龄检测
        System.out.println(result);
    }
}

人脸识别

TAipFace是调用腾讯AI中人脸识别的Java客户端,为调用腾讯AI中人脸识别功能的开发人员提供了一系列的交互方法。

用户可以参考如下代码新建一个 TAipFace,初始化完成后建议单例使用:


public class Sample{
 //设置APPID/APP_KEY
    public static final String APP_ID = "你的 App ID";
    public static final String APP_KEY = "你的 Api Key";
    public static void main(String[] args) throws Exception {
         // 初始化一个TAipPtu
        TAipFace aipFace = new TAipFace(APP_ID, APP_KEY);
        String filePath = "G:/body2.jpg";
        String filePathA = "G:/dc.jpg";
        String filePathB = "G:/dcg.jpg";
        /**********人脸识别**********/
        String result = aipFace.detect(filePath);//人脸检测与分析
        String result = aipFace.detectByUrl("https://yyb.gtimg.com/aiplat/static/ai-demo/small/f-3.jpg");//人脸检测与分析使用image_url参数
        String result = aipFace.detectMulti(filePath);    //多人脸检测
        String result = aipFace.faceCompare(filePathA, filePathB);    //人脸对比     
        String result = aipFace.detectCrossage(filePathA, filePathB);//跨年龄人脸识别
        String result = aipFace.faceShape(filePathA);//五官定位     
        String result = aipFace.faceIdentify(filePath, "group01", 9);//人脸识别
        String result = aipFace.faceVerify(filePath, "20180511");//人脸验证
        /**********个体管理**********/
        String result = aipFace.faceNewperson(filePath,"group20180511","201805110001","测试");//个体创建
        String result = aipFace.faceDelperson("201805110001");//删除个体
        /*增加人脸 图片二进制List*/
        List<byte[]> bytes = new ArrayList<byte[]>();
        byte [] faceA = FileUtil.readFileByBytes(filePathA);
        byte [] faceB = FileUtil.readFileByBytes(filePathB);
        bytes.add(faceA);
        bytes.add(faceB);
        String result = aipFace.faceAddfaceByte(bytes,"201805110001","测试增加人脸");
        /*增加人脸 图片本地路径List*/
        List<String> filePaths = new ArrayList<String>();
        filePaths.add(filePathA);
        filePaths.add(filePathB);
        String result = aipFace.faceAddfaceByFilePath(filePaths,"201805110001","测试增加人脸");//增加人脸
        String result = aipFace.faceDelFace("201805110001", "2573556034542000336");//删除人脸
        String result = aipFace.faceSetInfo("201805110001", "小帅测试","测试接口");//设置信息
        String result = aipFace.faceGetInfo("201805110001");//获取信息
        /**********信息查询**********/
        String result = aipFace.getGroupIds();//获取组列表
        String result = aipFace.getPersonIds("group20180511");//获取个体列表
        String result = aipFace.getFaceIds("201805110001");//获取人脸列表
        String result = aipFace.getFaceInfo("2573564663139686751");//获取人脸信息     
        System.out.println(result);
    }
}

自然语言处理

TAipNlp是调用腾讯AI中自然语言处理的Java客户端,为调用腾讯AI中自然语言处理功能的开发人员提供了一系列的交互方法。

用户可以参考如下代码新建一个 TAipNlp,初始化完成后建议单例使用:

public class Sample{
    public static final String APP_ID = "你的 App ID";
    public static final String APP_KEY = "你的 Api Key";
    public static void main2(String[] args) throws Exception {
        TAipNlp aipNlp = new TAipNlp(APP_ID, APP_KEY);
        String session = new Date().getTime()/1000+"";
        String filePath = "G:/tt.jpg";
        String filePath2 = "G:/16.pcm";
        String result = aipNlp.nlpWordseg("小帅开发者");//分词
        String result = aipNlp.nlpWordpos("小帅是一个热心的开发者");//词性标注
        String result = aipNlp.nlpWordner("最近张学友在深圳开了一场演唱会");//专有名词
        String result = aipNlp.nlpWordsyn("今天的天气怎么样");//同义词
        String result = aipNlp.nlpWordcom("今天深圳的天气怎么样?明天呢");//意图成分
        String result = aipNlp.nlpTextpolar("小帅很帅");//情感分析
        String result = aipNlp.nlpTextchat(session,"北京天气");//基础闲聊     
        String result = aipNlp.nlpTextTrans(0, "小帅开发者");//文本翻译(AI Lab)
        String result = aipNlp.nlpTextTranslate("小帅开发者", "zh", "en");//文本翻译(翻译君)     
        String result = aipNlp.nlpImageTranslate(filePath, session, "doc","zh", "en");//图片翻译
        String result = aipNlp.nlpSpeechTranslate(6, 0, 1, session, filePath2,"zh", "en");//语音翻译     
        String result = aipNlp.nlpTextDetect("こんにちは", 0);//语种识别
        System.out.println(result);
    }
}

智能鉴黄、暴恐图片识别

TAipVision是调用腾讯AI中智能鉴黄、暴恐图片识别、音频鉴黄识别的Java客户端,为调用腾讯AI中智能鉴黄、暴恐图片识别功能的开发人员提供了一系列的交互方法。

用户可以参考如下代码新建一个 TAipVision,初始化完成后建议单例使用:

public class Sample{
    public static final String APP_ID = "你的 App ID";
    public static final String APP_KEY = "你的 Api Key";
    public static void main2(String[] args) throws Exception {
        TAipVision aipVision = new TAipVision(APP_ID, APP_KEY);
        String filePath = "G:/tt.jpg";
        String imageUrl = "https://www.xsshome.cn/xxx.jpg";//图片的网络路径地址
        String result = aipVision.imageTerrorism(imageUrl);//暴恐图片
        String result = aipVision.imageTerrorismByURL(filePath);//暴恐图片ByURL
        String result = aipVision.visionPorn(filePath);//智能鉴黄
        String result = aipVision.visionPornByURL(imageUrl);//智能鉴黄ByURL
        String speech_url = "https://www.xsshome.cn/output.mp3";
		String result = aipVision.aaiEvilAudio(UUID.randomUUID().toString().replace("-", ""), speech_url);//音频鉴黄
        System.out.println(result);
    }
}
木兰宽松许可证, 第2版 木兰宽松许可证, 第2版 2020年1月 http://license.coscl.org.cn/MulanPSL2 您对“软件”的复制、使用、修改及分发受木兰宽松许可证,第2版(“本许可证”)的如下条款的约束: 0. 定义 “软件”是指由“贡献”构成的许可在“本许可证”下的程序和相关文档的集合。 “贡献”是指由任一“贡献者”许可在“本许可证”下的受版权法保护的作品。 “贡献者”是指将受版权法保护的作品许可在“本许可证”下的自然人或“法人实体”。 “法人实体”是指提交贡献的机构及其“关联实体”。 “关联实体”是指,对“本许可证”下的行为方而言,控制、受控制或与其共同受控制的机构,此处的控制是指有受控方或共同受控方至少50%直接或间接的投票权、资金或其他有价证券。 1. 授予版权许可 每个“贡献者”根据“本许可证”授予您永久性的、全球性的、免费的、非独占的、不可撤销的版权许可,您可以复制、使用、修改、分发其“贡献”,不论修改与否。 2. 授予专利许可 每个“贡献者”根据“本许可证”授予您永久性的、全球性的、免费的、非独占的、不可撤销的(根据本条规定撤销除外)专利许可,供您制造、委托制造、使用、许诺销售、销售、进口其“贡献”或以其他方式转移其“贡献”。前述专利许可仅限于“贡献者”现在或将来拥有或控制的其“贡献”本身或其“贡献”与许可“贡献”时的“软件”结合而将必然会侵犯的专利权利要求,不包括对“贡献”的修改或包含“贡献”的其他结合。如果您或您的“关联实体”直接或间接地,就“软件”或其中的“贡献”对任何人发起专利侵权诉讼(包括反诉或交叉诉讼)或其他专利维权行动,指控其侵犯专利权,则“本许可证”授予您对“软件”的专利许可自您提起诉讼或发起维权行动之日终止。 3. 无商标许可 “本许可证”不提供对“贡献者”的商品名称、商标、服务标志或产品名称的商标许可,但您为满足第4条规定的声明义务而必须使用除外。 4. 分发限制 您可以在任何媒介中将“软件”以源程序形式或可执行形式重新分发,不论修改与否,但您必须向接收者提供“本许可证”的副本,并保留“软件”中的版权、商标、专利及免责声明。 5. 免责声明与责任限制 “软件”及其中的“贡献”在提供时不带任何明示或默示的担保。在任何情况下,“贡献者”或版权所有者不对任何人因使用“软件”或其中的“贡献”而引发的任何直接或间接损失承担责任,不论因何种原因导致或者基于何种法律理论,即使其曾被建议有此种损失的可能性。 6. 语言 “本许可证”以中英文双语表述,中英文版本具有同等法律效力。如果中英文版本存在任何冲突不一致,以中文版为准。 条款结束 如何将木兰宽松许可证,第2版,应用到您的软件 如果您希望将木兰宽松许可证,第2版,应用到您的新软件,为了方便接收者查阅,建议您完成如下三步: 1, 请您补充如下声明中的空白,包括软件名、软件的首次发表年份以及您作为版权人的名字; 2, 请您在软件包的一级目录下创建以“LICENSE”为名的文件,将整个许可证文本放入该文件中; 3, 请将如下声明文本放入每个源文件的头部注释中。 Copyright (c) [Year] [name of copyright holder] [Software Name] is licensed under Mulan PSL v2. You can use this software according to the terms and conditions of the Mulan PSL v2. You may obtain a copy of Mulan PSL v2 at: http://license.coscl.org.cn/MulanPSL2 THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY OR FIT FOR A PARTICULAR PURPOSE. See the Mulan PSL v2 for more details. Mulan Permissive Software License,Version 2 Mulan Permissive Software License,Version 2 (Mulan PSL v2) January 2020 http://license.coscl.org.cn/MulanPSL2 Your reproduction, use, modification and distribution of the Software shall be subject to Mulan PSL v2 (this License) with the following terms and conditions: 0. Definition Software means the program and related documents which are licensed under this License and comprise all Contribution(s). Contribution means the copyrightable work licensed by a particular Contributor under this License. Contributor means the Individual or Legal Entity who licenses its copyrightable work under this License. Legal Entity means the entity making a Contribution and all its Affiliates. Affiliates means entities that control, are controlled by, or are under common control with the acting entity under this License, ‘control’ means direct or indirect ownership of at least fifty percent (50%) of the voting power, capital or other securities of controlled or commonly controlled entity. 1. Grant of Copyright License Subject to the terms and conditions of this License, each Contributor hereby grants to you a perpetual, worldwide, royalty-free, non-exclusive, irrevocable copyright license to reproduce, use, modify, or distribute its Contribution, with modification or not. 2. Grant of Patent License Subject to the terms and conditions of this License, each Contributor hereby grants to you a perpetual, worldwide, royalty-free, non-exclusive, irrevocable (except for revocation under this Section) patent license to make, have made, use, offer for sale, sell, import or otherwise transfer its Contribution, where such patent license is only limited to the patent claims owned or controlled by such Contributor now or in future which will be necessarily infringed by its Contribution alone, or by combination of the Contribution with the Software to which the Contribution was contributed. The patent license shall not apply to any modification of the Contribution, and any other combination which includes the Contribution. If you or your Affiliates directly or indirectly institute patent litigation (including a cross claim or counterclaim in a litigation) or other patent enforcement activities against any individual or entity by alleging that the Software or any Contribution in it infringes patents, then any patent license granted to you under this License for the Software shall terminate as of the date such litigation or activity is filed or taken. 3. No Trademark License No trademark license is granted to use the trade names, trademarks, service marks, or product names of Contributor, except as required to fulfill notice requirements in Section 4. 4. Distribution Restriction You may distribute the Software in any medium with or without modification, whether in source or executable forms, provided that you provide recipients with a copy of this License and retain copyright, patent, trademark and disclaimer statements in the Software. 5. Disclaimer of Warranty and Limitation of Liability THE SOFTWARE AND CONTRIBUTION IN IT ARE PROVIDED WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED. IN NO EVENT SHALL ANY CONTRIBUTOR OR COPYRIGHT HOLDER BE LIABLE TO YOU FOR ANY DAMAGES, INCLUDING, BUT NOT LIMITED TO ANY DIRECT, OR INDIRECT, SPECIAL OR CONSEQUENTIAL DAMAGES ARISING FROM YOUR USE OR INABILITY TO USE THE SOFTWARE OR THE CONTRIBUTION IN IT, NO MATTER HOW IT’S CAUSED OR BASED ON WHICH LEGAL THEORY, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. 6. Language THIS LICENSE IS WRITTEN IN BOTH CHINESE AND ENGLISH, AND THE CHINESE VERSION AND ENGLISH VERSION SHALL HAVE THE SAME LEGAL EFFECT. IN THE CASE OF DIVERGENCE BETWEEN THE CHINESE AND ENGLISH VERSIONS, THE CHINESE VERSION SHALL PREVAIL. END OF THE TERMS AND CONDITIONS How to Apply the Mulan Permissive Software License,Version 2 (Mulan PSL v2) to Your Software To apply the Mulan PSL v2 to your work, for easy identification by recipients, you are suggested to complete following three steps: i Fill in the blanks in following statement, including insert your software name, the year of the first publication of your software, and your name identified as the copyright owner; ii Create a file named “LICENSE” which contains the whole context of this License in the first directory of your software package; iii Attach the statement to the appropriate annotated syntax at the beginning of each source file. Copyright (c) [Year] [name of copyright holder] [Software Name] is licensed under Mulan PSL v2. You can use this software according to the terms and conditions of the Mulan PSL v2. You may obtain a copy of Mulan PSL v2 at: http://license.coscl.org.cn/MulanPSL2 THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY OR FIT FOR A PARTICULAR PURPOSE. See the Mulan PSL v2 for more details.

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TAIP是调用腾讯AI接口封装的Java客户端,为调用腾讯AI功能的开发人员提供了一系列的交互方法。 expand collapse
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