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\\"prob\\": 0.99,\\n \\"location\\": [\\n {\\n \\"x\\": 232,\\n \\"y\\": 94\\n },\\n {\\n \\"x\\": 259,\\n \\"y\\": 94\\n },\\n {\\n \\"x\\": 259,\\n \\"y\\": 112\\n },\\n {\\n \\"x\\": 232,\\n \\"y\\": 112\\n }\\n ],\\n \\"word\\": \\"汉\\",\\n \\"charInfo\\": [\\n {\\n \\"prob\\": 0.99,\\n \\"location\\": [\\n {\\n \\"x\\": 232,\\n \\"y\\": 94\\n },\\n {\\n \\"x\\": 259,\\n \\"y\\": 94\\n },\\n {\\n \\"x\\": 259,\\n \\"y\\": 112\\n },\\n {\\n \\"x\\": 232,\\n \\"y\\": 112\\n }\\n ],\\n \\"word\\": \\"汉\\"\\n }\\n ]\\n }\\n ],\\n \\"location\\": [\\n {\\n \\"x\\": 232,\\n \\"y\\": 94\\n },\\n {\\n \\"x\\": 259,\\n \\"y\\": 94\\n },\\n {\\n \\"x\\": 259,\\n \\"y\\": 112\\n },\\n {\\n \\"x\\": 232,\\n \\"y\\": 112\\n }\\n ],\\n \\"fieldWord\\": \\"汉\\"\\n }\\n ],\\n \\"specificType\\": \\"infoCustomeKvTemp\\",\\n \\"width\\": 586,\\n \\"angle\\": 0,\\n \\"classType\\": \\"template\\",\\n \\"height\\": 374,\\n \\"predictFile\\": \\"https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/demo/demo.png\\"\\n },\\n \\"Message\\": \\"successful\\",\\n \\"Code\\": \\"200\\"\\n}","type":"json"}]', 'title' => '模板服务预测API', 'requestParamsDescription' => 'content字段和body字段传参二选一，图片URL则content为图片访问地址。内容为base64编码则传参body，且BinaryToText传true。'."\n" ."\n" .'pdf 限制20Mb 10页'."\n" .'除长文档类型的模型预测以外，其他预测服务只会取第一页进行预测。', 'responseParamsDescription' => '```'."\n" .'模板服务预测接口，返回Data字段解释说明：'."\n" .'score 预测服务置信度 0-1 '."\n" .'data. 算法返回的预测结果，数组格式'."\n" .'prob 算法结果置信度 0-1 '."\n" .'fieldName 抽取key'."\n" .'fieldWord 抽取value'."\n" .'location 抽取结果坐标位置 { "x": 119,"y": 48 }表示页面坐标点'."\n" .'wordInfo 抽取内容详细信息，包括了每个字符的位置信息'."\n" .'specificType 算法类型（infoCustomeKvTemp:自定义KV 模板，infoCustomeTableTemp:自定义表格模板，ocr_infoExtractBill:信息抽取OCR识别，infoExtractBill:单据票证抽取，infoExtractDoc:长文档信息抽取 ）'."\n" .'classType 模型预测服务、模板预测服务'."\n" .'predictFile 预测文件地址（失效时间60分钟）'."\n" .'```', ], 'PredictModel' => [ 'summary' => '模型预测分为三种类型：长文档信息抽取、单票据信息抽取、表格信息抽取。', 'methods' => [ 'post', ], 'schemes' => [ 'http', 'https', ], 'security' => [ [ 'AK' => [], ], ], 'operationType' => 'read', 'deprecated' => false, 'systemTags' => [ 'operationType' => 'get', 'riskType' => 'none', 'chargeType' => 'free', ], 'parameters' => [ [ 'name' => 'Content', 'in' => 'query', 'schema' => [ 'description' => '图片或pdf文件访问URL地址', 'type' => 'string', 'required' => false, 'example' => 'https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/demo/extractBill.png', ], ], [ 'name' => 'ModelVersion', 'in' => 'query', 'schema' => [ 'description' => '模型对应的版本号，如果不传入版本号表示默认用模型最新生效的版本。', 'type' => 'string', 'required' => false, 'example' => '1', ], ], [ 'name' => 'ModelId', 'in' => 'query', 'schema' => [ 'description' => '模型ID。模型列表页模型ID', 'type' => 'integer', 'format' => 'int64', 'required' => true, 'maximum' => '9999999999999', 'minimum' => '1', 'example' => '123', ], ], [ 'name' => 'BinaryToText', 'in' => 'query', 'schema' => [ 'description' => 'content字段是图片URL时：false'."\n" .'body为base64的内容时：true', 'type' => 'boolean', 'required' => false, 'example' => 'false：表示content传入的是url'."\n" .'true：表示body是直接传入图片进行base64的内容', 'default' => 'false', ], ], [ 'name' => 'Body', 'in' => 'formData', 'schema' => [ 'description' => '图片base64编码内容', 'type' => 'string', 'required' => false, 'example' => 'data:image/png;base64,xxxxx'."\n", ], ], ], 'responses' => [ 200 => [ 'schema' => [ 'title' => 'Schema of Response', 'description' => 'Schema of Response', 'type' => 'object', 'properties' => [ 'RequestId' => [ 'title' => 'Id of the request', 'description' => 'Id of the request', 'type' => 'string', 'example' => '3EAC98E6-8DD6-511F-8764-DEE8B6EB6BB4', ], 'Code' => [ 'description' => '请求结果状态，200为成功', 'type' => 'integer', 'format' => 'int32', 'example' => '200', ], 'Message' => [ 'description' => '错误信息。', 'type' => 'string', 'example' => 'success', ], 'Data' => [ 'description' => '接口返回信息', 'type' => 'object', 'example' => '{'."\n" .' 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"value_loc": "1256,234,1256,312,678,312,678,233",'."\n" .' "key_prob": 1,'."\n" .' "key_loc": "",'."\n" .' "value_prob": 1,'."\n" .' "value": "440305198305101408",'."\n" .' "key": "证号"'."\n" .' },'."\n" .' {'."\n" .' "value_loc": "965,321,965,394,851,394,851,321",'."\n" .' "key_prob": 1,'."\n" .' "key_loc": "",'."\n" .' "value_prob": 1,'."\n" .' "value": "女",'."\n" .' "key": "性别"'."\n" .' }'."\n" .' ]'."\n" .' },'."\n" .' "Code": 200'."\n" .'}', ], ], ], ], ], 'errorCodes' => [ 200 => [ [ 'errorCode' => '21002', 'errorMessage' => '模板预测超时 ', ], [ 'errorCode' => '21003', 'errorMessage' => '模板预测失败 ', ], [ 'errorCode' => '10001', 'errorMessage' => '参数出错', ], [ 'errorCode' => '10005', 'errorMessage' => '服务不存在', ], [ 'errorCode' => '16001', 'errorMessage' => '未找到可预测的模型', ], [ 'errorCode' => '13018', 'errorMessage' => '未找到模型信息', ], [ 'errorCode' => '16004', 'errorMessage' => '指定的模型不存在', ], [ 'errorCode' => '23002', 'errorMessage' => '获取资源HTTP异常', ], [ 'errorCode' => '11002', 'errorMessage' => '账号没有开通服务', ], [ 'errorCode' => '19999', 'errorMessage' => '未知异常', ], ], ], 'staticInfo' => [ 'returnType' => 'synchronous', ], 'responseDemo' => '[{"errorExample":"","example":"{\\n \\"RequestId\\": \\"3EAC98E6-8DD6-511F-8764-DEE8B6EB6BB4\\",\\n \\"Code\\": 200,\\n \\"Message\\": \\"success\\",\\n \\"Data\\": {\\n \\"RequestId\\": \\"0C066DD3-F55D-18F7-8577-DE533E04054D\\",\\n \\"Message\\": \\"\\",\\n \\"Data\\": {\\n 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1,\\n \\"value\\": \\"440305198305101408\\",\\n \\"key\\": \\"证号\\"\\n },\\n {\\n \\"value_loc\\": \\"965,321,965,394,851,394,851,321\\",\\n \\"key_prob\\": 1,\\n \\"key_loc\\": \\"\\",\\n \\"value_prob\\": 1,\\n \\"value\\": \\"女\\",\\n \\"key\\": \\"性别\\"\\n }\\n ]\\n },\\n \\"Code\\": 200\\n }\\n}","type":"json"}]', 'title' => '模型服务预测API', 'requestParamsDescription' => 'BinaryToText为非必填项。'."\n" ."\n" .'content字段和body字段传参二选一，图片URL则content为图片访问地址。内容为base64编码则传参body，且BinaryToText传true。'."\n" ."\n" .'pdf 限制20Mb 10页'."\n" .'除了长文档类型的模型预测以外，其他预测服务只会取第一页进行预测。', 'responseParamsDescription' => '长文档信息抽取模型data返回字段解释说明：'."\n" .'```json'."\n" .'originalFileUrl 原始文件url'."\n" .'predictFile 解析后用于预测的图片url集合'."\n" .'data 具体预测结果'."\n" .'angle 图片的角度，当NeedRotate为true时才会返回，0表示正向，90表示图片朝右，180朝下，270朝左'."\n" .'content 识别出图片的文字块汇总'."\n" .'height 算法矫正图片后的高度'."\n" .'width 算法矫正图片后的宽度'."\n" .'orgHeight 原图的高度'."\n" .'orgWidth 原图的宽度'."\n" .'prism_wnum 识别的文字块的数量，prism_wordsInfo数组的大小'."\n" .'```'."\n" .'prism-wordsInfo文字块数组内的字段说明'."\n" .'```json'."\n" .'angle 文字块的角度，这个角度只影响width和height，当角度为-90、90、-270、270，width和height的值需要自行互换'."\n" .'height 文字块的高度'."\n" .'width 文字块的宽度'."\n" .'pos 文字块的外矩形四个点的坐标按顺时针排列，左上、右上、右下、左下，当NeedRotate为true时，如果最外层的angle不为0，需要按照angle矫正图片后，坐标才准确'."\n" .'word 文字块的文字'."\n" .'tableId 当OutputTable为true并且该文字块在表格内则存在该字段，tableId表示表格的id'."\n" .'tableCellId 当OutputTable为true并且该文字块在表格内则存在该字段，表示表格中单元格的id'."\n" .'```'."\n" .'charInfo单字信息'."\n" .'```json'."\n" .'word 单字文字'."\n" .'x 单字左上角横坐标'."\n" .'y 单字左上角纵坐标'."\n" .'w 单字宽度'."\n" .'h 单字高度'."\n" .'```'."\n" .'prism-tablesInfo表格数组内的字段说明'."\n" .'```json'."\n" .'tableId 表格id，和prism_wordsInfo信息中的tableId对应'."\n" .'xCellSize 表格中横坐标单元格的数量'."\n" .'yCellSize 表格中纵坐标单元格的数量'."\n" .'```'."\n" .'cellInfos单元格信息，包含单元格在整个表格中的空间拓扑关系'."\n" .'```json'."\n" .'tableCellId 表格中单元格id，和prism_wordsInfo信息中的tableCellId对应'."\n" .'word 单元格中的文字'."\n" .'xsc xStartCell缩写，表示横轴方向该单元格起始在第几个单元格，第一个单元格值为0'."\n" .'xec xEndCell缩写，表示横轴方向该单元格结束在第几个单元格，第一个单元格值为0，如果xsc和xec都为0说明该文字在横轴方向占据了一个单元格并且在第一个单元格内'."\n" .'ysc yStartCell缩写，表示纵轴方向该单元格起始在第几个单元格，第一个单元格值为0'."\n" .'yec yEndCell缩写，表示纵轴方向该单元格结束在第几个单元格，第一个单元格值为0'."\n" .'pos 单元格位置，按照单元格四个角的坐标顺时针排列，分别为左上XY坐标、右上XY坐标、右下XY坐标、左下XY坐标'."\n" .'```', ], 'PredictClassifierModel' => [ 'summary' => '文档自学习分类器预测接口。', 'methods' => [ 'post', ], 'schemes' => [ 'http', 'https', ], 'security' => [ [ 'AK' => [], ], ], 'operationType' => 'read', 'deprecated' => false, 'systemTags' => [ 'operationType' => 'get', 'riskType' => 'none', 'chargeType' => 'free', ], 'parameters' => [ [ 'name' => 'ClassifierId', 'in' => 'query', 'schema' => [ 'description' => '分类器ID', 'type' => 'integer', 'format' => 'int64', 'required' => false, 'maximum' => '99999999999999', 'minimum' => '1', 'example' => '1', ], ], [ 'name' => 'AutoPrediction', 'in' => 'query', 'schema' => [ 'description' => '是否开启自动预测，false：不开启， true：开启，默认开启', 'type' => 'boolean', 'required' => false, 'example' => 'true', 'default' => 'true', ], ], [ 'name' => 'Content', 'in' => 'query', 'schema' => [ 'description' => '图片或pdf文件可访问地址', 'type' => 'string', 'required' => false, 'example' => 'https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/demo/table.png', ], ], [ 'name' => 'Body', 'in' => 'formData', 'schema' => [ 'description' => '图片base64编码内容', 'type' => 'string', 'required' => false, 'example' => 'data:image/png;base64,xxxxx'."\n", ], ], [ 'name' => 'BinaryToText', 'in' => 'query', 'schema' => [ 'description' => 'content字段是图片URL时：false
body为base64的内容时：true', 'type' => 'boolean', 'required' => false, 'example' => 'false', 'default' => 'false', ], ], ], 'responses' => [ 200 => [ 'schema' => [ 'title' => 'Schema of Response', 'description' => 'Schema of Response', 'type' => 'object', 'properties' => [ 'RequestId' => [ 'title' => 'Id of the request', 'description' => 'Id of the request', 'type' => 'string', 'example' => '232B91A8-9938-5C10-B522-127D1E342A57', ], 'Code' => [ 'description' => '成功', 'type' => 'integer', 'format' => 'int32', 'example' => '200', ], 'Data' => [ 'description' => '返回数据。', 'type' => 'object', 'example' => '{'."\n" .' "score": 1,'."\n" .' "classID": "269_2b6819527769749d962bf51d034b1820",'."\n" .' "tables": ['."\n" .' {'."\n" .' "columns": ['."\n" .' {'."\n" .' "header_value": "姓名",'."\n" .' "bodies": ['."\n" .' {'."\n" .' "prob": 0,'."\n" .' "fieldWordRaw": "学生1",'."\n" .' "wordInfo": [],'."\n" .' "location": ['."\n" .' {'."\n" .' "x": 76,'."\n" .' "y": 99'."\n" .' },'."\n" .' {'."\n" .' 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"value": "学生3"'."\n" .' },'."\n" .' {'."\n" .' "prob": 0,'."\n" .' "fieldWordRaw": "学生4",'."\n" .' "wordInfo": [],'."\n" .' "location": ['."\n" .' {'."\n" .' "x": 76,'."\n" .' "y": 169'."\n" .' },'."\n" .' {'."\n" .' "x": 187,'."\n" .' "y": 169'."\n" .' },'."\n" .' {'."\n" .' "x": 187,'."\n" .' "y": 191'."\n" .' },'."\n" .' {'."\n" .' "x": 76,'."\n" .' "y": 191'."\n" .' }'."\n" .' ],'."\n" .' "value": "学生4"'."\n" .' },'."\n" .' {'."\n" .' "prob": 0,'."\n" .' "fieldWordRaw": "学生5",'."\n" .' "wordInfo": [],'."\n" .' "location": ['."\n" .' {'."\n" .' "x": 76,'."\n" .' "y": 191'."\n" .' },'."\n" .' {'."\n" .' "x": 187,'."\n" .' "y": 191'."\n" .' },'."\n" .' {'."\n" .' "x": 187,'."\n" .' "y": 215'."\n" .' },'."\n" .' {'."\n" .' "x": 76,'."\n" .' "y": 215'."\n" .' }'."\n" .' ],'."\n" .' "value": "学生5"'."\n" .' },'."\n" .' {'."\n" .' "prob": 0,'."\n" .' "fieldWordRaw": "学生6",'."\n" .' "wordInfo": [],'."\n" .' "location": ['."\n" .' {'."\n" .' "x": 76,'."\n" .' 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\\"pos\\": [\\n {\\n \\"x\\": 103,\\n \\"y\\": 34\\n },\\n {\\n \\"x\\": 124,\\n \\"y\\": 34\\n },\\n {\\n \\"x\\": 124,\\n \\"y\\": 48\\n },\\n {\\n \\"x\\": 103,\\n \\"y\\": 48\\n }\\n ],\\n \\"word\\": \\"班\\"\\n }\\n ]\\n }\\n ],\\n \\"name\\": \\"班级\\",\\n \\"location\\": [\\n {\\n \\"x\\": 1,\\n \\"y\\": 30\\n },\\n {\\n \\"x\\": 1102,\\n \\"y\\": 30\\n },\\n {\\n \\"x\\": 1102,\\n \\"y\\": 54\\n },\\n {\\n \\"x\\": 1,\\n \\"y\\": 54\\n }\\n ],\\n \\"fieldWord\\": \\"班级：初二3班\\"\\n }\\n ],\\n \\"specificType\\": \\"infoCustomeTableTemp\\",\\n \\"className\\": \\"自定义表格模板测试cz02064-学生名\\",\\n \\"originalFileUrl\\": \\"https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/3/xxx/stage/upload/20230208/oss-uwGPIS8AsKcGRHfMRjvIrQVqN0uAxTgk.png?Expires=1675843535&OSSAccessKeyId=xxx&Signature=uPhg6JpDn47TgLt%2FI%2F7j4f%2FsFeA%3D\\",\\n \\"templateID\\": \\"269_2b6819527769749d962bf51d034b1820\\",\\n \\"message\\": \\"\\",\\n \\"classType\\": \\"template\\",\\n \\"predictFile\\": \\"https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/3/xxx/stage/upload/20230208/oss-uwGPIS8AsKcGRHfMRjvIrQVqN0uAxTgk.png?Expires=1675843535&OSSAccessKeyId=xxx&Signature=uPhg6JpDn47TgLt%2FI%2F7j4f%2FsFeA%3D\\"\\n },\\n \\"Message\\": \\"success\\"\\n}","type":"json"}]', 'title' => '分类器服务预测API', 'requestParamsDescription' => 'content字段和body字段传参二选一，图片URL则content为图片访问地址。内容为base64编码则传参body，且BinaryToText传true。'."\n" ."\n" .'pdf限制20Mb，10页。'."\n" .'除了长文档类型的模型预测以外，其他预测服务只会取第一页进行预测。', 'responseParamsDescription' => '分类器服务预测接口，返回Data字段解释说明：'."\n" .'```json'."\n" .'score 预测服务置信度 0-1'."\n" .'data 算法返回的预测结果，数组格式 '."\n" .'tables 表格区域预测结果'."\n" .'prob 算法结果置信度 0-1 '."\n" .'fieldName 抽取key '."\n" .'fieldWord 抽取value '."\n" .'location 抽取结果坐标位置 { "x": 119,"y": 48 }表示页面坐标点 '."\n" .'wordInfo 抽取内容详细信息，包括了每个字符的位置信息 '."\n" .'specificType 算法类型（infoCustomeKvTemp:自定义KV 模板，infoCustomeTableTemp:自定义表格模板，ocr_infoExtractBill:信息抽取OCR识别，infoExtractBill:单据票证抽取，infoExtractDoc:长文档信息抽取 ）'."\n" .'classType 模型预测服务、模板预测服务 '."\n" .'predictFile 预测文件地址（失效时间60分钟）'."\n" .'```', ], 'CreateModelAsyncPredict' => [ 'summary' => '文档自学习创建异步预测任务接口。', 'methods' => [ 'post', ], 'schemes' => [ 'http', 'https', ], 'security' => [ [ 'AK' => [], ], ], 'operationType' => 'write', 'deprecated' => false, 'systemTags' => [ 'operationType' => 'create', 'riskType' => 'none', 'chargeType' => 'free', ], 'parameters' => [ [ 'name' => 'ModelVersion', 'in' => 'query', 'schema' => [ 'description' => '模型对应的版本号，如果不传入版本号表示默认用模型最新生效的版本。', 'type' => 'string', 'required' => false, 'example' => 'V1', ], ], [ 'name' => 'BinaryToText', 'in' => 'query', 'schema' => [ 'description' => 'content字段是图片URL时：false'."\n" .'body为base64的内容时：true', 'type' => 'boolean', 'required' => false, 'example' => 'false：表示content传入的是url'."\n" .'true：表示body是直接传入图片进行base64的内容'."\n", 'default' => 'false', ], ], [ 'name' => 'Content', 'in' => 'query', 'schema' => [ 'description' => '图片或pdf文件访问URL地址', 'type' => 'string', 'required' => false, 'example' => 'https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/3/1559855998794593/stage/upload/20230206/oss-hlfCRJ1SorSWs10MkqxK6YcL4OVAFSv4.png?Expires=1675665563&OSSAccessKeyId=XXXX&Signature=WLKghBc3zKzWJ3Td69%2B4C21jrbE%3D', ], ], [ 'name' => 'ModelId', 'in' => 'query', 'schema' => [ 'description' => '模型ID。模型列表页模型ID', 'type' => 'integer', 'format' => 'int64', 'required' => false, 'maximum' => '9999999999999', 'minimum' => '1', 'example' => '123', ], ], [ 'name' => 'ServiceName', 'in' => 'query', 'schema' => [ 'description' => '预训练服务名称', 'type' => 'string', 'required' => false, 'example' => 'pre_train_service', ], ], [ 'name' => 'ServiceVersion', 'in' => 'query', 'schema' => [ 'description' => '预训练服务版本', 'type' => 'string', 'required' => false, 'example' => 'V1', ], ], [ 'name' => 'Body', 'in' => 'formData', 'schema' => [ 'description' => '图片base64编码内容', 'type' => 'string', 'required' => false, 'example' => 'data:image/png;base64,xxxxx', ], ], ], 'responses' => [ 200 => [ 'schema' => [ 'title' => 'Schema of Response', 'description' => 'Schema of Response', 'type' => 'object', 'properties' => [ 'RequestId' => [ 'title' => 'Id of the request', 'description' => 'Id of the request', 'type' => 'string', 'example' => '3EAC98E6-8DD6-511F-8764-DEE8B6EB6BB4', ], 'Code' => [ 'description' => '请求结果状态，200为成功', 'type' => 'integer', 'format' => 'int32', 'example' => '200', ], 'Message' => [ 'description' => '错误信息。', 'type' => 'string', 'example' => 'success', ], 'Data' => [ 'description' => '返回数据', 'type' => 'string', 'example' => '{'."\n" .' "RequestId": "292D1584-134C-1221-B9BB-1B847C623D41",'."\n" .' "Message": "",'."\n" .' "Data": 1,'."\n" .' 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