- API
- 智能文档版面检测与识别
POST/ai_image_detect/wen_dang_ban_mian/v1
请求参数(Header)
无参数
请求参数(Query)
无参数
请求参数(Body)
- 接口文档
- 请求示例
- 成功响应
- 失败响应
- 错误码
- 调用结果
接口信息
https://wdbm.market.alicloudapi.com/ai_image_detect/wen_dang_ban_mian/v1
POST
JSON
API 简单身份认证调用方法(APPCODE)API 签名认证调用方法(AppKey & AppSecret)
接口参数
请求参数(Header)
字段名称 | 必填 | 字段详情 |
---|---|---|
无参数 |
请求参数(Query)
字段名称 | 必填 | 字段详情 |
---|---|---|
无参数 |
请求参数(Body)
字段名称 | 必填 | 字段详情 |
---|---|---|
IMAGE string | Y | 图像数据,BASE64编码后进行URLENCODE,要求BASE64编码和URLENCODE后大小不超过2M,最短边至少15PX,最长边最大4096PX,支持JPG/PNG/BMP格式 实例值: 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wq1/wkRKFxYzbUhWWUsQpQFmXoeT90n8qANsnBxijNZF+bqfVba1ivprRGglkYwqhLEMgH3lb+8elUrfxAY7SF5w8k7qqbIwArtuYEjuPuk9elAHS0HgVhf8JH8hk+wzBEiWWUsQpQFmXoev3Sabc+IZES8WO12zQZ2LK2DJhguQOpHPUe1AG9n2ozWE+svZm486NpGN0IYo17fulcjP8A31StroWNpltrl+EzGVxs3Z5PGQBtPPTpQBu0Vh/28wvJwYUa1S3t5UkRwctI7r16Y4H61LPrbR3bW0Nm80is6nDgD5VRu/8AvigDXorEPiOPdG0ds727PGhlyBt3gEcdehFRw+JfPQGOwnJcoI88BtxI6n0xQBv0Vmf2wv8AZbXjRhCshiKO4HzBymM9DyOPWqaeJfNRGjsZW/dvJJ8wGwKwU9evWgDeJxRurF17V5LLTZmtYWknNrLOpBA2hVzu59yOKZPrqWsrRiKaeUvtCcY4RWOCB0+YfmaAN6iorecXEEUyqyrIoYBhgjIzyOxqWgAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAqKX/Wwf8AXQ/+gtUtRS/62D/rof8A0FqAJaKKKACiiigAooooAKKKKACiiigAooooAKKKKACobiKGRUMwBEbh1JPQjoam7Vka6oMNs0q7rZZwZgVLDGDgkdxnFAFySytrmeO5IbzEHyvHKy5Gc4OCMjPY5p/2G28kQ+UPLEglAyeGDbs/nzXLSX+ow2UaWYgtoC8gjmWMojYAIO0hiBuLfXHUZq5JqWoQ6lJES0rMjeXFCAVQhC3zZXPUYyCeo4oA1pNLs2lRyjK6szKUlZTljubODyCQDg8cVZt4IYI8QoFVmaQ85yWJYn8SSa5qwur24eynvJFlVbnhlHK5iYYYbV7n36023vbm0sNFCyOIlt40lhjUeYXGFIwVORnIOCD6ZoA3otMsrePy1RhHvRgrSsVUq2VwCeACBgDih9Jsjem8MTeezKxPmNglRgErnBIHtWNcy3N5aXEZupVuBcxjyRGP3QE6gMDjJ455z1qPUtV1GzscLJMZ1afa5jUK4QjAb5TyQeAAM88igDoFsLMwx23lDy4U2ImT8o27cflxUF9pkEluUiREkwgVmZht2njBUgjuOD3rH8q4TUZrgzTRq2pxliEH3Ps6gDp03HFaurubjQ7zygznaV4BzkUAS6ZpEGn21qgBMkEXlB9x5BOeRnnn1ok0HTZZJXe3LeasiuvmNtw/38LnAz3IFU7Sa/F7G0s0jxy3E0XlmMAIqlipBHPYDnrms++mka41T+zJZ/tUNtPySxMku35Qo6YU9/w55oA6SOwt4rp7mNXWRzlgJG2k+u3O3Pvio/7LtRdvdKJlldw7bZ3Ck4AyVzt6Adu1c3LLiXas11/ZnmHa4LHLeXwM9cbs/jirsdu01zp4aSf7UyrPOWc/IiqBjHTk4/8AHqANX+yrB4lgMA2xxLEuHIKqCCuCDkEEAg9QR1qQabagAGNnxG0eXkZjtYgkZJz2FYlxcXMHimUQzPlxbKIPL+WRSzhjuxxgc8HtVRLzVbqxle4uDHslt3ZYxl4sTDeMbR8u33PQ0AdJdaRZXoQTxMdilBslZMqcZB2kZHA60DSbJb0XgiImBJB8xtoJABIXOAcAc4rMW4voonu5biQx/a2jKGMYSIOQDwM9B1z3rJ1LX7+PRLu9juXg8uO7eBvJB8xkkcRqQR02gHt60AdNLo+nvdC7eDMqMzjMjbQxUqTtztyVJGcd6I9KtFtvIQziIkEAXMnHHQHdkD2HFZ3iO6uYkESTvBFJbysXSLcWcbdq8g9QW9+Kox6hq0cksalUEMR2REcsoiBDD5eTu98dqAOiuNNsp9LbTZoFazdPKMTE4K+meuffr3prWFlJdLcMn70MM4kIBI6ZUHBI7ZHGBVG9gu18PPLJLJc3UAS6HygFmTD7QAO+0j/gVYltDepeR7YpG3o+qjcDjeVKiM+/zg/8BoA61tOtntY7fEiRR/dEUzofzUgnrUbaNYMFHkbQqoi+W7JtCfdxgjGPb6Vi2N1q11HAjXYVZJ8GSNQzKPLyVOUAHPt3rS0/zkvtWWSWWQ+erRq3ZfKTpx6g/lQBPDpVjCnlRwgDYyEFyx2scnknPJo/sTT/ALSLjyWEgJK4lcBSV2kgZwCR3AzXLw6hqOJ7pJpHmeK1WV2i2eSSW3gfKenuDjNbOnS6ndXsYuLrESWySHykBEjFnHUgHoq8DFAGh/YtgVAeFpMSJKDLIzncv3eSSePTpyfWlbTLL7W0xizI4bILkjngkLnAOOCQM81mfbdSPiKS33Ituj4CMeXTy87h8vXdx97GB0rOmlv4otHubi9nE72kjSSeQv3ysZ2424AJ9eeMUAdNLptrcRxJIj7IxhUWV1UjjggHDdO+aP7Ls85EbKfn5WRh98kt0PqSfbtislLvURDqF3cSzqsJRUgiiXvFGSckZPzM3tx7VUtdVvpEZbi6khhSd0+0LGGJARGA+7jqzDOP4fzANqPRdPEUUKJKFg4jIuJNyDABUHdkDpxnHA9Ktf2fa5Y+UDukEpyTywUKD+QA/CuecX8TzmGeUpcXMkZQRjAHlMQwOM53KPbmmxX+qLdWNtFOPK+zwndLx5rEsHB+Q8gBemOTQBsroGmxIypA43BRu859yhfuhTnK47YxTxZ2LCSHAcvGInDSFmKgkgEk5/iPvzVHSJ9QaaL7VM8izLIxVowoTD4UDAHbHWs8LbG5dIYANQ/tIMGWPD7d67vmx027u9AHQ3GnWt+0c0ok3orKrxTPGcHGRlSMjgflQ2kWDQrELcIiKiII2KbQv3cEEYx7Vz8Ooar9rs4V2RRtBE2112q7FmDjAUngBeAR1qRbrV1tGka6+eSN2BljCrERJgYwp/h9QeecdqAN06bZiKRWjLB4xG5d2JKgkgEk56sajbSrOV5JHV380EHdM7AA9cAnC/UYrCNxc3c9vIZbnYbS7iZWVcSODHjoPQNjoePrUltf6g2pW1urrHbbYgqv/wAtEKZY/dPOcjGR933oA2TpVlMCxRzuKvuWZwcgYDAg5zjjPcdakbS7Vl27ZRkKCyzOrHGcfMDnue9YNhf3wfS1mZts9rDmGJACjlMsWBXgZ9Dx6UkOpXVhpkIlmldvsrbWdMsZVbBBwOtAG7/Y9htKiDAMSwnDsMqpJXv1BJIPUZNLb6VZWrl4ojvJZizSMxJYAHJJPZR+VZCXmrLmfLzFpJlWAxgDChtnOM5JA5z3qiNY1DMyQ3rXEamAPK0YQx7lfd/D/eCjkHGfyANWXQI3v7WRFSOGB43CqzZJQYXjdt9OcZxVxNNsrUAKpChgyq8zEKRnGATgdTwKyRdasUac3B/c2scgSOMMsjF3zklQeVC9MVJqwX+37YzNAIfs7Z86FpATuHTBGDigDWk0+0ltnt3T920nmHa5BDlt2QQcg7ueKjg0vT4kaOKIYKMrAyFiQxyc5OeTWVcSOZbizXzPtD6lbyRqoPMYMTMfphWz+NQaXaXUeqWckqrHEzTsrRxEM7ZYbHJbGMHcOOdvbuAdBe6TY6jbiG6hLRhSmFdkypGCCVIyCO1EulWcxLNGyuW3b45WRs4C9VIPQD8qyLqaezn1NfPmAmeJUdskRbgckemB/IetKL9dS0CzntN/luiTPEJNrGIdRuOB+ZGcUAdCqhVVRnAGBkk06uU8h7iwtTI1ylxctthRpOYowSxY4PUKf/QRVzQ9US81K6iZn85kWYKSfkTLKq4I4OFyfdjQBv0UUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAVFL/rYP+uh/wDQWqWopf8AWwf9dD/6C1AEtFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABUFzdR2yxl8/vHCKAM8mp+1Z2pIxexZUZglwpbaCcDBGfpzQBYivLeTyCkqsLhN8RH8S4zn8iKsZGa5ZNJ1CD7aiK3lQkJaeXIFZoWk3uo5G0gfIOR06irFpp1293C9x9ritUWYrG1ydy5MezcQx3Hh+5xmgDfSRXXK5xnuCKbDcRToXicOodkJH95SVI/AgiuTuE1a7WFrWO4kVXysqT7efNOQwLjI2gY4buOO8zaVqENvdtbmdZ5jeHAnOBuJ8sgZwp6HjFAHTz3EVtA80zhI0GWY9qjhvra4CmOTO9iqgqVJIGeh9qztQ06RfD1xa2onllZBgGXc5PHQucdvpTGS7ZbO4+y3cj28zM0crxeYwKFcjDbf4vUdKAL8ur2EKhpLlQCXGQCcbSQ3Tpggg1YNzAIPPM0YhI3CTcNuPXPpXMx6PqfkboZWs52F1IrAqdjSzNIqt16Buce9W7yzKaLp7xw+W9jtdLeUeZk7GQIcdT83UdwKAN7emzfuG3Gc54xTHuYYzHukH71tqY53HGf5VhvbXcOhx6etpJLtCJMY2QblPLbcsPpziqZXVtQsrC9jtbiG6NmNiiRFEMpA5cbuV9hk47ZoA6iS4ijRyWBKoXKjrgU23McqrdIo/eoCGxyV6jP5n86595r5dbuUl0+fy57ebEo2MAqbQgGGzzubjGckehxs6aXWxghkhkQxwp8zYwTjkdc5GO4FADrTVLS+I+ztKwZdysYXVSPUEjBqxLPHBE8srhUQZZj2Fc3ptpfw6E1lLFqccotPKDeZBhW24/d4bOc9M+nNWEtb2Xw7eWssEiuyskavLucgjjJ3Nj86AN/cvqOap3llb32EuA7L/cEjKrD0YA4YexzWNdWOoxQzwQJdTQtcAoRdHeqeWMkEuDjfngn19qSCw1Vktp52n+0pHZhl+0fLuDfvsqG2njOfXtQB0ZniW4SAuBK6M6r3KggE/huH50klxFEyrI4Uvnbn2GT+grk307V2vppI47hZha3UYn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商品介绍
产品亮点
智能图像分析-智能文档版面检测与识别-艾科瑞特(iCREDIT)
智能图像分析-智能文档版面检测与识别-艾科瑞特(iCREDIT),凭借领先的人工智能与知识图谱技术,通过客观、真实的数据,创新、完善的技术解决方案,帮助企业获得敏锐的洞察力及卓越的运营能力,智能图像分析-智能文档版面检测与识别,赋能智慧数据领域应用场景,让企业实现数字化升级;智能图像分析-智能文档版面检测与识别,支持对图像文档版面中多种图样检测与识别,支持远距离、近距离多种图样类型识别与定位,实现快速远距离与近距离甄别文档版面目标图样定位与聚焦,辨析图像中是否包含图标、标志、图表、表格、签字等信息
新技术必将改变企业的方方面面,您将从何处踏上数字化转型征程?至关重要的是,企业必须首先找到一家深谙业务与技术交汇融合的合作伙伴
为日新月异的中国新经济变革,将咨询、数字和技术等领域的独到服务应用于行业领域,助力客户应对最严峻的挑战
关键词:智能文档版面检测与识别、自然语言处理、企业知识图谱、NLP、深度学习、人工智能、AI、DEEP LEARNING
产品说明
智能图像分析-智能文档版面检测与识别-艾科瑞特(iCREDIT)
智能图像分析-智能文档版面检测与识别-艾科瑞特(iCREDIT),凭借领先的人工智能与知识图谱技术,通过客观、真实的数据,创新、完善的技术解决方案,帮助企业获得敏锐的洞察力及卓越的运营能力,智能图像分析-智能文档版面检测与识别,赋能智慧数据领域应用场景,让企业实现数字化升级;智能图像分析-智能文档版面检测与识别,支持对图像文档版面中多种图样检测与识别,支持远距离、近距离多种图样类型识别与定位,实现快速远距离与近距离甄别文档版面目标图样定位与聚焦,辨析图像中是否包含图标、标志、图表、表格、签字等信息
新技术必将改变企业的方方面面,您将从何处踏上数字化转型征程?至关重要的是,企业必须首先找到一家深谙业务与技术交汇融合的合作伙伴
为日新月异的中国新经济变革,将咨询、数字和技术等领域的独到服务应用于行业领域,助力客户应对最严峻的挑战
关键词:智能文档版面检测与识别、自然语言处理、企业知识图谱、NLP、深度学习、人工智能、AI、DEEP LEARNING
产品参数
交付方式 | API |
开票主体 | 深圳艾科瑞特科技有限公司 |
所属类目 | AI应用与OCR |
上架日期 | 2020-10-15 |
产品截图
售后支持范围
工作日:周一至周五【每天10:30-17:00】 技术支持钉钉号:icredit【备注:阿里云市场】 技术支持电话:0532-88984128
产品资质
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商品价格(此处价格仅供参考,实际价格以选配后的价格为准)
版本名称 | 计费项 | 新购 |
0.01元/1次 | 版本基础价格 | 0.01元 |
998元/10万次 | 版本基础价格 | 998元 |
1998元/40万次 | 版本基础价格 | 1998元 |
4998元/100万次 | 版本基础价格 | 4998元 |
9998元/200万次 | 版本基础价格 | 9998元 |
19998元/1000万次 | 版本基础价格 | 19998元 |
私有化授权费-59998元/次【不限制装机量】 | 版本基础价格 | 59998元 |
私有化模型更新费-9998元/年 | 版本基础价格 | 9998元 |
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服务商
深圳艾科瑞特科技有限公司
艾科瑞特科技(iCREDIT)集团面向全球提供人工智能(AI)与大数据(BIG DATA)解决方案,通过其旗下品牌服务全球顶尖投资银行、基金公司以及众多世界五百强企业,素有全华尔街都在使用的中国标准之称。企业拥有众多深受信赖的优质、领先品牌,包括艾科瑞特(iCREDIT)、超验(iTRANSCEND)、玄机(iTHEORY)、泰始明昌(TAISHIMINGCHANG)等等;艾科瑞特在全球近约近三百个国家和地区开展业务
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- 数据与API
- AI与大数据计算
客服在线:09:00-18:00【工作日】
旺旺:技术支持,官方钉钉与微信:17060450860旺旺:商务支持,官方钉钉与微信:17060450860旺旺:发票支持,官方钉钉与微信:17060450860钉钉:17060450860(微信同号),技术支持钉钉:17060450860(微信同号),商务支持电话:0532-88984128
邮箱:market@icredit.link 官方钉钉与微信:17060450860入住时间:2017-09-30
所在地区:440000 440300
入驻集市:数据市场
可开发票类型:增值税专用发票
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商家商品数量:5000近180天成交订单量:4811近180天退单率:0.12%店铺评分状态
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用户评论 (1)
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