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用于图像的 OCR (版本 4.0)
注意
要从 PDF、Office 和 HTML 文档和文档图像中提取文本，请使用针对文本较多的数字文档和扫描文档优化的文档智能读取 OCR 模型，其异步 API 可轻松助力智能文档处理。
OCR 传统上是一种基于机器学习的技术，用于从原始图像和非文档图像（如产品标签、用户生成的图像、屏幕截图、路标和海报等）中提取文本。 对于一些场景（如文本不多的单个图像），你需要快速且同步的 API 或服务。 这样可将 OCR 嵌入准实时的用户体验中，从而能以较快的运转速度丰富内容理解并跟进用户操作。
什么是计算机视觉 v4.0 读取 OCR?
新的计算机视觉图像分析 4.0 REST API 提供了在性能增强的统一同步 API 中从图像中提取打印文本或手写文本的功能，借助该 API，可通过单个 API 操作轻松获取包括 OCR 结果在内的所有图像见解。 读取 OCR 引擎建立在多个深度学习模型的基础之上，这些模型由基于脚本的通用模型支持，以提供全球语言支持。
提示
可以通过 Azure OpenAI 服务使用 OCR 功能。 使用 GPT-4 Turbo with Vision 模型，可以与能够分析所共享图像的 AI 助手聊天，并且视觉增强选项使用可图像分析为 AI 助手提供有关图像的更多详细信息（可读文本和对象位置）。 有关详细信息，请参阅 GPT-4 Turbo with Vision 快速入门。
文本提取示例
以下 JSON 响应说明了在从给定图像中提取文本时图像分析 4.0 API 返回的内容。
{
"modelVersion": "2024-02-01",
"metadata":
{
"width": 1000,
"height": 945
},
"readResult":
{
"blocks":
[
{
"lines":
[
{
"text": "You must be the change you",
"boundingPolygon":
[
{"x":251,"y":265},
{"x":673,"y":260},
{"x":674,"y":308},
{"x":252,"y":318}
],
"words":
[
{"text":"You","boundingPolygon":[{"x":252,"y":267},{"x":307,"y":265},{"x":307,"y":318},{"x":253,"y":318}],"confidence":0.996},
{"text":"must","boundingPolygon":[{"x":318,"y":264},{"x":386,"y":263},{"x":387,"y":316},{"x":319,"y":318}],"confidence":0.99},
{"text":"be","boundingPolygon":[{"x":396,"y":262},{"x":432,"y":262},{"x":432,"y":315},{"x":396,"y":316}],"confidence":0.891},
{"text":"the","boundingPolygon":[{"x":441,"y":262},{"x":503,"y":261},{"x":503,"y":312},{"x":442,"y":314}],"confidence":0.994},
{"text":"change","boundingPolygon":[{"x":513,"y":261},{"x":613,"y":262},{"x":613,"y":306},{"x":513,"y":311}],"confidence":0.99},
{"text":"you","boundingPolygon":[{"x":623,"y":262},{"x":673,"y":263},{"x":673,"y":302},{"x":622,"y":305}],"confidence":0.994}
]
},
{
"text": "wish to see in the world !",
"boundingPolygon":
[
{"x":325,"y":338},
{"x":695,"y":328},
{"x":696,"y":370},
{"x":325,"y":381}
],
"words":
[
{"text":"wish","boundingPolygon":[{"x":325,"y":339},{"x":390,"y":337},{"x":391,"y":380},{"x":326,"y":381}],"confidence":0.992},
{"text":"to","boundingPolygon":[{"x":406,"y":337},{"x":443,"y":335},{"x":443,"y":379},{"x":407,"y":380}],"confidence":0.995},
{"text":"see","boundingPolygon":[{"x":451,"y":335},{"x":494,"y":334},{"x":494,"y":377},{"x":452,"y":379}],"confidence":0.996},
{"text":"in","boundingPolygon":[{"x":502,"y":333},{"x":533,"y":332},{"x":534,"y":376},{"x":503,"y":377}],"confidence":0.996},
{"text":"the","boundingPolygon":[{"x":542,"y":332},{"x":590,"y":331},{"x":590,"y":375},{"x":542,"y":376}],"confidence":0.995},
{"text":"world","boundingPolygon":[{"x":599,"y":331},{"x":664,"y":329},{"x":664,"y":372},{"x":599,"y":374}],"confidence":0.995},
{"text":"!","boundingPolygon":[{"x":672,"y":329},{"x":694,"y":328},{"x":694,"y":371},{"x":672,"y":372}],"confidence":0.957}
]
},
{
"text": "Everything has its beauty , but",
"boundingPolygon":
[
{"x":254,"y":439},
{"x":644,"y":433},
{"x":645,"y":484},
{"x":255,"y":488}
],
"words":
[
{"text":"Everything","boundingPolygon":[{"x":254,"y":442},{"x":379,"y":440},{"x":380,"y":486},{"x":257,"y":488}],"confidence":0.97},
{"text":"has","boundingPolygon":[{"x":388,"y":440},{"x":435,"y":438},{"x":436,"y":485},{"x":389,"y":486}],"confidence":0.965},
{"text":"its","boundingPolygon":[{"x":445,"y":438},{"x":485,"y":437},{"x":486,"y":485},{"x":446,"y":485}],"confidence":0.99},
{"text":"beauty","boundingPolygon":[{"x":495,"y":437},{"x":567,"y":435},{"x":568,"y":485},{"x":496,"y":485}],"confidence":0.685},
{"text":",","boundingPolygon":[{"x":577,"y":435},{"x":583,"y":435},{"x":583,"y":485},{"x":577,"y":485}],"confidence":0.939},
{"text":"but","boundingPolygon":[{"x":589,"y":435},{"x":644,"y":434},{"x":644,"y":485},{"x":589,"y":485}],"confidence":0.628}
]
},
{
"text": "not everyone sees it !",
"boundingPolygon":
[
{"x":363,"y":508},
{"x":658,"y":493},
{"x":659,"y":539},
{"x":364,"y":552}
],
"words":
[
{"text":"not","boundingPolygon":[{"x":363,"y":510},{"x":412,"y":508},{"x":413,"y":548},{"x":365,"y":552}],"confidence":0.989},
{"text":"everyone","boundingPolygon":[{"x":420,"y":507},{"x":521,"y":501},{"x":522,"y":542},{"x":421,"y":548}],"confidence":0.924},
{"text":"sees","boundingPolygon":[{"x":536,"y":501},{"x":588,"y":498},{"x":589,"y":540},{"x":537,"y":542}],"confidence":0.987},
{"text":"it","boundingPolygon":[{"x":597,"y":497},{"x":627,"y":495},{"x":628,"y":540},{"x":598,"y":540}],"confidence":0.995},
{"text":"!","boundingPolygon":[{"x":635,"y":495},{"x":656,"y":494},{"x":657,"y":540},{"x":636,"y":540}],"confidence":0.952}
]
}
]
}
]
}
}
使用 API
文本提取功能是分析图像 API 的一部分。 将 Read 包括在 features 查询参数中。 然后，在获取完整 JSON 响应时，请分析 "readResult" 部分内容的字符串。
后续步骤
按照图像分析快速入门，使用图像分析 4.0 API 从图像中提取文本。