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OCR for images (version 4.0)

Note

If you want to extract text from PDFs, Office files, or HTML documents and document images, use the Document Intelligence Read OCR model. It's optimized for text-heavy digital and scanned documents and uses an asynchronous API that makes it easy to power your intelligent document processing scenarios.

OCR is a machine-learning-based technique for extracting text from in-the-wild and non-document images like product labels, user-generated images, screenshots, street signs, and posters. The Azure AI Vision OCR service provides a fast, synchronous API for lightweight scenarios where images aren't text-heavy. This allows OCR to be embedded in near real-time user experiences to enrich content understanding and follow-up user actions with fast turn-around times.

What is Azure AI Vision v4.0 Read OCR?

The new Azure AI Vision Image Analysis 4.0 REST API offers the ability to extract printed or handwritten text from images in a unified performance-enhanced synchronous API that makes it easy to get all image insights including OCR results in a single API operation. The Read OCR engine is built on top of multiple deep learning models supported by universal script-based models for global language support.

Text extraction example

The following JSON response illustrates what the Image Analysis 4.0 API returns when extracting text from the given image.

Photo of a sticky note with writing on it.

{
    "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}
                        ]
                    }
                ]
            }
        ]
    }
}

Use the API

The text extraction feature is part of the Analyze Image API. Include Read in the features query parameter. Then, when you get the full JSON response, parse the string for the contents of the "readResult" section.

Next steps

Follow the Image Analysis quickstart to extract text from an image using the Image Analysis 4.0 API.