OCR för avbildningar (version 4.0)

Kommentar

Om du vill extrahera text från PDF-filer, Office-filer eller HTML-dokument och dokumentbilder använder du OCR-modellen För dokumentinformation. Den är optimerad för textintensiva digitala och skannade dokument och använder ett asynkront API som gör det enkelt att driva dina intelligenta dokumentbearbetningsscenarier.

OCR är en maskininlärningsbaserad teknik för att extrahera text från vilda och icke-dokumentbilder som produktetiketter, användargenererade bilder, skärmbilder, gatuskyltar och affischer. Azure AI Vision OCR-tjänsten tillhandahåller ett snabbt, synkront API för enklare scenarier där bilder inte är texttunga. Detta gör att OCR kan bäddas in i användarupplevelser i nära realtid för att berika innehållstolkning och uppföljning av användaråtgärder med snabba omsvängningstider.

Vad är Azure AI Vision v4.0 Läs OCR?

Det nya REST-API:et för Azure AI Vision Image Analysis 4.0 ger möjlighet att extrahera tryckt eller handskriven text från bilder i ett enhetligt prestandaförstärkt synkront API som gör det enkelt att få alla bildinsikter, inklusive OCR-resultat i en enda API-åtgärd. Read OCR-motorn bygger på flera djupinlärningsmodeller som stöds av universella skriptbaserade modeller för globalt språkstöd.

Exempel på textextrahering

Följande JSON-svar illustrerar vad API:et för bildanalys 4.0 returnerar när du extraherar text från den angivna bilden.

Foto av en klibbig anteckning med skrivning på den.

{
    "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}
                        ]
                    }
                ]
            }
        ]
    }
}

Använda API:et

Funktionen för textextrahering är en del av API:et Analysera bild. Inkludera Read i frågeparametern funktioner . När du sedan får det fullständiga JSON-svaret parsar du strängen för innehållet i "readResult" avsnittet.

Nästa steg

Följ snabbstarten Bildanalys för att extrahera text från en bild med api:et Bildanalys 4.0.