Cloudmersive · Schema

PhotoToWordsWithLocationResult

Result of an photo to words-with-location OCR operation

BarcodesConversionDocumentsImage RecognitionNatural-LanguageOCRProcessingValidationVirus Scanning

Properties

Name Type Description
Successful boolean True if successful, false otherwise
TextElements array Word elements in the image
DiagnosticImage string Typically null. To analyze OCR performance, enable diagnostic mode by adding the HTTP header "DiagnosticMode" with the value "true". When this is true, a diagnostic image showing the details of the OC
View JSON Schema on GitHub

JSON Schema

cloudmersive-photo-to-words-with-location-result-schema.json Raw ↑
{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "$id": "https://artifacts.apis.io/cloudmersive/json-schema/cloudmersive-photo-to-words-with-location-result-schema.json",
  "title": "PhotoToWordsWithLocationResult",
  "description": "Result of an photo to words-with-location OCR operation",
  "x-generated": "2026-11-05",
  "x-method": "derived",
  "x-generator": "derive-json-schema.py",
  "x-source": "openapi/cloudmersive-imageocr-api-openapi.yml#/components/schemas/PhotoToWordsWithLocationResult",
  "type": "object",
  "properties": {
    "Successful": {
      "description": "True if successful, false otherwise",
      "type": "boolean"
    },
    "TextElements": {
      "description": "Word elements in the image",
      "type": "array",
      "items": {
        "$ref": "#/$defs/OcrPhotoTextElement"
      }
    },
    "DiagnosticImage": {
      "format": "byte",
      "description": "Typically null.  To analyze OCR performance, enable diagnostic mode by adding the HTTP header \"DiagnosticMode\" with the value \"true\".  When this is true, a diagnostic image showing the details of the OCR result will be set in PNG format into DiagnosticImage.",
      "type": "string"
    }
  },
  "$defs": {
    "OcrPhotoTextElement": {
      "description": "A single text in an OCR document",
      "type": "object",
      "properties": {
        "Text": {
          "description": "Text of the word",
          "type": "string"
        },
        "XLeft": {
          "format": "int32",
          "description": "X location of the left edge of the word in pixels",
          "type": "integer"
        },
        "YTop": {
          "format": "int32",
          "description": "Y location of the top edge of the word in pixels",
          "type": "integer"
        },
        "Width": {
          "format": "int32",
          "description": "Width of the word in pixels",
          "type": "integer"
        },
        "Height": {
          "format": "int32",
          "description": "Height of the word in pixels",
          "type": "integer"
        },
        "BoundingPoints": {
          "description": "Points that form the bounding polygon around the text",
          "type": "array",
          "items": {
            "$ref": "#/$defs/Point"
          }
        },
        "ConfidenceLevel": {
          "format": "double",
          "description": "Confidence level of the machine learning result; possible values are 0.0 (lowest accuracy) - 1.0 (highest accuracy)",
          "type": "number"
        }
      }
    },
    "Point": {
      "description": "Point location in 2D in an image, where 0, 0 represents the top/left corner of the image",
      "type": "object",
      "properties": {
        "X": {
          "format": "int32",
          "description": "X location in 2D in the image, where 0 represents the left edge of the image",
          "type": "integer"
        },
        "Y": {
          "format": "int32",
          "description": "Y location in 2D in the image, where 0 represents the top edge of the image",
          "type": "integer"
        }
      }
    }
  }
}

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