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articles/applied-ai-services/form-recognizer/concept-business-card.md

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#### Sample Labeling tool
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You will need a business card document. You can use our [sample business card document](https://raw.githubusercontent.com/Azure-Samples/cognitive-services-REST-api-samples/master/curl/form-recognizer/businessCard.png).
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You'll need a business card document. You can use our [sample business card document](https://raw.githubusercontent.com/Azure-Samples/cognitive-services-REST-api-samples/master/curl/form-recognizer/businessCard.png).
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1. On the Sample Labeling tool home page, select **Use prebuilt model to get data**.
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* Supported file formats: JPEG, PNG, BMP, TIFF, and PDF (text-embedded or scanned). Text-embedded PDFs are best to eliminate the possibility of error in character extraction and location.
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* For PDF and TIFF, up to 2000 pages can be processed (with a free tier subscription, only the first two pages are processed).
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* The file size must be less than 50 MB.
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* Image dimensions must be between 50 x 50 pixels and 10000 x 10000 pixels.
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* Image dimensions must be between 50 x 50 pixels and 10,000 x 10,000 pixels.
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* PDF dimensions are up to 17 x 17 inches, corresponding to Legal or A3 paper size, or smaller.
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* The total size of the training data is 500 pages or less.
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* If your PDFs are password-locked, you must remove the lock before submission.

articles/applied-ai-services/form-recognizer/concept-layout.md

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* Supported file formats: JPEG, PNG, BMP, TIFF, and PDF (text-embedded or scanned). Text-embedded PDFs are best to eliminate the possibility of error in character extraction and location.
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* For PDF and TIFF, up to 2000 pages can be processed (with a free tier subscription, only the first two pages are processed).
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* The file size must be less than 50 MB.
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* Image dimensions must be between 50 x 50 pixels and 10000 x 10000 pixels.
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* Image dimensions must be between 50 x 50 pixels and 10,000 x 10,000 pixels.
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> [!NOTE]
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> The [Sample Labeling tool](https://fott-2-1.azurewebsites.net/) does not support the BMP file format. This is a limitation of the tool not the Form Recognizer Service.
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## Supported languages and locales
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Form Recognizer preview version introduces additional language support for the layout model. *See* our [Language Support](language-support.md) for a complete list of supported handwritten and printed languages.
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Form Recognizer preview version introduces additional language support for the layout model. *See* [Language Support](language-support.md) for a complete list of supported handwritten and printed languages.
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## Features
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### Tables and table headers
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Layout API extracts tables in the `pageResults` section of the JSON output. Documents can be scanned, photographed, or digitized. Tables can be complex with merged cells or columns, with or without borders, and with odd angles. Extracted table information includes the number of columns and rows, row span, and column span. Each cell with its bounding box is output along with information whether it's recognized as part of a header or not. The model predicted header cells can span multiple rows and are not necessarily the first rows in a table. They also work with rotated tables. Each table cell also includes the full text with references to the individual words in the `readResults` section.
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Layout API extracts tables in the `pageResults` section of the JSON output. Documents can be scanned, photographed, or digitized. Tables can be complex with merged cells or columns, with or without borders, and with odd angles. Extracted table information includes the number of columns and rows, row span, and column span. Each cell with its bounding box is output along with information whether it's recognized as part of a header or not. The model predicted header cells can span multiple rows and aren't necessarily the first rows in a table. They also work with rotated tables. Each table cell also includes the full text with references to the individual words in the `readResults` section.
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:::image type="content" source="./media/layout-table-headers-example.png" alt-text="Layout table headers output":::
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### Text lines and words
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Layout API extracts text from documents and images with multiple text angles and colors. It accepts photos of documents, faxes, printed and/or handwritten (English only) text, and mixed modes. Text is extracted with information provided on lines, words, bounding boxes, confidence scores, and style (handwritten or other). All the text information is included in the `readResults` section of the JSON output.
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Layout API extracts text from documents and images with multiple text angles and colors. It accepts photos of documents, faxes, printed and/or handwritten (English only) text, and mixed modes. Text is extracted with information provided in lines, words, and bounding boxes. All the text information is included in the `readResults` section of the JSON output.
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:::image type="content" source="./media/layout-text-extraction.png" alt-text="Layout text extraction output":::
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### Natural reading order for text lines (Latin only)
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In Form Recognizer v2.1, you can specify the order in which the text lines are output with the `readingOrder` query parameter. Use `natural` for a more human-friendly reading order output as shown in the following example. This feature is only supported for Latin languages.
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In Form Recognizer v3.0, the natural reading order output is used by the service in all cases. Therefore, there is no `readingOrder` parameter provided in this version.
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In Form Recognizer v3.0, the natural reading order output is used by the service in all cases. Therefore, there's no `readingOrder` parameter provided in this version.
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### Handwritten classification for text lines (Latin only)
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