Preparing content for recognition

Aspose.OCR for Python via .NET provides a versatile way to prepare your content for OCR. A package of recognized files/folders/URLs, regardless of their number and type, is constructed as OcrInput object. With this approach, you can easily process a single image or a large number of images from an auto-feed scanner in a single API call.

The object constructor takes the type of the provided content and optional processing filters that will be applied to all images in a batch.

Supported content types

You can only pack sources of the same type into one OcrInput object. The type is specified in the constructor and cannot be changed later.

Source content type	Supported file formats
`InputType.SINGLE_IMAGE`	One or more GIF, PNG, JPEG, BMP, or single-page TIFF images. The images can be provided by their absolute or relative paths, as `MemoryStream` objects, or as arrays of pixels. You can add images of different types in a single batch.
`InputType.PDF`	One or more PDF documents, containing scanned pages. The files can be provided by their absolute or relative paths or as `MemoryStream` objects.
`InputType.TIFF`	One or more multi-page TIFF images. The files can be provided by their absolute or relative paths or as `MemoryStream` objects.
`InputType.DJVU`	One or more DjVu files, provided by their absolute or relative paths or as `MemoryStream` objects.
`InputType.URL`	One or more web links to GIF, PNG, JPEG, BMP, or single-page TIFF images. Aspose.OCR for Python via .NET will download them automatically before processing. Limitations: Aspose.OCR for Python via .NET does not support authentication and can only work with public URLs. The URL must point directly to the image. Aspose.OCR for Python via .NET cannot extract images from HTML pages.
`InputType.DIRECTORY`	Absolute or relative paths to one or more folders containing GIF, PNG, JPEG, BMP, or single-page TIFF images. Unless specifically configured, all nested images will be recognized. Subfolders and nested archives will not be processed!
`InputType.ZIP`	Absolute or relative paths to one or more ZIP archives containing GIF, PNG, JPEG, BMP, or single-page TIFF images. Unless specifically configured, all archived images will be recognized. Nested archives and folders will not be processed!
`InputType.BASE64`	One or more GIF, PNG, JPEG, BMP, or single-page TIFF images provided as Base64-encoded strings.

Combination of different content types (for example, images and PDF documents) within one OcrInput object is not supported.

Adding source content

To manage a batch of images, scanned PDFs, URLs, folders, and other OCR content, use the following methods of the OcrInput class:

Method	Purpose
`add(string)`	Adds an absolute or relative path to a file/folder, or a URL to an image file on the web.
`add(string, int, int)`	Adds an absolute or relative path to a multi-page image, PDF document, ZIP archive or folder, specifying the images/pages for recognition.
`add(stream)`	Adds a stream, containing a file to be recognized.
`add(stream, int, int)`	Adds a stream, containing a milti-page image, PDF document, or ZIP archive, specifying the images/pages for recognition.
`add(Color[], int, int)`	Adds an image provided as an array of pixels. You must specify the width and height.
`add(byte[], int, int, PixelType)`	Adds an image provided as an array of pixels. You must specify the width, height and color model.
`add_base64(string)`	Adds an image encoded as Base64 string.

To get the number of items in the batch, use count() method.

Removing source content

To remove all sources from a batch, use clear() method.

Applying image processing filters

The accuracy and reliability of text recognition is highly dependent on the quality of the original image. Aspose.OCR for Python via .NET offers a large number of fully automated and manual image processing filters that enhance an image before it is sent to the OCR engine.

To apply processing filters to all images in the batch, provide them in the OcrInput object constructor, or later using replace_filters() method.

To remove all processing filters from a batch, use clear_filters() method.

Examples

The following code samples demonstrates how to prepare content for recognition:

Provide multiple images

input = OcrInput(InputType.SINGLE_IMAGE)
input.add("page1.png")
input.add("page2.png")

Provide scanned PDF

input = OcrInput(InputType.PDF)
# Recognize pages 2 to 8
input.add("contract.pdf", 1, 7)

Apply processing filters

# Automatically deskew all images
filters = PreprocessingFilter()
filters.add(PreprocessingFilter.auto_skew())
# Prepare batch
input = OcrInput(InputType.SINGLE_IMAGE, filters)
input.add("page1.png")
input.add("page2.png")

Recognition languages