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Aspose.OCR for Python via .NET 25.4.0 - Release Notes
What was changed
| Key | Summary | Category |
|---|---|---|
| OCRNET‑995, OCRNET‑1000 | Added universal recognition of Arabic, Persian and English alphabets. | New feature |
| OCRNET‑1002 | Automatic analysis of image content and detection of layout blocks. | New feature |
| OCRNET‑1001 | Recognition speed improvements. | Enhancement |
| OCRNET‑1006, OCRNET‑1012 | Add markdown output format with document layout. | New feature |
| OCRNET‑1010, OCRNET‑1011 | Automatic language detection during recognition. | New feature |
| OCRNET‑1009 | Docx output format improvements. | Enhancement |
Public API changes and backwards compatibility
This section lists all public API changes introduced in Aspose.OCR for Python via .NET 25.4.0 that may affect the code of existing applications.
Added public APIs:
The following public APIs have been introduced in this release:
aspose.ocr.ContentArea class
This class stores a layout block detected in an image.
| Property | Type | Description |
|---|---|---|
index | int | The sequential index of the content area, unique within the entire image. |
rectangle | aspose.ocr.Rectangle | The bounding rectangle of the content area. |
aspose.ocr.LayoutOutput class
This class stores a layout block detected in an image.
| Property | Type | Description |
|---|---|---|
source | string | The full path to the file or URL, if applicable. Empty for images provided as a stream, byte array, or Base64. |
page | int | Page number for multi-page images. |
paragraphs | Array of ContentArea | Detected paragraphs. |
images | Array of ContentArea | Detected illustrations. |
headers | Array of ContentArea | Detected headers. |
tables | Array of ContentArea | Detected tables. |
lists | Array of ContentArea | Detected lists. |
captions | Array of ContentArea | Detected captions. |
equations | Array of ContentArea | Detected equations. |
aspose.ocr.DetectDocumentLayout method
Analyzes images and identifies the different types of layout blocks within it. This method supports PNG, JPEG, BMP, TIFF, JFIF, and GIF images from files, streams, pixel arrays, and can bulk process folders and archives.
Detected layout blocks are returned as aspose.ocr.LayoutOutput object.
aspose.ocr.LanguageDetectionLevel enumeration
Defines the level of language detection for text recognition in an image:
| Level | Value | Description |
|---|---|---|
| BY_PAGE | aspose.ocr.LanguageDetectionLevel.BY_PAGE | Detects a single language for the entire image. |
| BY_PARAGRAPH | aspose.ocr.LanguageDetectionLevel.BY_PARAGRAPH | Detects the language separately for each paragraph. |
| BY_WORD | aspose.ocr.LanguageDetectionLevel.BY_WORD | Detects the language separately for each word. |
Updated public APIs:
The following public APIs have been updated in Aspose.OCR for .NET 25.4.0 release:
aspose.ocr.Language
Aspose.OCR for .NET can now extract mixed-language texts in Persian, Arabic and English alphabets.Use the following language identifier in recognition settings:
aspose.ocr.Language.PERSO_ARABICaspose.ocr.Language.ISLAMIC
- Universal Persian/Arabic text recognition requires aspose-ocr-arabic-v1 OCR feature to be installed.
aspose.ocr.Language
Aspose.OCR for .NET can now Automatically detects the language in the input document or image. Use the following language identifier in recognition settings:
aspose.ocr.Language.MULTILANGUAGEaspose.ocr.Language.AUTOaspose.ocr.Language.UNIVERSAL
- Universal text recognition and language detection requires aspose-ocr-language-classification-v1 OCR feature to be installed.
aspose.ocr.SaveFormat
Aspose.OCR for .NET can now save the document as a Markdown (.md) file. If aspose.ocr.DetectAreasMode.MULTICOLUMN is used, images will also be extracted.
aspose.ocr.SaveFormat.MD
Removed public APIs:
No changes.
Examples
The code samples below illustrate the changes introduced in this release:
Detect languages on the image
# Instantiate Aspose.OCR API
api = AsposeOcr()
# Add image to the recognition batch
input = OcrInput(InputType.SINGLE_IMAGE)
input.add("source.png")
# Set language detection
set = RecognitionSettings()
set.language = Language.AUTO
set.language_detection_level = LanguageDetectionLevel.BY_WORD
# Detect languages and recognize image
results = api.recognize(input, set)
for result in results:
print(result.recognition_text)
Detect layout on the image
# Instantiate Aspose.OCR API
api = AsposeOcr()
# Add image to the recognition batch
input = OcrInput(InputType.SINGLE_IMAGE)
input.add("source.png")
# Detect layout
results = api.detect_document_layout(input)
# Print result
for result in results:
print("paragraphs:" + str(len(result.paragraphs)))
print("images:" + str(len(result.images)))
print("tables:" + str(len(result.tables)))
print("headers:" + str(len(result.headers)))
print("lists:" + str(len(result.lists)))
print("captions:" + str(len(result.captions)))
print("equations:" + str(len(result.equations)))
# Recognize only headers
# Set rectangles for recognition
set = RecognitionSettings()
set.recognition_areas = [area.rectangle for area in result.headers] # use paragraphs or any other areas
# Recognize areas (rectangles)
results = api.recognize(input, set)
for result in results:
print(result.recognition_text)