Browse our Products

Aspose.OCR for Python via C++ 24.3.0 - Release Notes

This article contains a summary of recent changes, enhancements and bug fixes in Aspose.OCR for Python via C++ 24.3.0 (March 2024) release.

What was changed

Key	Summary	Category
OCRCPP‑575	Receipt recognition.	New feature
OCRCPP‑575	Vehicle registration plate recognition.	New feature
OCRCPP‑574	Automatic detection of image areas where text recognition may be inaccurate or where information may be lost.	New feature
OCRCPP‑579	Logging recognition events to a console or saving them to a file.	New feature
OCRCPP‑584	Multithreading support.	New feature

Public API changes and backwards compatibility

This section lists all public API changes introduced in Aspose.OCR for Python via C++ 24.3.0 that may affect the code of existing applications.

Added public APIs:

The following public APIs have been introduced in Aspose.OCR for Python via C++ 24.3.0 release:

`AsposeOCRRecognizeVehicleLicensePlate()`

Extracts text from a vehicle license plate image. This method also allows you to customize recognition accuracy and other settings.

`AsposeOCRRecognizeReceipt()`

Extracts text from scanned or photographed receipts. This method also allows you to customize recognition accuracy and other settings.

`DefectType` enumeration

Automatically find potentially problematic areas of image during recognition. In order to enable this functionality, specify the type of image defects to be detected in defects property of recognition settings.

The following types of defects can be found:

Defect	Enumeration value	Description	Impact
Salt-and-pepper noise	`DefectType.SALT_PEPPER_NOISE`	Appears as random white and black pixels scattered across the area. Often occurs in digital photographs.	Some characters are misidentified Unnecessary dots or commas appear in recognition results
Low contrast between text and background	`DefectType.DARK_IMAGES`	Highlights and shadows typically appear on curved pages.	Low recognition accuracy Text not recognized (ignored by OCR engine)
Curved text	`DefectType.CURVED_TEXT`	Cylindrical curvature of the page that often appear when photographing pages of books and magazine articles.	Some characters are misidentified Text not recognized
Blur	`DefectType.BLURED_IMAGE`	The entire image or some of its areas are out of focus. Important: This detection algorithm can only identify the entire image as blurry. Specific areas cannot be detected.	Characters are not recognized correctly Text not recognized (ignored by OCR engine)
Glare	`DefectType.GLARE`	Highlight areas in an image caused by uneven lighting, such as spot lights or flash.	Low recognition accuracy Text not recognized (ignored by OCR engine)
Thick text	`DefectType.EXTRA_BOLD_TEXT`	Extra-bold text.	Some characters are misidentified

To detect multiple defects, combine them through the OR bitwise operator:

import asposeocr

settings = asposeocr.RecognitionSettings()
settings.defects = asposeocr.DefectType.SALT_PEPPER_NOISE | asposeocr.DefectType.DARK_IMAGES

`AsposeOCRLogSettings` object

Allows you to configure the global logging parameters:

Property	Description
`console_output_enabled`	Set to `true` to enable the display of recognition progress in the console.
`logging_level`	Specify the log severity. See the description of `LogLevel` enumeration for details.
`output_path`	Specify an absolute or relative path to the log file.

`LogLevel` enumeration

The log severity used as a value of logging_level property:

Value	Description
`ERROR`	Error events of considerable importance that will affect normal program execution.
`WARNING`	Potentially harmful situations that might still allow the application to continue running. The log will also include errors (as if `ERROR` is also specified).
`TRACE`	Detailed trace messages useful for application developers. The log will also include errors and warnings (as if `ERROR` and `WARNING` are specified).

`AsposeOCRSetAllowedThreadNumber()`

Specifies the number of threads used by the recognition engine. By default, recognition is performed on the application’s main thread.

`AsposeOCRGetAllowedThreadNumber()`

Return the number of threads used by the recognition engine.

Updated public APIs:

No changes.

Removed public APIs:

No changes.

Examples

The code samples below illustrate the changes introduced in this release:

Recognize vehicle license place

import asposeocr

''' add image to the recognition batch '''
images = [asposeocr.AsposeOCRInput()]
images[0].url = 'photo.png'

''' recognize the image '''
settings = asposeocr.RecognitionSettings()
recognition_result = asposeocr.AsposeOCRRecognizeVehicleLicensePlate(images, settings)
recognition_text = asposeocr.AsposeOCRSerializeResult(recognition_result, asposeocr.ExportFormat.text)
print(result[0].recognition_text)

Detect low contrast an noisy areas

import asposeocr

''' add image to the recognition batch '''
images = [asposeocr.AsposeOCRInput()]
images[0].url = 'image.png'

''' detect image defects and recognize the image '''
settings = asposeocr.RecognitionSettings()
settings.defects = asposeocr.DefectType.SALT_PEPPER_NOISE | asposeocr.DefectType.DARK_IMAGES
recognition_result = asposeocr.AsposeOCRRecognizeVehicleLicensePlate(images, settings)

Log errors and warnings to console

import asposeocr

log_settings = asposeocr.AsposeOCRLogSettings()
log_settings.logging_level = asposeocr.LogLevel.WARNING

Run recognition on 8 threads

import asposeocr

asposeocr.AsposeOCRSetAllowedThreadNumber(8)