Filter Wizard

In case of not knowing which filter should be applied to the image, OcrInputFilterWizard provides the list of filters suitable for OCR input.

Python Code Example

Below is an example of how you might work with the OcrInputFilterWizard in Python. The code demonstrates retrieving and applying the suitable filters for an image preprocessing task relevant to Optical Character Recognition (OCR).

# Import necessary libraries
from ocr_filter_wizard import OcrInputFilterWizard
from PIL import Image

def apply_ocr_filters(image_path):
    """
    This function uses OcrInputFilterWizard to obtain suitable filters for OCR 
    and apply them to the given image.

    :param image_path: str, Path to the image to be processed
    """
    # Open the image file
    image = Image.open(image_path)

    # Create an instance of OcrInputFilterWizard
    filter_wizard = OcrInputFilterWizard()

    # Retrieve suitable filters for OCR input
    filters = filter_wizard.get_suitable_filters()

    # Apply each filter in the list to the image
    for filter_function in filters:
        image = filter_function(image)

    # Save or process the filtered image further as needed
    # For demonstration, we save the processed image
    image.save('processed_image.png')
    print("Image processing complete. Processed image saved as 'processed_image.png'.")

# Example usage of the function
apply_ocr_filters('input_image.png')

# Import necessary libraries
from ocr_filter_wizard import OcrInputFilterWizard
from PIL import Image

def apply_ocr_filters(image_path):
    """
    This function uses OcrInputFilterWizard to obtain suitable filters for OCR 
    and apply them to the given image.

    :param image_path: str, Path to the image to be processed
    """
    # Open the image file
    image = Image.open(image_path)

    # Create an instance of OcrInputFilterWizard
    filter_wizard = OcrInputFilterWizard()

    # Retrieve suitable filters for OCR input
    filters = filter_wizard.get_suitable_filters()

    # Apply each filter in the list to the image
    for filter_function in filters:
        image = filter_function(image)

    # Save or process the filtered image further as needed
    # For demonstration, we save the processed image
    image.save('processed_image.png')
    print("Image processing complete. Processed image saved as 'processed_image.png'.")

# Example usage of the function
apply_ocr_filters('input_image.png')

Explanation

• Import Libraries: The code starts by importing necessary libraries: ocr_filter_wizard for OCR filter handling, and PIL.Image to work with image files.
• open_image: Utilizing the Image.open() routine from the PIL library to load an image from the specified image_path.
• Filter Wizard Instantiation: Instantiate OcrInputFilterWizard to facilitate the retrieval of appropriate filters for OCR processing.
• Retrieve Filters: Use get_suitable_filters() method of the wizard instance to get a list of filters suitable for OCR. These filters are assumed to be functions that process images.
• Apply Filters: Loop over each filter and sequentially apply it to the image. The assumption here is that each filter is a callable that modifies and returns an image object.
• Save Processed Image: Once all filters have been applied, the processed image is saved using the image.save() method. This can be modified to suit further processing or alternative handling of the filtered image.

Keep in mind to replace 'ocr_filter_wizard' and 'OcrInputFilterWizard' with the correct module and class name you have in your application if these do not exist or differ.

Error Handling

For robustness, it is essential to add error handling in real-world applications. For instance, ensure the provided image path is valid, the image file format supported, and potentially catch exceptions for each filter application step.