itk

import itk import os # Load a test image (ensure itk.test_data is available or provide your own path) # Example: itk.test_data.dir() + '/BrainProtonDensitySlice.png' # Or download one, e.g., from https://itk.org/Doxygen/html/itkTestingData_2itkTestingData_8h-example.html # For demonstration, we'll try to find a suitable test image try: input_image_path = itk.test_data.dir() + '/BrainProtonDensitySlice.png' except AttributeError: print("itk.test_data not found. Please provide a path to a test image.") # Fallback to a placeholder, won't run without a real image input_image_path = "path/to/your/image.png" if not os.path.exists(input_image_path): # Ensure the path actually exists print(f"Warning: Test image not found at {input_image_path}. Please provide a valid image path to run this example.") # Create a dummy image for the rest of the code to parse if test data isn't there # This part won't execute if os.path.exists is true or real path given image = itk.Image[itk.F, 2].New() image.SetRegions(itk.ImageRegion[2]([0,0], [10,10])) image.Allocate() print("Using a dummy image for processing.") else: # Read the image, specifying the pixel type (itk.F for float) image = itk.imread(input_image_path, itk.F) print(f"Read image with dimensions: {image.GetLargestPossibleRegion().GetSize()} and pixel type: {image.GetPixelID()}')") # Define the image type (float, 2D) for the filter pixel_type = itk.F image_type = itk.Image[pixel_type, 2] # Create a Gaussian filter instance gamma_filter = itk.GammaImageAdaptor[image_type, pixel_type].New() # Set the input image gamma_filter.SetInputImage(image) # Apply a gamma correction (e.g., gamma = 0.5) gamma_filter.SetGamma(0.5) # Update the filter to execute gamma_filter.Update() output_image = gamma_filter.GetOutput() # Write the output image output_file_name = "gamma_corrected_output.png" # Ensure a real image was processed before trying to write if os.path.exists(input_image_path): itk.imwrite(output_image, output_file_name) print(f"Processed image and saved to {output_file_name}") else: print("Skipped writing output because a real input image was not processed.")