color-operations

import numpy as np from color_operations import operations # Simulate a 3-band RGB image (e.g., 100x100 pixels) # Input arrays are expected to be (bands, rows, columns) and scaled 0-1. image_array = np.random.rand(3, 100, 100).astype(np.float32) # Apply a sigmoidal contrast adjustment # contrast: adjusts the slope of the sigmoid function (higher values mean higher contrast) # bias: shifts the sigmoid function (affects brightness) sigmoidal_adjusted = operations.sigmoidal(image_array, contrast=5, bias=0.5) # Apply gamma correction to brighten midtones (e.g., gamma > 1.0 darkens, < 1.0 brightens) gamma_corrected = operations.gamma(image_array, g=0.8) # Adjust saturation (proportion > 1.0 increases saturation, < 1.0 decreases) saturated_image = operations.saturation(image_array, proportion=1.5) print(f"Original image array shape: {image_array.shape}") print(f"Sigmoidal adjusted image shape: {sigmoidal_adjusted.shape}") print(f"Gamma corrected image shape: {gamma_corrected.shape}") print(f"Saturated image shape: {saturated_image.shape}")