Lighting And Color Transformation

via “photometric augmentation with color space awareness”

Fast, flexible, and advanced augmentation library for deep learning, computer vision, and medical imaging. Albumentations offers a wide range of transformations for both 2D (images, masks, bboxes, keypoints) and 3D (volumes, volumetric masks, keypoints) data, with optimized performance and seamless

Unique: Automatically handles color space conversions (RGB↔HSV, RGB↔LAB) for color-aware transforms, applying operations in perceptually appropriate spaces and converting back without artifacts; supports both uint8 and float32 images with automatic range handling

vs others: More robust than channel-wise color augmentation because it respects color space semantics; more efficient than manual color space conversion because it caches conversions and applies multiple transforms in a single pass

via “lighting-and-color-transformation”

via “lighting-atmosphere-control”

via “color-palette-transformation”

via “lighting and environment customization”

via “adaptive product relighting”

via “lighting-and-environment-adjustment”

via “lighting simulation and adjustment”

via “lighting-simulation-and-preview”

via “lighting-scenario-visualization”