Color

dataphy.visionpack.tforms.color

Classes

ColorJitter(magnitude: Optional[float] = None, brightness: Optional[float] = None, contrast: Optional[float] = None, saturation: Optional[float] = None, hue: Optional[float] = None, order: Optional[List[str]] = None, space: Literal['rgb', 'hsv', 'hsl'] = 'rgb', preserve_robot_color: bool = False, clip_range: Optional[List[float]] = None, gamma: Optional[float] = None, temperature_shift: Optional[float] = None, correlate_views: float = 0.0, **kwargs: Any)

Bases: BaseTransform

Color jittering transform for image augmentation.

This transform applies random color adjustments to images, including brightness, contrast, saturation, and hue changes. It supports multiple color spaces and can preserve robot colors in robotics datasets.

Parameters:

Name	Type	Description	Default
magnitude	Optional[float]	Global magnitude for all color adjustments (overrides individual params)	None
brightness	Optional[float]	Brightness adjustment range	None
contrast	Optional[float]	Contrast adjustment range	None
saturation	Optional[float]	Saturation adjustment range	None
hue	Optional[float]	Hue adjustment range	None
order	Optional[List[str]]	Order of color operations to apply	None
space	Literal['rgb', 'hsv', 'hsl']	Color space to work in ("rgb", "hsv", "hsl")	'rgb'
preserve_robot_color	bool	Whether to preserve robot colors using masks	False
clip_range	Optional[List[float]]	Range to clip output values	None
gamma	Optional[float]	Gamma correction value	None
temperature_shift	Optional[float]	Color temperature shift	None
correlate_views	float	Probability of using correlated parameters across views	0.0
**kwargs	Any	Additional base transform parameters	{}

Source code in src/dataphy/visionpack/tforms/color.py

def __init__(
    self,
    magnitude: Optional[float] = None,
    brightness: Optional[float] = None,
    contrast: Optional[float] = None,
    saturation: Optional[float] = None,
    hue: Optional[float] = None,
    order: Optional[List[str]] = None,
    space: Literal["rgb", "hsv", "hsl"] = "rgb",
    preserve_robot_color: bool = False,
    clip_range: Optional[List[float]] = None,
    gamma: Optional[float] = None,
    temperature_shift: Optional[float] = None,
    correlate_views: float = 0.0,
    **kwargs: Any
):
    """Initialize the ColorJitter transform.

    Args:
        magnitude: Global magnitude for all color adjustments (overrides individual params)
        brightness: Brightness adjustment range
        contrast: Contrast adjustment range
        saturation: Saturation adjustment range
        hue: Hue adjustment range
        order: Order of color operations to apply
        space: Color space to work in ("rgb", "hsv", "hsl")
        preserve_robot_color: Whether to preserve robot colors using masks
        clip_range: Range to clip output values
        gamma: Gamma correction value
        temperature_shift: Color temperature shift
        correlate_views: Probability of using correlated parameters across views
        **kwargs: Additional base transform parameters
    """
    super().__init__(**kwargs)  # type: ignore

    # Use individual parameters if provided, otherwise fall back to magnitude
    if magnitude is not None and all(x is None for x in [brightness, contrast, saturation, hue]):
        self.brightness = magnitude
        self.contrast = magnitude
        self.saturation = magnitude
        self.hue = magnitude
    else:
        self.brightness = brightness or 0.0
        self.contrast = contrast or 0.0
        self.saturation = saturation or 0.0
        self.hue = hue or 0.0

    self.order = order or ["brightness", "contrast", "saturation", "hue"]
    self.space = space
    self.preserve_robot_color = preserve_robot_color
    self.clip_range = clip_range or [0.0, 1.0]
    self.gamma = gamma
    self.temperature_shift = temperature_shift
    self.correlate_views = correlate_views

    # Store correlated parameters for multi-view consistency
    self._correlated_params = {}
    self._last_episode_id = None

Attributes

brightness = magnitude instance-attribute

contrast = magnitude instance-attribute

saturation = magnitude instance-attribute

hue = magnitude instance-attribute

order = order or ['brightness', 'contrast', 'saturation', 'hue'] instance-attribute

space = space instance-attribute

preserve_robot_color = preserve_robot_color instance-attribute

clip_range = clip_range or [0.0, 1.0] instance-attribute

gamma = gamma instance-attribute

temperature_shift = temperature_shift instance-attribute

correlate_views = correlate_views instance-attribute

p = p instance-attribute

apply_to = apply_to if apply_to is not None else ['rgb'] instance-attribute

sync_views = sync_views instance-attribute

update_intrinsics = update_intrinsics instance-attribute

mask_protect = mask_protect if mask_protect is not None else [] instance-attribute

min_visible_mask_pct = min_visible_mask_pct instance-attribute

resample = resample instance-attribute

border_mode = border_mode instance-attribute

pad_mode = pad_mode instance-attribute

pad_value = pad_value instance-attribute

seed_policy = seed_policy instance-attribute

Functions

forward(batch: Dict[str, Any]) -> Dict[str, Any]

Base forward method that handles cross-cutting logic.

Source code in src/dataphy/visionpack/tforms/base.py

def forward(self, batch: Dict[str, Any]) -> Dict[str, Any]:
    """Base forward method that handles cross-cutting logic."""
    if not self._should_apply():
        return batch

    # Setup seed policy
    episode_id = batch.get("episode_id")
    self._setup_seed(episode_id)

    # Apply transform
    return self._apply_transform(batch)