Artifacts

dataphy.visionpack.tforms.artifacts

Classes

JPEGCompress(quality: List[int] = [35, 90], **kwargs: Any)

Bases: BaseTransform

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

def __init__(
    self,
    quality: List[int] = [35, 90],
    **kwargs: Any
):
    super().__init__(**kwargs)
    self.quality_range = quality

Attributes

quality_range = quality 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)

BitDepth(bits: List[int] = [8, 10, 12], **kwargs: Any)

Bases: BaseTransform

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

def __init__(
    self,
    bits: List[int] = [8, 10, 12],
    **kwargs: Any
):
    super().__init__(**kwargs)
    self.bits_options = bits

Attributes

bits_options = bits 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)

Vignette(strength: List[float] = [0.0, 0.3], softness: List[float] = [0.2, 0.7], center_bias_vignette: List[float] = [-0.1, 0.1], **kwargs: Any)

Bases: BaseTransform

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

def __init__(
    self,
    strength: List[float] = [0.0, 0.3],
    softness: List[float] = [0.2, 0.7],
    center_bias_vignette: List[float] = [-0.1, 0.1],
    **kwargs: Any
):
    super().__init__(**kwargs)
    self.strength_range = strength
    self.softness_range = softness
    self.center_bias_range = center_bias_vignette

Attributes

strength_range = strength instance-attribute

softness_range = softness instance-attribute

center_bias_range = center_bias_vignette 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)

LensDistortion(k1: List[float] = [-0.1, 0.1], k2: List[float] = [-0.05, 0.05], crop_or_pad: Literal['crop', 'pad'] = 'crop', **kwargs: Any)

Bases: BaseTransform

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

def __init__(
    self,
    k1: List[float] = [-0.1, 0.1],
    k2: List[float] = [-0.05, 0.05],
    crop_or_pad: Literal["crop", "pad"] = "crop",
    **kwargs: Any
):
    super().__init__(**kwargs)
    self.k1_range = k1
    self.k2_range = k2
    self.crop_or_pad = crop_or_pad

Attributes

k1_range = k1 instance-attribute

k2_range = k2 instance-attribute

crop_or_pad = crop_or_pad 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)