def apply_adjust_gamma(input: torch.Tensor, params: Dict[str, torch.Tensor]) -> torch.Tensor:
r"""Perform gamma correction on an image.
Args:
input (torch.Tensor): Tensor to be transformed with shape :math:`(*, C, H, W)`.
params (Dict[str, torch.Tensor]):
- params['gamma_factor']: Non negative real number, same as γ\gammaγ in the equation.
gamma larger than 1 make the shadows darker, while gamma smaller than 1 make
dark regions lighter.
Returns:
torch.Tensor: Adjusted image with shape :math:`(B, C, H, W)`.
"""
transformed = adjust_gamma(input, params['gamma_factor'].to(input.dtype))
return transformed
def apply_adjust_gamma(input: torch.Tensor, params: Dict[str, torch.Tensor]) -> torch.Tensor:
r"""Perform gamma correction on an image.
Args:
input (torch.Tensor): Tensor to be transformed with shape (H, W), (C, H, W), (B, C, H, W).
params (Dict[str, torch.Tensor]):
- params['gamma_factor']: Non negative real number, same as γ\gammaγ in the equation.
gamma larger than 1 make the shadows darker, while gamma smaller than 1 make
dark regions lighter.
Returns:
torch.Tensor: Adjusted image.
"""
input = _transform_input(input)
_validate_input_dtype(input, accepted_dtypes=[torch.float16, torch.float32, torch.float64])
transformed = adjust_gamma(input, params['gamma_factor'].to(input.dtype))
return transformed