spandrel_extra_arches.architectures.DDColor._

module documentation

(source)

Undocumented

def lab_to_linear_rgb(image: torch.Tensor, clip: bool = True) -> torch.Tensor: (source) ¶

Convert a Lab image to RGB.

The L channel is assumed to be in the range of [0, 100]. a and b channels are in the range of [ − 128, 127].

Example

>>> input = torch.rand(2, 3, 4, 5)
>>> output = lab_to_rgb(input)  # 2x3x4x5

Parameters
image:`torch.Tensor`	Lab image to be converted to RGB with shape (*, 3, H, W).
clip:`bool`	Whether to apply clipping to insure output RGB values in range [0, 1].
Returns
`torch.Tensor`	Lab version of the image with shape (*, 3, H, W). The output RGB image are in the range of [0, 1].

def lab_to_rgb(image: torch.Tensor, clip: bool = True) -> torch.Tensor: (source) ¶

Undocumented

def linear_rgb_to_lab(image: torch.Tensor) -> torch.Tensor: (source) ¶

Convert a RGB image to Lab.

The input RGB image is assumed to be in the range of [0, 1]. Lab color is computed using the D65 illuminant and Observer 2.

Example

>>> input = torch.rand(2, 3, 4, 5)
>>> output = rgb_to_lab(input)  # 2x3x4x5

Parameters
image:`torch.Tensor`	RGB Image to be converted to Lab with shape (*, 3, H, W).
Returns
`torch.Tensor`	Lab version of the image with shape (*, 3, H, W). The L channel values are in the range 0..100. a and b are in the range -128..127.

def linear_rgb_to_rgb(image: torch.Tensor) -> torch.Tensor: (source) ¶

Undocumented

def linear_rgb_to_xyz(image: torch.Tensor) -> torch.Tensor: (source) ¶

Convert a RGB image to XYZ.

Example

>>> input = torch.rand(2, 3, 4, 5)
>>> output = rgb_to_xyz(input)  # 2x3x4x5

Parameters
image:`torch.Tensor`	RGB Image to be converted to XYZ with shape (*, 3, H, W).
Returns
`torch.Tensor`	XYZ version of the image with shape (*, 3, H, W).

def rgb_to_lab(image: torch.Tensor) -> torch.Tensor: (source) ¶

Undocumented

def rgb_to_linear_rgb(image: torch.Tensor) -> torch.Tensor: (source) ¶

Undocumented

def xyz_to_linear_rgb(image: torch.Tensor) -> torch.Tensor: (source) ¶

Convert a XYZ image to RGB.

Example

>>> input = torch.rand(2, 3, 4, 5)
>>> output = xyz_to_rgb(input)  # 2x3x4x5

Parameters
image:`torch.Tensor`	XYZ Image to be converted to RGB with shape (*, 3, H, W).
Returns
`torch.Tensor`	RGB version of the image with shape (*, 3, H, W).

spandrel_extra_arches.architectures.DDColor.__color