kornia.color¶

The functions in this section perform various color space conversions.

rgb_to_bgr(image: torch.Tensor) → torch.Tensor[source]¶

Convert a RGB image to BGR.

Parameters: image (torch.Tensor) – RGB Image to be converted to BGRof of shape \((*,3,H,W)\).
Returns: BGR version of the image with shape of shape \((*,3,H,W)\).
Return type: torch.Tensor

Example

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

rgb_to_grayscale(image: torch.Tensor, rgb_weights: torch.Tensor = tensor([0.2990, 0.5870, 0.1140])) → torch.Tensor[source]¶

Convert a RGB image to grayscale version of image.

The image data is assumed to be in the range of (0, 1).

Parameters

image (torch.Tensor) – RGB image to be converted to grayscale with shape \((*,3,H,W)\).
rgb_weights (torch.Tensor) – Weights that will be applied on each channel (RGB). The sum of the weights should add up to one.

Returns

grayscale version of the image with shape \((*,1,H,W)\).

Return type

torch.Tensor

Example

>>> input = torch.rand(2, 3, 4, 5)
>>> gray = rgb_to_grayscale(input) # 2x1x4x5

rgb_to_hsv(image: torch.Tensor, eps: float = 1e-06) → torch.Tensor[source]¶

Convert an image from RGB to HSV.

The image data is assumed to be in the range of (0, 1).

Parameters

image (torch.Tensor) – RGB Image to be converted to HSV with shape of \((*, 3, H, W)\).
eps (float, optional) – scalar to enforce numarical stability. Default: 1e-6.

Returns

HSV version of the image with shape of \((*, 3, H, W)\).

Return type

torch.Tensor

Example

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

rgb_to_hls(image: torch.Tensor) → torch.Tensor[source]¶

Convert a RGB image to HLS.

The image data is assumed to be in the range of (0, 1).

Parameters: image (torch.Tensor) – RGB image to be converted to HLS with shape \((*, 3, H, W)\).
Returns: HLS version of the image with shape \((*, 3, H, W)\).
Return type: torch.Tensor

Example

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

rgb_to_luv(image: torch.Tensor, eps: float = 1e-12) → torch.Tensor[source]¶

Converts a RGB image to Luv.

The image data is assumed to be in the range of \([0, 1]\). Luv color is computed using the D65 illuminant and Observer 2.

Parameters

image (torch.Tensor) – RGB Image to be converted to Luv with shape \((*, 3, H, W)\).
eps (float) – for numerically stability when dividing. Default: 1e-12.

Returns

Luv version of the image with shape \((*, 3, H, W)\).

Return type

torch.Tensor

Example

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

rgb_to_lab(image: torch.Tensor) → torch.Tensor[source]¶

Converts a RGB image to Lab.

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

Parameters: image (torch.Tensor) – RGB Image to be converted to Lab with shape \((*, 3, H, W)\).
Returns: Lab version of the image with shape \((*, 3, H, W)\).
Return type: torch.Tensor

Example

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

rgb_to_rgba(image: torch.Tensor, alpha_val: Union[float, torch.Tensor]) → torch.Tensor[source]¶

Convert an image from RGB to RGBA.

Parameters

image (torch.Tensor) – RGB Image to be converted to RGBA of shape \((*,3,H,W)\).
alpha_val (float, torch.Tensor) – A float number for the alpha value or a tensor of shape \((*,1,H,W)\).

Returns

RGBA version of the image with shape \((*,4,H,W)\).

Return type

torch.Tensor

Note

The current functionality is NOT supported by Torchscript.

Example

>>> input = torch.rand(2, 3, 4, 5)
>>> output = rgb_to_rgba(input, 1.) # 2x4x4x5

rgb_to_xyz(image: torch.Tensor) → torch.Tensor[source]¶

Converts a RGB image to XYZ.

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

Example

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

rgb_to_ycbcr(image: torch.Tensor) → torch.Tensor[source]¶

Convert an RGB image to YCbCr.

Parameters: image (torch.Tensor) – RGB Image to be converted to YCbCr with shape \((*, 3, H, W)\).
Returns: YCbCr version of the image with shape \((*, 3, H, W)\).
Return type: torch.Tensor

Examples

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

rgb_to_yuv(image: torch.Tensor) → torch.Tensor[source]¶

Convert an RGB image to YUV.

The image data is assumed to be in the range of (0, 1).

Parameters: image (torch.Tensor) – RGB Image to be converted to YUV with shape \((*, 3, H, W)\).
Returns: YUV version of the image with shape \((*, 3, H, W)\).
Return type: torch.Tensor

Example

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

rgb_to_linear_rgb(image: torch.Tensor) → torch.Tensor[source]¶

Convert an sRGB image to linear RGB. Used in colorspace conversions.

Parameters: image (torch.Tensor) – sRGB Image to be converted to linear RGB of shape \((*,3,H,W)\).
Returns: linear RGB version of the image with shape of \((*,3,H,W)\).
Return type: torch.Tensor

Example

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

linear_rgb_to_rgb(image: torch.Tensor) → torch.Tensor[source]¶

Convert a linear RGB image to sRGB. Used in colorspace conversions.

Parameters: image (torch.Tensor) – linear RGB Image to be converted to sRGB of shape \((*,3,H,W)\).
Returns: sRGB version of the image with shape of shape \((*,3,H,W)\).
Return type: torch.Tensor

Example

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

rgba_to_rgb(image: torch.Tensor) → torch.Tensor[source]¶

Convert an image from RGBA to RGB.

Parameters: image (torch.Tensor) – RGBA Image to be converted to RGB of shape \((*,4,H,W)\).
Returns: RGB version of the image with shape \((*,3,H,W)\).
Return type: torch.Tensor

Example

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

rgba_to_bgr(image: torch.Tensor) → torch.Tensor[source]¶

Convert an image from RGBA to BGR.

Parameters: image (torch.Tensor) – RGBA Image to be converted to BGR of shape \((*,4,H,W)\).
Returns: RGB version of the image with shape \((*,3,H,W)\).
Return type: torch.Tensor

Example

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

bgr_to_grayscale(image: torch.Tensor) → torch.Tensor[source]¶

Convert a BGR image to grayscale.

The image data is assumed to be in the range of (0, 1). First flips to RGB, then converts.

Parameters: image (torch.Tensor) – BGR image to be converted to grayscale with shape \((*,3,H,W)\).
Returns: grayscale version of the image with shape \((*,1,H,W)\).
Return type: torch.Tensor

Example

>>> input = torch.rand(2, 3, 4, 5)
>>> gray = bgr_to_grayscale(input) # 2x1x4x5

bgr_to_rgb(image: torch.Tensor) → torch.Tensor[source]¶

Convert a BGR image to RGB.

Parameters: image (torch.Tensor) – BGR Image to be converted to BGR of shape \((*,3,H,W)\).
Returns: RGB version of the image with shape of shape \((*,3,H,W)\).
Return type: torch.Tensor

Example

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

bgr_to_rgba(image: torch.Tensor, alpha_val: Union[float, torch.Tensor]) → torch.Tensor[source]¶

Convert an image from BGR to RGBA.

Parameters

image (torch.Tensor) – BGR Image to be converted to RGBA of shape \((*,3,H,W)\).
alpha_val (float, torch.Tensor) – A float number for the alpha value or a tensor of shape \((*,1,H,W)\).

Returns

RGBA version of the image with shape \((*,4,H,W)\).

Return type

torch.Tensor

Note

The current functionality is NOT supported by Torchscript.

Example

>>> input = torch.rand(2, 3, 4, 5)
>>> output = bgr_to_rgba(input, 1.) # 2x4x4x5

hls_to_rgb(image: torch.Tensor) → torch.Tensor[source]¶

Convert a HLS image to RGB.

The image data is assumed to be in the range of (0, 1).

Parameters: image (torch.Tensor) – HLS image to be converted to RGB with shape \((*, 3, H, W)\).
Returns: RGB version of the image with shape \((*, 3, H, W)\).
Return type: torch.Tensor

Example

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

hsv_to_rgb(image: torch.Tensor) → torch.Tensor[source]¶

Convert an image from HSV to RGB.

The image data is assumed to be in the range of (0, 1).

Parameters: image (torch.Tensor) – HSV Image to be converted to HSV with shape of \((*, 3, H, W)\).
Returns: RGB version of the image with shape of \((*, 3, H, W)\).
Return type: torch.Tensor

Example

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

lab_to_rgb(image: torch.Tensor, clip: bool = True) → torch.Tensor[source]¶

Converts a Lab image to RGB.

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 \([0, 1]\). Default is True

Returns

Lab version of the image with shape \((*, 3, H, W)\).

Return type

torch.Tensor

Example

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

luv_to_rgb(image: torch.Tensor, eps: float = 1e-12) → torch.Tensor[source]¶

Converts a Luv image to RGB.

Parameters

image (torch.Tensor) – Luv image to be converted to RGB with shape \((*, 3, H, W)\).
eps (float) – for numerically stability when dividing. Default: 1e-12.

Returns

Luv version of the image with shape \((*, 3, H, W)\).

Return type

torch.Tensor

Example

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

ycbcr_to_rgb(image: torch.Tensor) → torch.Tensor[source]¶

Convert an YCbCr image to RGB.

The image data is assumed to be in the range of (0, 1).

Parameters: image (torch.Tensor) – YCbCr Image to be converted to RGB with shape \((*, 3, H, W)\).
Returns: RGB version of the image with shape \((*, 3, H, W)\).
Return type: torch.Tensor

Examples

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

yuv_to_rgb(image: torch.Tensor) → torch.Tensor[source]¶

Convert an YUV image to RGB.

The image data is assumed to be in the range of (0, 1).

Parameters: image (torch.Tensor) – YUV Image to be converted to RGB with shape \((*, 3, H, W)\).
Returns: RGB version of the image with shape \((*, 3, H, W)\).
Return type: torch.Tensor

Example

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

xyz_to_rgb(image: torch.Tensor) → torch.Tensor[source]¶

Converts a XYZ image to RGB.

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

Example

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

Modules¶

class RgbToGrayscale(rgb_weights: torch.Tensor = tensor([0.2990, 0.5870, 0.1140]))[source]¶

Module to convert a RGB image to grayscale version of image.

The image data is assumed to be in the range of (0, 1).

Shape:

image: \((*, 3, H, W)\)
output: \((*, 1, H, W)\)

reference:

https://docs.opencv.org/4.0.1/de/d25/imgproc_color_conversions.html

Example

>>> input = torch.rand(2, 3, 4, 5)
>>> gray = RgbToGrayscale()
>>> output = gray(input)  # 2x1x4x5

class BgrToGrayscale[source]¶

Module to convert a BGR image to grayscale version of image.

The image data is assumed to be in the range of (0, 1). First flips to RGB, then converts.

Shape:

image: \((*, 3, H, W)\)
output: \((*, 1, H, W)\)

reference:

https://docs.opencv.org/4.0.1/de/d25/imgproc_color_conversions.html

Example

>>> input = torch.rand(2, 3, 4, 5)
>>> gray = BgrToGrayscale()
>>> output = gray(input)  # 2x1x4x5

class RgbToHsv(eps: float = 1e-06)[source]¶

Convert an image from RGB to HSV.

The image data is assumed to be in the range of (0, 1).

Parameters: eps (float, optional) – scalar to enforce numarical stability. Default: 1e-6.
Returns: HSV version of the image.
Return type: torch.tensor

Shape:

image: \((*, 3, H, W)\)
output: \((*, 3, H, W)\)

Example

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

class HsvToRgb[source]¶

Convert an image from HSV to RGB.

The image data is assumed to be in the range of (0, 1).

Returns: RGB version of the image.
Return type: torch.Tensor

Shape:

image: \((*, 3, H, W)\)
output: \((*, 3, H, W)\)

Example

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

class RgbToHls[source]¶

Convert an image from RGB to HLS.

The image data is assumed to be in the range of (0, 1).

Returns: HLS version of the image.
Return type: torch.Tensor

Shape:

image: \((*, 3, H, W)\)
output: \((*, 3, H, W)\)

Examples

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

class HlsToRgb[source]¶

Convert an image from HLS to RGB.

The image data is assumed to be in the range of (0, 1).

Returns: RGB version of the image.
Return type: torch.Tensor

Shape:

input: \((*, 3, H, W)\)
output: \((*, 3, H, W)\)

Reference:

https://en.wikipedia.org/wiki/HSL_and_HSV

Examples

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

class RgbToBgr[source]¶

Convert an image from RGB to BGR.

The image data is assumed to be in the range of (0, 1).

Returns: BGR version of the image.
Return type: torch.Tensor

Shape:

image: \((*, 3, H, W)\)
output: \((*, 3, H, W)\)

Example

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

class BgrToRgb[source]¶

Convert image from BGR to RGB.

The image data is assumed to be in the range of (0, 1).

Returns: RGB version of the image.
Return type: torch.Tensor

Shape:

image: \((*, 3, H, W)\)
output: \((*, 3, H, W)\)

Example

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

class RgbToYuv[source]¶

Convert an image from RGB to YUV.

The image data is assumed to be in the range of (0, 1).

Returns: YUV version of the image.
Return type: torch.Tensor

Shape:

image: \((*, 3, H, W)\)
output: \((*, 3, H, W)\)

Examples

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

Reference::: [1] https://es.wikipedia.org/wiki/YUV#RGB_a_Y’UV

class YuvToRgb[source]¶

Convert an image from YUV to RGB.

The image data is assumed to be in the range of (0, 1).

Returns: RGB version of the image.
Return type: torch.Tensor

Shape:

image: \((*, 3, H, W)\)
output: \((*, 3, H, W)\)

Examples

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

class RgbToRgba(alpha_val: Union[float, torch.Tensor])[source]¶

Convert an image from RGB to RGBA.

Add an alpha channel to existing RGB image.

Parameters: alpha_val (float, torch.Tensor) – A float number for the alpha value or a tensor of shape \((*,1,H,W)\).
Returns: RGBA version of the image with shape \((*,4,H,W)\).
Return type: torch.Tensor

Shape:

image: \((*, 3, H, W)\)
output: \((*, 4, H, W)\)

Note

The current functionality is NOT supported by Torchscript.

Example

>>> input = torch.rand(2, 3, 4, 5)
>>> rgba = RgbToRgba(1.)
>>> output = rgba(input)  # 2x4x4x5

class BgrToRgba(alpha_val: Union[float, torch.Tensor])[source]¶

Convert an image from BGR to RGBA.

Add an alpha channel to existing RGB image.

Parameters: alpha_val (float, torch.Tensor) – A float number for the alpha value or a tensor of shape \((*,1,H,W)\).
Returns: RGBA version of the image with shape \((*,4,H,W)\).
Return type: torch.Tensor

Shape:

image: \((*, 3, H, W)\)
output: \((*, 4, H, W)\)

Note

The current functionality is NOT supported by Torchscript.

Example

>>> input = torch.rand(2, 3, 4, 5)
>>> rgba = BgrToRgba(1.)
>>> output = rgba(input)  # 2x4x4x5

class RgbaToRgb[source]¶

Convert an image from RGBA to RGB.

Remove an alpha channel from RGB image.

Returns: RGB version of the image.
Return type: torch.Tensor

Shape:

image: \((*, 4, H, W)\)
output: \((*, 3, H, W)\)

Example

>>> input = torch.rand(2, 4, 4, 5)
>>> rgba = RgbaToRgb()
>>> output = rgba(input)  # 2x3x4x5

class RgbaToBgr[source]¶

Convert an image from RGBA to BGR.

Remove an alpha channel from BGR image.

Returns: BGR version of the image.
Return type: torch.Tensor

Shape:

image: \((*, 4, H, W)\)
output: \((*, 3, H, W)\)

Example

>>> input = torch.rand(2, 4, 4, 5)
>>> rgba = RgbaToBgr()
>>> output = rgba(input)  # 2x3x4x5

class RgbToXyz[source]¶

Converts an image from RGB to XYZ.

The image data is assumed to be in the range of (0, 1).

Returns: XYZ version of the image.
Return type: torch.Tensor

Shape:

image: \((*, 3, H, W)\)
output: \((*, 3, H, W)\)

Examples

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

Reference:: [1] https://docs.opencv.org/4.0.1/de/d25/imgproc_color_conversions.html

class XyzToRgb[source]¶

Converts an image from XYZ to RGB.

Returns: RGB version of the image.
Return type: torch.Tensor

Shape:

image: \((*, 3, H, W)\)
output: \((*, 3, H, W)\)

Examples

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

Reference:: [1] https://docs.opencv.org/4.0.1/de/d25/imgproc_color_conversions.html

class RgbToLuv[source]¶

Converts an image from RGB to Luv.

The image data is assumed to be in the range of \([0, 1]\). Luv color is computed using the D65 illuminant and Observer 2.

Returns: Luv version of the image.
Return type: torch.Tensor

Shape:

image: \((*, 3, H, W)\)
output: \((*, 3, H, W)\)

Examples

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

Reference:

[1] https://docs.opencv.org/4.0.1/de/d25/imgproc_color_conversions.html

[2] https://www.easyrgb.com/en/math.php

[3] http://www.poynton.com/ColorFAQ.html

class LuvToRgb[source]¶

Converts an image from Luv to RGB.

Returns: RGB version of the image.
Return type: torch.Tensor

Shape:

image: \((*, 3, H, W)\)
output: \((*, 3, H, W)\)

Examples

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

References

[1] https://docs.opencv.org/4.0.1/de/d25/imgproc_color_conversions.html

[2] https://www.easyrgb.com/en/math.php

[3] http://www.poynton.com/ColorFAQ.html

class YcbcrToRgb[source]¶

Convert an image from YCbCr to Rgb.

The image data is assumed to be in the range of (0, 1).

Returns: RGB version of the image.
Return type: torch.Tensor

Shape:

image: \((*, 3, H, W)\)
output: \((*, 3, H, W)\)

Examples

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

class RgbToYcbcr[source]¶

Convert an image from RGB to YCbCr.

The image data is assumed to be in the range of (0, 1).

Returns: YCbCr version of the image.
Return type: torch.Tensor

Shape:

image: \((*, 3, H, W)\)
output: \((*, 3, H, W)\)

Examples

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

class RgbToLab[source]¶

Converts an image from RGB to Lab.

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

Returns: Lab version of the image.
Return type: torch.Tensor

Shape:

image: \((*, 3, H, W)\)
output: \((*, 3, H, W)\)

Examples

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

Reference:

[1] https://docs.opencv.org/4.0.1/de/d25/imgproc_color_conversions.html

[2] https://www.easyrgb.com/en/math.php

[3] https://github.com/torch/image/blob/dc061b98fb7e946e00034a5fc73e883a299edc7f/generic/image.c#L1467

class LabToRgb[source]¶

Converts an image from Lab to RGB.

Returns: RGB version of the image. Range may not be in \([0, 1]\).
Return type: torch.Tensor

Shape:

image: \((*, 3, H, W)\)
output: \((*, 3, H, W)\)

Examples

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

References

[1] https://docs.opencv.org/4.0.1/de/d25/imgproc_color_conversions.html

[2] https://www.easyrgb.com/en/math.php

[3] https://github.com/torch/image/blob/dc061b98fb7e946e00034a5fc73e883a299edc7f/generic/image.c#L1518

class LinearRgbToRgb[source]¶

Convert a linear RGB image to sRGB.

Applies gamma correction to linear RGB values, at the end of colorspace conversions, to get sRGB.

Returns: sRGB version of the image.
Return type: torch.Tensor

Shape:

image: \((*, 3, H, W)\)
output: \((*, 3, H, W)\)

Example

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

References

[1] https://stackoverflow.com/questions/35952564/convert-rgb-to-srgb

[2] https://www.cambridgeincolour.com/tutorials/gamma-correction.htm

[3] https://en.wikipedia.org/wiki/SRGB

class RgbToLinearRgb[source]¶

Convert an image from sRGB to linear RGB.

Reverses the gamma correction of sRGB to get linear RGB values for colorspace conversions. The image data is assumed to be in the range of \([0, 1]\)

Returns: Linear RGB version of the image.
Return type: torch.Tensor

Shape:

image: \((*, 3, H, W)\)
output: \((*, 3, H, W)\)

Example

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

References

[1] https://stackoverflow.com/questions/35952564/convert-rgb-to-srgb

[2] https://www.cambridgeincolour.com/tutorials/gamma-correction.htm

[3] https://en.wikipedia.org/wiki/SRGB