RGB#

Functions#

kornia.color.rgb_to_bgr(image)[source]#

Convert a RGB image to BGR.

_images/rgb_to_bgr.png
Parameters:

image (Tensor) – RGB Image to be converted to BGRof of shape \((*,3,H,W)\).

Return type:

Tensor

Returns:

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

Example

>>> input = torch.rand(2, 3, 4, 5)
>>> output = rgb_to_bgr(input) # 2x3x4x5
kornia.color.rgb_to_rgb255(image)[source]#

Convert an image from RGB to RGB [0, 255] for visualization purposes.

Parameters:

image (Tensor) – RGB Image to be converted to RGB [0, 255] of shape \((*,3,H,W)\).

Return type:

Tensor

Returns:

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

Example

>>> input = torch.rand(2, 3, 4, 5)
>>> output = rgb_to_rgb255(input) # 2x3x4x5
kornia.color.rgb255_to_rgb(image)[source]#

Convert an image from RGB [0, 255] to RGB for visualization purposes.

Parameters:

image (Tensor) – RGB Image to be converted to RGB of shape \((*,3,H,W)\).

Return type:

Tensor

Returns:

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

Example

>>> input = torch.rand(2, 3, 4, 5)
>>> output = rgb255_to_rgb(input) # 2x3x4x5
kornia.color.rgb255_to_normals(image)[source]#

Convert an image from RGB [0, 255] to surface normals for visualization purposes.

Parameters:

image (Tensor) – RGB Image to be converted to surface normals of shape \((*,3,H,W)\).

Return type:

Tensor

Returns:

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

Example

>>> input = torch.rand(2, 3, 4, 5)
>>> output = rgb255_to_normals(input) # 2x3x4x5
kornia.color.normals_to_rgb255(image)[source]#

Convert surface normals to RGB [0, 255] for visualization purposes.

Parameters:

image (Tensor) – surface normals to be converted to RGB with quantization of shape \((*,3,H,W)\).

Return type:

Tensor

Returns:

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

Example

>>> input = torch.rand(2, 3, 4, 5)
>>> output = normals_to_rgb255(input) # 2x3x4x5

Modules#

class kornia.color.RgbToBgr(*args, **kwargs)[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.

Shape:
  • image: \((*, 3, H, W)\)

  • output: \((*, 3, H, W)\)

Example

>>> input = torch.rand(2, 3, 4, 5)
>>> bgr = RgbToBgr()
>>> output = bgr(input)  # 2x3x4x5
class kornia.color.RgbToRgb255(*args, **kwargs)[source]#

Convert an image from RGB to RGB [0, 255] for visualization purposes.

Returns:

RGB version of the image.

Shape:
  • image: \((*, 3, H, W)\)

  • output: \((*, 3, H, W)\)

Example

>>> input = torch.rand(2, 3, 4, 5)
>>> rgb = RgbToRgb255()
>>> output = rgb(input)  # 2x3x4x5
class kornia.color.Rgb255ToRgb(*args, **kwargs)[source]#

Convert an image from RGB [0, 255] to RGB for visualization purposes.

Returns:

RGB version of the image.

Shape:
  • image: \((*, 3, H, W)\)

  • output: \((*, 3, H, W)\)

Example

>>> input = torch.rand(2, 3, 4, 5)
>>> rgb = Rgb255ToRgb()
>>> output = rgb(input)  # 2x3x4x5
class kornia.color.Rgb255ToNormals(*args, **kwargs)[source]#

Convert an image from RGB [0, 255] to surface normals for visualization purposes.

Returns:

surface normals version of the image.

Shape:
  • image: \((*, 3, H, W)\)

  • output: \((*, 3, H, W)\)

Example

>>> input = torch.rand(2, 3, 4, 5)
>>> normals = Rgb255ToNormals()
>>> output = normals(input)  # 2x3x4x5
class kornia.color.NormalsToRgb255(*args, **kwargs)[source]#

Convert surface normals to RGB [0, 255] for visualization purposes.

Returns:

RGB version of the image.

Shape:
  • image: \((*, 3, H, W)\)

  • output: \((*, 3, H, W)\)

Example

>>> input = torch.rand(2, 3, 4, 5)
>>> rgb = NormalsToRgb255()
>>> output = rgb(input)  # 2x3x4x5