normalization

sleap_nn.data.normalization

This module implements data pipeline blocks for normalization operations.

Functions:

Name	Description
apply_normalization	Normalize image tensor.
convert_to_grayscale	Convert given image to Grayscale image (single-channel).
convert_to_rgb	Convert given image to RGB image (three-channel image).

apply_normalization(image)

Normalize image tensor.

Source code in sleap_nn/data/normalization.py

def apply_normalization(image: torch.Tensor):
    """Normalize image tensor."""
    if not torch.is_floating_point(image):
        image = image.to(torch.float32) / 255.0
    return image

convert_to_grayscale(image)

Convert given image to Grayscale image (single-channel).

This functions converts the input image to grayscale only if the given image is not a single-channeled image.

Parameters:

Name	Type	Description	Default
image	Tensor	Tensor image of shape (..., 3, H, W)	required

Returns:

Type	Description
	Tensor image of shape (..., 1, H, W).

Source code in sleap_nn/data/normalization.py

def convert_to_grayscale(image: torch.Tensor):
    """Convert given image to Grayscale image (single-channel).

    This functions converts the input image to grayscale only if the given image is not
    a single-channeled image.

    Args:
        image: Tensor image of shape (..., 3, H, W)

    Returns:
        Tensor image of shape (..., 1, H, W).
    """
    if image.shape[-3] != 1:
        image = F.rgb_to_grayscale(image, num_output_channels=1)
    return image

convert_to_rgb(image)

Convert given image to RGB image (three-channel image).

This functions converts the input image to RGB only if the given image is not a RGB image.

Parameters:

Name	Type	Description	Default
image	Tensor	Tensor image of shape (..., 1, H, W)	required

Returns:

Type	Description
	Tensor image of shape (..., 3, H, W).

Source code in sleap_nn/data/normalization.py

def convert_to_rgb(image: torch.Tensor):
    """Convert given image to RGB image (three-channel image).

    This functions converts the input image to RGB only if the given image is not
    a RGB image.

    Args:
        image: Tensor image of shape (..., 1, H, W)

    Returns:
        Tensor image of shape (..., 3, H, W).
    """
    if image.shape[-3] != 3:
        image = image.repeat(1, 3, 1, 1)
    return image