ToFloat

Targets:

image

Image Types:uint8, float32

Convert the input image to float32 in [0, 1] by dividing by max_value. Useful for normalizing before neural networks or algorithms that expect float input.

Arguments

max_value

float | None

The maximum possible input value. If None, the transform will try to infer the maximum value by inspecting the data type of the input image:

uint8: 255
float32: 1.0 Default: None.

p

float

Probability of applying the transform. Default: 1.0.

Examples

>>> import numpy as np
>>> import albumentations as A
>>>
# Convert uint8 image to float
>>> image = np.random.randint(0, 256, (100, 100, 3), dtype=np.uint8)
>>> transform = A.ToFloat(max_value=None)
>>> float_image = transform(image=image)['image']
>>> assert float_image.dtype == np.float32
>>> assert 0 <= float_image.min() <= float_image.max() <= 1.0
>>>

Returns

np.ndarray

Image in floating point representation, with values in range [0, 1.0].

Notes

If the input image is already float32 with values in [0, 1], it will be returned unchanged.
For uint8, the function will scale the values to [0, 1] range.
The output will always be float32, regardless of the input type.
This transform is often used as a preprocessing step before applying other transformations or feeding the image into a neural network.