Convert the input image to a floating-point representation. This transform divides pixel values by `max_value` to get a float32 output array where all values lie in the range [0, 1.0]. It's useful for normalizing image data before feeding it into neural networks or other algorithms that expect float input. Args: 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 - uint16: 65535 - uint32: 4294967295 - float32: 1.0 Default: None. p (float): Probability of applying the transform. Default: 1.0. Targets: image, volume Image types: uint8, uint16, uint32, float32 Returns: np.ndarray: Image in floating point representation, with values in range [0, 1.0]. Note: - If the input image is already float32 with values in [0, 1], it will be returned unchanged. - For integer types (uint8, uint16, uint32), 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. Raises: TypeError: If the input image data type is not supported. 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 >>> # Convert uint16 image to float with custom max_value >>> image = np.random.randint(0, 4096, (100, 100, 3), dtype=np.uint16) >>> transform = A.ToFloat(max_value=4095) >>> float_image = transform(image=image)['image'] >>> assert float_image.dtype == np.float32 >>> assert 0 <= float_image.min() <= float_image.max() <= 1.0 See Also: FromFloat: The inverse operation, converting from float back to the original data type.
- max_value
- type:float | NoneDefault:null