AsType

class deeptrack.features.AsType(dtype: str | Callable[[...], str] = 'float64', **kwargs: Any)

Bases: Feature

Convert the data type of arrays.

Astype changes the data type (dtype) of input arrays to a specified type. The accepted types are standard NumPy or PyTorch data types (e.g., “float64”, “int32”, “uint8”, “int8”, and “torch.float32”).

Parameters

dtype: PropertyLike[str], optional

The desired data type for the image. Defaults to “float64”.

**kwargs: Any

Additional keyword arguments passed to the parent Feature class.

Methods

get(inputs, dtype, **kwargs) -> array

Convert the data type of the input image.

Examples

>>> import deeptrack as dt

Create an input array:

>>> import numpy as np
>>>
>>> input_array = np.array([1.5, 2.5, 3.5])

Apply an AsType feature to convert to “int32”:

>>> astype_feature = dt.AsType(dtype="int32")
>>> output_array = astype_feature.get(input_array, dtype="int32")
>>> output_array
array([1, 2, 3], dtype=int32)

Verify the data type:

>>> output_array.dtype
dtype('int32')

Methods Summary

get(inputs, dtype, **kwargs)

Convert the data type of the input image.

Methods Documentation

get(inputs: ndarray | Tensor, dtype: str, **kwargs: Any) → ndarray | Tensor

Convert the data type of the input image.

Parameters

inputs: array

The input data to process. It can be a NumPy array, a PyTorch tensor, or an Image.

dtype: str

The desired data type.

**kwargs: Any

Additional keyword arguments (unused here).

Returns

array

The input data converted to the specified data type. It can be a NumPy array or a PyTorch tensor.