metaheuristic_designer.encodings.image_encoding module

Encoding for image-based optimization tasks.

class ImageEncoding(shape, color=True, **kwargs)

Bases: Encoding

Encoding that maps between flat genotype vectors and image tensors.

Each individual is reshaped to (height, width, channels). When color is False the channel dimension is omitted (grayscale).

Parameters:

shapetuple of int

(height, width) of the image.

colorbool, optional

If True (default), the image has 3 colour channels (RGB). If False, it has 1 channel (grayscale).

**kwargs

Forwarded to Encoding.

Attributes:

params

Access parameter values by attribute-style lookup.

Parameters:

• shape (Tuple[int, int])

• color (bool)

Methods

decode(population)	Decodes a population matrix into a list/array of solutions.
encode(solution)	Encodes a list of solutions to our problem to an population matrix.
gather_params()	Overridable thin wrapper around get_params
get_params()	Return a copy of the current parameter dictionary.
store_kwargs([progress])	Store keyword arguments and evaluate them at the given progress.
update(progress)	Re-evaluate all stored parameters at the current progress.
update_kwargs([progress])	Add or replace parameters and immediately evaluate them.

get_state

encode(solution)

Encodes a list of solutions to our problem to an population matrix.

Return type:

ndarray[tuple[int, int], floating] | ndarray[tuple[int, int], integer] | ndarray[tuple[int, int], uint8 | bool]

Parameters:

solutions: Iterable

Solutions that should be encoded.

Returns:

population: ndarray

Population array.

Parameters:

solution (Iterable)

decode(population)

Decodes a population matrix into a list/array of solutions.

Return type:

Iterable

Parameters:

population: ndarray

Population that should be decoded.

Returns:

solutions: Iterable

List/array of solutions.

Parameters:

population (ndarray[tuple[int, int], floating] | ndarray[tuple[int, int], integer] | ndarray[tuple[int, int], uint8 | bool])