haralick_analysis package

Haralick texture analysis of images using gray level co-occurrence matrices (GLCMs).

class haralick_analysis.CoOccurrenceMatrix(data: ndarray[tuple[int, int], dtype[float64]])

Bases: object

Represents a grey level co-occurrence matrix and provides methods to compute Haralick metrics.

property data: ndarray[tuple[int, int], dtype[float64]]

Obtain the gray level co-occurrence matrix data.

classmethod from_file(path: Path, *, params: CoOccurrenceParams | None = None) → CoOccurrenceMatrix

Create a Co-occurrenceMatrix from a grayscale image file.

classmethod from_image(image: ndarray[tuple[int, int], dtype[float64]], *, params: CoOccurrenceParams | None = None) → CoOccurrenceMatrix

Create a Co-occurrenceMatrix from a grayscale image.

property haralick_asm: float

Obtain value for the Haralick metric of Angular Second Moment (ASM).

property haralick_contrast: float

Obtain value for the Haralick metric of Contrast.

property haralick_correlation: float

Obtain value for the Haralick metric of Correlation.

property haralick_energy: float

Obtain value for the Haralick metric of Energy.

property haralick_homogeneity: float

Obtain value for the Haralick metric of Homogeneity.

property haralick_mean: float

Obtain value for the Haralick metric of Mean.

property haralick_std: float

Obtain value for the Haralick metric of Standard Deviation.

class haralick_analysis.CoOccurrenceParams(n_levels: int = 256, angle: int = 0, distance: int = 1)

Bases: object

Parameters for the co-occurrence matrix calculation.

angle: int = 0

distance: int = 1

n_levels: int = 256

haralick_analysis.plot_co_occurrence_matrix(matrix: CoOccurrenceMatrix, *, ax: Axes | None = None) → tuple[Figure, Axes]

Produce 2D colour map of gray level co-occurrence matrix for angle of 0 rad.

haralick_analysis.read_image_to_grayscale(path: Path) → np.ndarray[tuple[int, int], np.dtype[np.float64]]

Read image and convert to grayscale.