src package

Submodules

src.ActiveContour module

class src.ActiveContour.ActiveContour(image: list, x_coords: list = None, y_coords: list = None, alpha: float = 0.1, beta: float = 0.25, gamma: float = 1.0, kappa: float = 0.0, mu: float = 0.1, vf_iterations: int = 100, contour_iterations: int = 200)

Bases: object

Class that represents the snake, the contour that deforms until reaching a state of equilibrium through an optimization process. This class contains the methods needed to do that.

Methods

adjustContour(perimeter_factor=None, f_close=None, plot_contour=None, fix_point_count=None,

fix_point_indices=None, f_keep_point_count=None, f_compute_convergence=None, convergence_thresh=None, convergence_metric_type=None, convergence_metric_value=None) Runs the GGVF Active Contour code to completion. It deforms iteratively the initial contour until it reaches a sate of equilibrium.

adjustContour(perimeter_factor=None, f_close=None, plot_contour=None, fix_point_count=None, fix_point_indices=None, f_keep_point_count=None, f_compute_convergence=None, convergence_thresh=None, convergence_metric_type=None, convergence_metric_value=None) → ndarray

Runs the GGVF Active Contour code to completion. It deforms iteratively the initial contour until it reaches a sate of equilibrium.

Parameters

perimeter_factor: float, optional

It indicates the factor to compute the number of points to use for a given contour, by default None.

f_close: bool, optional

Flag to indicate if a contour must be closed, adding an extra point, by default None.

plot_contour: int, optional

Flag to indicate if a contour must be closed, adding an extra point, by default None.

fix_point_count: int, optional

Number of points to fix in the contour, by default None.

fix_point_indices: np.ndarray, optional

Array of indices of the points to be fixed.

f_keep_point_count: bool, optional

Flag to indicate that the number of points in the contour must be kept, and if False, it re-interpolates them.

f_compute_convergence: bool, optional

Flaf to indicate that the convergence must be computed.

convergence_thresh: float, optional

Value of the convergence limit.

convergence_metric_type: string, optional

It indicates the type of metric to compute the variation between the contour in the current iteration and the last iteration, until reaching convergence.

convergence_metric_value: float, optional

It indicates that the convergence must be computed, in case the flags f_compute_convergence or f_use_convergence_threshold where not set.

Returns

np.ndarray

It returns an array with the coordinates x and y of the contour after the adjustment, when the state of equilibrium is reached.

arcSample(points=50, f_close=None) → None

It takes a closed curve and re-samples it in equal arc lengths.

Parameters

pointsint, optional

The number of points in the output vectors, by default 50.

f_closebool, optional

Set this keyword to True to specify the contour curve, by default None.

calcGGVF() → None

It computes the GGVF, and sets the values of self.u and self.v.

edgeMap() → None

Computes the edge map of a given image, and sets the values of the coordinates u and v of the GGVF.

getCoords(xyRes=array([1., 1.])) → ndarray

It returns the coordinates x and y of the image.

Parameters

xyResnp.ndarray of floats, optional

Resolution of the image, by default np.array([1.,1.])

Returns

np.ndarray

Coordinates x and y of the image

note:: in case xCoords is an invalid value, it returns -1.

getDistance(xyRes=array([1., 1.])) → ndarray

This method calculates the distance between consecutive points.

Parameters:

xyRes: np.ndarray of floats, optional.

Resolution of the image, by default np.array([1,1]).

Returns:

np.ndarray

Array of floats with the euclidean distance between the consecutive points of a segment. note:: in case xCoords is an invalid value, it returns -1.

getPerimeter(xyRes=array([1., 1.])) → float

This method calculates the perimeter of a contour.

Parameters:

xyRes: np.ndarray of floats, optional.

Resolution of the image. Default: np.array([1,1]).

Returns:

float

Value of the perimeter of a contour. note:: in case xCoords is an invalid value, it returns -1.

get_GGVF()

It returns the values of the GGVF, with its coordinates u and v.

Returns

np.ndarray

It returns an array with the value of the GGVF.

get_x_coords()

It returns the array of coordinates x of the contour.

Returns

np.ndarray

X coordinates of the contour.

get_y_coords()

It returns the array of coordinates y of the contour.

Returns

np.ndarray

Y coordinates of the contour.

gradient(image: ndarray, direction: int) → ndarray

Computes the gradient of the image’s intensity.

Parameters

imagenp.ndarray

Array with the intensity values per pixel of the image.

directionint

It indicates the direction in which to calculate the gradient.

Returns

np.ndarray

Returns the result of computing the gradient of the image.

laplacian(image: ndarray) → ndarray

Computes the laplacian of an image.

Parameters

imagenp.ndarray

Image to apply the laplacian.

Returns

np.ndarray

Returns the laplacian of the image, computing the convolution of it with a kernel.

plotGVF() → None

setContour(x: list, y: list) → None

Set the [x, y] coordinates for the active contour.

Parameters

xlist

x coordinate array of the contour to be set.

ylist

y coordinate array of the contour to be set.

src.FilterActiveContour module

src.geometryFunctions module

src.geometryFunctions.calcNorm_L1ForVector(vec)

Computes the L1-norm for a vector of n components.

Parameters

vecnp.ndarray

vector

Returns

float

Value of the L1-norm for a vector of n components.

src.geometryFunctions.calcNorm_L2ForVector(vec)

Computes the L2-norm for a vector of n components.

Parameters

vecnp.ndarray

vector

Returns

float

Value of the L2-norm for a vector of n components.

src.geometryFunctions.calcNorm_LInfiniteForVector(vec)

Computes the L-infinity-norm for a vector of n components.

Parameters

vecnp.ndarray

vector

Returns

float

Value of the L-infinity-norm for a vector of n components.

src.geometryFunctions.polygon_line_sample(x, y, n_points_per_pix=None, f_close_output=None, flag_vector=None, interp_flag_vector=None, f_force_zero_flag_vector=None) → ndarray

src.geometryFunctions.polygon_perimeter(x: list, y: list, xyFactor: list = [1.0, 1.0]) → ndarray

Computes the perimeter for a given polygon (list of 2D points).

The polygon is not required to be closed.

Parameters

xlist

The input polygon x-coordinate array.

ylist

The input polygon y-coordinate array.

xyFactorlist, optional

Scaling factor in x and y (array of 2 elements).

Returns

np.ndarray

The perimeter of the given polygon.

src.hausdorffDistanceCalc module

src.hausdorffDistanceCalc.hausdorffDistanceFor2Dpoints(x1, y1, x2, y2)

Computes the Hausdorff Distance for 2D points.

Parameters

x1np.ndarray

x coordinate of point 1

y1np.ndarray

y coordinate of point 1

x2np.ndarray

x coordinate of point 2

y2np.ndarray

y coordinate of point 2

Returns

float

Value of the Hausdorff Distance for 2D points

src.utils module

src.utils.get_coords_from_csv(filepath)

src.utils.get_image(image_path: str, padding=100) → ndarray

src.utils.load_params(params_path: str) → dict

Module contents