Module i2pp.core.visualizers.image_visualizer

Functions for visualizations.

Classes

class ImageVisualizer (pixel_type: PixelValueType,
pixel_range: numpy.ndarray,
title: str | None = None)
Expand source code 
class ImageVisualizer(Visualizer):
    """A specialized visualizer for image-based structured grids.

    This class extends `Visualizer` to handle image data and generate a
    structured grid representation using PyVista. It supports RGB and scalar
    pixel values, applying the appropriate transformations for visualization.
    """

    def compute_grid(self, image_data: ImageData) -> None:
        """Creates a structured grid from image data.

        This function constructs a PyVista `StructuredGrid` using the
        predefined grid coordinates from the `ImageData` object. It assigns
        pixel values to the corresponding cell data. If the image data
        contains RGB values, they are reshaped accordingly; otherwise, scalar
        values are stored.

        Additionally, a transformation matrix is applied to adjust the grid's
        orientation and position in 3D space.

        All necessary information for plotting (specifically `self.grid` and
        `self.grid_visible`) is stored in the instance attributes for later use

        Arguments:
            image_data (ImageData): The image data containing precomputed grid
                coordinates, pixel values, orientation, and position.

        Returns:
            None
        """

        x, y, z = np.meshgrid(
            image_data.grid_coords.slice,
            image_data.grid_coords.row,
            image_data.grid_coords.col,
            indexing="ij",
        )
        structured_grid = pv.StructuredGrid(x, y, z)

        if image_data.pixel_type == PixelValueType.RGB:
            structured_grid.point_data[
                f"{image_data.pixel_type.value}_values"
            ] = image_data.pixel_data.reshape(-1, 3, order="F")
        elif (
            image_data.pixel_type == PixelValueType.CT
            or image_data.pixel_type == PixelValueType.MRT
        ):
            structured_grid.point_data[
                f"{image_data.pixel_type.value}_values"
            ] = image_data.pixel_data.flatten(order="F")

        transform_matrix = np.eye(4)
        transform_matrix[:3, :3] = image_data.orientation
        transform_matrix[:3, 3] = image_data.position

        structured_grid.transform(transform_matrix)

        self.grid = structured_grid
        self.grid_visible = structured_grid

        return None

A specialized visualizer for image-based structured grids.

This class extends Visualizer to handle image data and generate a structured grid representation using PyVista. It supports RGB and scalar pixel values, applying the appropriate transformations for visualization.

Initialize the Visualizer.

Arguments

pixel_type (PixelValueType): Specifies whether the pixel data is RGB or scalar. title (str | None, optional): The title of the plot window. Defaults to None.

Ancestors

Methods

def compute_grid(self,
image_data: ImageData) ‑> None
Expand source code 
def compute_grid(self, image_data: ImageData) -> None:
    """Creates a structured grid from image data.

    This function constructs a PyVista `StructuredGrid` using the
    predefined grid coordinates from the `ImageData` object. It assigns
    pixel values to the corresponding cell data. If the image data
    contains RGB values, they are reshaped accordingly; otherwise, scalar
    values are stored.

    Additionally, a transformation matrix is applied to adjust the grid's
    orientation and position in 3D space.

    All necessary information for plotting (specifically `self.grid` and
    `self.grid_visible`) is stored in the instance attributes for later use

    Arguments:
        image_data (ImageData): The image data containing precomputed grid
            coordinates, pixel values, orientation, and position.

    Returns:
        None
    """

    x, y, z = np.meshgrid(
        image_data.grid_coords.slice,
        image_data.grid_coords.row,
        image_data.grid_coords.col,
        indexing="ij",
    )
    structured_grid = pv.StructuredGrid(x, y, z)

    if image_data.pixel_type == PixelValueType.RGB:
        structured_grid.point_data[
            f"{image_data.pixel_type.value}_values"
        ] = image_data.pixel_data.reshape(-1, 3, order="F")
    elif (
        image_data.pixel_type == PixelValueType.CT
        or image_data.pixel_type == PixelValueType.MRT
    ):
        structured_grid.point_data[
            f"{image_data.pixel_type.value}_values"
        ] = image_data.pixel_data.flatten(order="F")

    transform_matrix = np.eye(4)
    transform_matrix[:3, :3] = image_data.orientation
    transform_matrix[:3, 3] = image_data.position

    structured_grid.transform(transform_matrix)

    self.grid = structured_grid
    self.grid_visible = structured_grid

    return None

Creates a structured grid from image data.

This function constructs a PyVista StructuredGrid using the predefined grid coordinates from the ImageData object. It assigns pixel values to the corresponding cell data. If the image data contains RGB values, they are reshaped accordingly; otherwise, scalar values are stored.

Additionally, a transformation matrix is applied to adjust the grid's orientation and position in 3D space.

All necessary information for plotting (specifically self.grid and self.grid_visible) is stored in the instance attributes for later use

Arguments

image_data (ImageData): The image data containing precomputed grid coordinates, pixel values, orientation, and position.

Returns

None

Inherited members