HypVINN.utils.visualization_utils¶

HypVINN.utils.visualization_utils.get_lut(lookup_table_path=PosixPath('/home/runner/work/FastSurfer/FastSurfer/src/HypVINN/config/HypVINN_ColorLUT.txt'))[source]¶

Retrieve a color lookup table (LUT) from a file.

This function reads a file and constructs a lookup table (LUT) from it.

Parameters:

lookup_table_pathPath, default=”/home/runner/work/FastSurfer/FastSurfer/src/HypVINN/config/HypVINN_ColorLUT.txt”: The path to the file from which the LUT will be constructed.

Returns:

lutOrderedDict: The constructed LUT as an ordered dictionary.

HypVINN.utils.visualization_utils.map_hyposeg2label(hyposeg, lut_file=PosixPath('/home/runner/work/FastSurfer/FastSurfer/src/HypVINN/config/HypVINN_ColorLUT.txt'))[source]¶

Map a HypVINN segmentation to a continuous label space using a lookup table.

Parameters:

hyposegnp.ndarray: The original segmentation map.
lut_filePath, default=”/home/runner/work/FastSurfer/FastSurfer/src/HypVINN/config/HypVINN_ColorLUT.txt”: The path to the lookup table file.

Returns:

mapped_hyposegndarray: The mapped segmentation.
cmapListedColormap: The colormap for the mapped segmentation.

HypVINN.utils.visualization_utils.plot_coronal_predictions(cmap, images_batch=None, pred_batch=None, img_per_row=8)[source]¶

Plot the predicted segmentations on a grid layout.

Parameters:

cmapmatplotlib.colors.Colormap: The colormap to be used for the predicted segmentations.
images_batchnp.ndarray, optional: The batch of input images. If not provided, the function will not plot anything.
pred_batchnp.ndarray, optional: The batch of predicted segmentations. If not provided, the function will not plot anything.
img_per_rowint, default=8: The number of images to be plotted per row in the grid layout.

Returns:

fig: matplotlib.figure.Figure: The figure containing the plotted images and predictions.

HypVINN.utils.visualization_utils.plot_qc_images(subject_qc_dir, orig_path, prediction_path, padd=45, lut_file=PosixPath('/home/runner/work/FastSurfer/FastSurfer/src/HypVINN/config/HypVINN_ColorLUT.txt'), slice_step=2)[source]¶

Plot the quality control images for the subject.

Parameters:

subject_qc_dirPath: The directory for the subject.
orig_pathPath: The path to the original image.
prediction_pathPath: The path to the predicted image.
paddint, default=45: The padding value for cropping the images and segmentations.
lut_filePath, default=”/home/runner/work/FastSurfer/FastSurfer/src/HypVINN/config/HypVINN_ColorLUT.txt”: The path to the lookup table file.
slice_stepint, default=2: The step size for selecting indices from the predicted segmentation.

HypVINN.utils.visualization_utils.remove_values_from_list(the_list, val)[source]¶

Removes values from a list.

Parameters:

the_listlist: The original list from which values will be removed.
valany: The value to be removed from the list.

Returns:

list: A new list with the specified value removed.

HypVINN.utils.visualization_utils.select_index_to_plot(hyposeg, slice_step=2)[source]¶

Select indices to plot based on the given segmentation map.

Parameters:

hyposegnp.ndarray: The segmentation map from which indices will be selected.
slice_stepint, default=2: The step size for selecting indices from the remaining indices after removing certain indices.

Returns:

list: The selected indices, sorted in ascending order.