scallops.visualize.segmentation.plot_segmentation

scallops.visualize.segmentation.plot_segmentation(data, dpi=300, titles=None, save_to_file=None, plot_cols=None, fontsize=None, **kwargs)

Plot basic segmentation results.

Parameters:

data (Sequence[ndarray]) – List of segmented images as ndarrays.
dpi (int) – Requested DPI (only relevant if saving to file).
titles (None | Sequence[str]) – Optional list of titles. Must be the same length as the number of stacks to plot.
save_to_file (None | str) – Optional filename of the output file (format will be taken from the extension).
plot_cols (None | int) – Number of columns to plot.
fontsize (None | int) – Size of the titles’ font.
kwargs – Extra keyword arguments for plt.subplots.Axes.

Example:

import numpy as np
from scallops.visualize.segmentation import plot_segmentation

# Create synthetic segmented images
segmentations = [
    np.random.rand(100, 100) > 0.5,
    np.random.rand(100, 100) > 0.5,
    np.random.rand(100, 100) > 0.5,
]

# Plot segmentation results
plot_segmentation(
    data=segmentations,
    dpi=150,
    titles=["Segmentation 1", "Segmentation 2", "Segmentation 3"],
    fontsize=12,
)
plt.show()