overlay_probability_map¶

overlay_probability_map(img, prediction, alpha=0.35, colour_map='jet', min_val=0.0, ax=None, *, return_ax)[source]¶

Generate an overlay, given a 2D prediction map.

Parameters:

  • img (ndarray) – Input image to overlay the results on top of. Assumed to be HW.

  • prediction (ndarray) – 2D prediction map. Values are expected to be between 0-1.

  • alpha (float) – Opacity value used for the overlay.

  • colour_map (string) – The colour map to use for the heatmap. jet is used as the default.

  • min_val (float) – Only consider pixels that are greater than or equal to min_val. Otherwise, the original WSI in those regions will be displayed.

  • alpha – Opacity value used for the overlay.

  • ax (ax) – Matplotlib axis object.

  • return_ax (bool) – Whether to return the matplotlib ax object. If not, then the overlay array will be returned.

Returns:

If return_ax is True, return the matplotlib ax object. Else, return the overlay array.

Return type:

np.ndarray | Axes

Examples

>>> from tiatoolbox.utils.visualization import overlay_probability_map
>>> import numpy as np
>>> from matplotlib import pyplot as plt
>>> # Generate a random example; replace with your own data
>>> img = np.random.randint(0, 256, size=(256, 256, 3), dtype=np.uint8)
>>> probability_map = np.random.rand(256, 256).astype(np.float32)
>>> # Example usage of overlay_probability_map
>>> ax = overlay_probability_map(
...     img=img,
...     prediction=probability_map,
...     alpha=0.35,
...     colour_map="jet",
...     min_val=0.0,
...     ax=None,
...     return_ax=True,
... )
>>> plt.show()