CAMs Visualization
Table of contents
CAMs Example
visualize_cams()
It shows all the ground truth and the related Class Activation Maps of the model.
Parameters
- categories
list, optional- List of categories to be included in the visualization. If not specified, all the categories are included.
(default is None) - cams_categories
list, optional- List of CAMs categories to be included in the visualization. If not specified, all the categories are included.
(default is None) - heatmap
bool, optional- Indicates whether to visualize the CAMs in heatmap mode or not.
(default is True) - threshold
float, optional- Threshold used for the CAMs visualization.
(default is 0.5) - show_predictions
bool, optional- Indicates whether to visualize also the predictions.
(default is False) - show_only_gt_cams
bool, optional- If cams_categories is not specified, indicates whether to show all the CAMs or only the ones related to the ground truth labels.
(default is False) - model
str, optional- Name of the model used for the visualization. If not specified, it is considered the first provided.
(default is None)
Example
Classification
from odin.classes import VisualizerClassification
my_visualizer = VisualizerClassification(models)
my_visualizer.visualize_cams()
Tasks supported
| Binary Classification | Single-label Classification | Multi-label Classification | Object Detection | Instance Segmentation |
|---|---|---|---|---|
| yes | yes | yes | no | no |