Curves
Table of contents
analyze_curve()
It provides an overall analysis of the model performances by plotting the desired curve.
Parameters
- curve
Curves, optional- Evaluation curve used for the analysis.
(default is Curves.PRECISION_RECALL_CURVE) - average
str, optional- Indicates the averaging method. It can be 'macro' or 'micro'.
(default is 'macro') - show
bool, optional- Indicates whether the plot should be shown or not. If False, returns the results as dict.
(default is True)
Example
Classification
from odin.classes import AnalyzerClassification
my_analyzer = AnalyzerClassification("my_classifier_name", my_classification_dataset)
my_analyzer.analyze_curve()
Localization
from odin.classes import AnalyzerLocalization
my_analyzer = AnalyzerLocalization("my_detector_name", my_localization_dataset)
my_analyzer.analyze_curve()
Models comparison
Example
Classification
from odin.classes import ComparatorClassification
my_comparator = ComparatorClassification(dataset_gt_param, classification_type, models_proposals)
my_comparator.analyze_curve()
Localization
from odin.classes import ComparatorLocalization
my_comparator = ComparatorLocalization(dataset_gt_param, task_type, models_proposals)
my_comparator.analyze_curve()
Tasks supported
| Binary Classification | Single-label Classification | Multi-label Classification | Object Detection | Instance Segmentation |
|---|---|---|---|---|
| yes | yes | yes | yes | yes |
analyze_curve_for_categories()
For each category, it provides an analysis of the model performances by plotting the desired curve.
Parameters
- categories
list, optional- List of categories to be included in the analysis. If not specified, all the categories are included.
(default is None) - curve
Curves, optional- Evaluation curve used for the analysis.
(default is Curves.PRECISION_RECALL_CURVE) - show
bool, optional- Indicates whether the plot should be shown or not. If False, returns the results as dict.
(default is True)
Example
Classification
from odin.classes import AnalyzerClassification
my_analyzer = AnalyzerClassification("my_classifier_name", my_classification_dataset)
my_analyzer.analyze_curve_for_categories()
Localization
from odin.classes import AnalyzerLocalization
my_analyzer = AnalyzerLocalization("my_detector_name", my_localization_dataset)
my_analyzer.analyze_curve_for_categories()
Models comparison
Example
Classification
from odin.classes import ComparatorClassification
my_comparator = ComparatorClassification(dataset_gt_param, classification_type, models_proposals)
my_comparator.analyze_curve_for_categories()
Localization
from odin.classes import ComparatorLocalization
my_comparator = ComparatorLocalization(dataset_gt_param, task_type, models_proposals)
my_comparator.analyze_curve_for_categories()
Tasks supported
| Binary Classification | Single-label Classification | Multi-label Classification | Object Detection | Instance Segmentation |
|---|---|---|---|---|
| no | yes | yes | yes | yes |