SemanticSegmentationEvaluation#
- class SemanticSegmentationEvaluation[source]#
Bases:
ClassificationEvaluation
Evaluation for semantic segmentation.
- __init__(class_config: ClassConfig)[source]#
- Parameters
class_config (ClassConfig) –
Methods
__init__
(class_config)compute
(gt_labels, pred_labels)Compute metrics for a single scene.
Compute average metrics over all classes.
merge
(other[, scene_id])Merge Evaluation for another Scene into this one.
reset
()Reset the Evaluation.
save
(output_uri)Save this Evaluation to a file.
to_json
()Serialize to a dict or list.
- __init__(class_config: ClassConfig)[source]#
- Parameters
class_config (ClassConfig) –
- compute(gt_labels: SemanticSegmentationLabels, pred_labels: SemanticSegmentationLabels) None [source]#
Compute metrics for a single scene.
- Parameters
ground_truth_labels – Ground Truth labels to evaluate against.
prediction_labels – The predicted labels to evaluate.
gt_labels (SemanticSegmentationLabels) –
pred_labels (SemanticSegmentationLabels) –
- Return type
None
- merge(other: ClassificationEvaluation, scene_id: Optional[str] = None) None #
Merge Evaluation for another Scene into this one.
This is useful for computing the average metrics of a set of scenes. The results of the averaging are stored in this Evaluation.
- Parameters
other (ClassificationEvaluation) – Evaluation to merge into this one
scene_id (Optional[str], optional) – ID of scene. If specified, (a copy of)
other
will be saved and be availabel into_json()
’s output. Defaults to None.
- Return type
None
- reset()#
Reset the Evaluation.