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View source on GitHub Arize class to map up to 3 columns (bounding_boxes_coordinates_column_name, categories_column_name, and scores_column_name) to a single object detection prediction or actual column. 
class ObjectDetectionColumnNames(
    bounding_boxes_coordinates_column_name: str
    categories_column_name: str
    scores_column_name: Optional[str] = None
)
ParametersData TypeExpected Type In ColumnDescription
bounding_boxes_coordinates_column_namestrThe contents of this column must be List[List[float]](Required) Column name containing the coordinates of the rectangular outline that locates an object within an image or video. Pascal VOC format required.
categories_column_namestrThe contents of this column must be List[str](Required) Column name containing the predefined classes or labels used by the model to classify the detected objects.
scores_column_namestrThe contents of this column must be List[float](Optional*) Column name containing the confidence scores that the model assigns to its predictions, indicating how certain the model is that the predicted class is contained within the bounding box. * This parameter is not applicable to actual (ground truth) labels and is only applicable when defining object_detection_prediction_column_names

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Code Example

Indexprediction_bboxesactual_bboxesprediction_categoriesactual_categoriesprediction_scores
0[[50.43, 109.49, 538.21...[[55.39, 107.72, 539.25, 362.9], [554.41, 194....[bus][bus, person, person][0.9997552]
object_detection_prediction_column_names = ObjectDetectionColumnNames(
  (bounding_boxes_coordinates_column_name = "prediction_bboxes"),
  (categories_column_name = "prediction_categories"),
  (scores_column_name = "prediction_scores")
);
object_detection_actual_column_names = ObjectDetectionColumnNames(
  (bounding_boxes_coordinates_column_name = "actual_bboxes"),
  (categories_column_name = "actual_categories")
);