Map the validation dataset Table like name of file -> it's id in the W&B Table. Useful for - referencing artifacts for evaluation.

Mean of results, return mp, mr, map50, map

Args: img_size (tuple): The image size. polygons (np.ndarray): [N, M], N is the number of polygons, M is the number o

Return correct prediction matrix Arguments: detections (array[N, 6]), x1, y1, x2, y2, conf, class labels (array[M, 5]), class

Register a new action to a callback hook Args: hook: The callback hook name to register the action to name:

Compute the average precision, given the recall and precision curves. Source: https://github.com/rafaelpadilla/Object-Detection-Metrics. # Ar

Args: tp_b: tp of boxes. tp_m: tp of masks. other arguments see `func: ap_per_class`.