This repo implements hierarchical uncertainty aggregation from the paper Active Learning for Object Detection with Evidential Deep Learning and Hierarchical Uncertainty Aggregation by Park et al. (2022).
It is in written in Rust with bindings for Python.
Run maturin build
to build the wheel.
-
Import the package with
import hua
. -
Create a
hua.HUA
object withiou_threshold
andscore_threshold
. -
Call
hua.HUA.run()
with:bounding_boxes: Array of bounding boxes in the format [x1, y1, x2, y2] of shape (N, 4), class_probabilities: Array of class probabilities of shape (N, C), uncertainty_scores: Array of instance level uncertainty scores of shape (N,), scales: Array of FPN scales from which the corresponding prediction was obtained of shape (N,).
-
The method returns the informativeness score of the image and the indices of the groups created by HUA.
Powerboxes: It was used to speed up the IOU calculation in the code.