powerboxes 0.3.1

Utility functions to manipulate and compute metrics on boxes

PowerBoxes

Powerboxes is a package containing utility functions for transforming bounding boxes and computing metrics. It is implemented in both Python and Rust. It shows a significant speedup over the equivalent numpy implementations in Python, or other libraries such as shapely or torchvision.

Documentation

Installation

pip install powerboxes

Usage

import powerboxes as pb
import numpy as np

boxes = np.array([[0, 0, 1, 1], [2, 2, 3, 3]], dtype=np.float64)

# Compute areas
areas = pb.box_areas(boxes)

# Compute IoU distance matrix
iou = pb.iou_distance(boxes, boxes)

# Draw boxes on an image (CHW format, uint8)
image = np.zeros((3, 100, 100), dtype=np.uint8)
draw_boxes = np.array([[10.0, 10.0, 50.0, 50.0]])
result = pb.draw_boxes(image, draw_boxes, filled=True, opacity=0.35)

# Draw rotated boxes in cxcywha format
rotated_boxes = np.array([[50.0, 50.0, 30.0, 20.0, 30.0]])
rotated = pb.draw_rotated_boxes(image, rotated_boxes)

For more details, see the full documentation or the GitHub repository.