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08ec965 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | # Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/detectron2/structures/boxes.py
import torch
def pairwise_iou_max_scores(boxes1: torch.Tensor, boxes2: torch.Tensor) -> torch.Tensor:
"""
Given two lists of boxes of size N and M, compute the IoU
(intersection over union) between **all** N x M pairs of boxes.
The box order must be (xmin, ymin, xmax, ymax).
Args:
boxes1,boxes2 (Boxes): two `Boxes`. Contains N & M boxes, respectively.
Returns:
Tensor: IoU, sized [N,M].
"""
area1 = (boxes1[:, 2] - boxes1[:, 0]) * (boxes1[:, 3] - boxes1[:, 1]) # [N]
area2 = (boxes2[:, 2] - boxes2[:, 0]) * (boxes2[:, 3] - boxes2[:, 1]) # [M]
width_height = torch.min(boxes1[:, None, 2:], boxes2[:, 2:]) - torch.max(
boxes1[:, None, :2], boxes2[:, :2]
) # [N,M,2]
width_height.clamp_(min=0) # [N,M,2]
inter = width_height.prod(dim=2) # [N,M]
# handle empty boxes
iou = torch.where(
inter > 0,
inter / (area1[:, None] + area2 - inter),
torch.zeros(1, dtype=inter.dtype, device=inter.device),
)
iou_max, _ = torch.max(iou, dim=1)
return iou_max |