# 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