box_iou does not work as expected when boxes1 dtype is int

Describe the bug
box_iou() does not work as expected when boxes1 dtype is int, resulting in returned IoU=0 (after converting back to int dtype). No warning messages are generated in this case.

To Reproduce
Steps to reproduce the behavior:

1. Install monai.
2. Run commands:

import torch
from monai.data.box_utils import box_iou
a = torch.tensor([1., 1., 1., 2., 2., 2.]).unsqueeze(0)
b = torch.tensor([1, 1, 1, 2, 2, 2]).unsqueeze(0)

print(a, a.dtype)
print(b, b.dtype)

iou_aa = box_iou(a,a)
print(f"{iou_aa=}")
iou_ab = box_iou(a,b)
print(f"{iou_ab=}")
iou_bb = box_iou(b,b)
print(f"{iou_bb=}")
iou_ba = box_iou(b,a)
print(f"{iou_ba=}")

OUTPUT:

tensor([[1., 1., 1., 2., 2., 2.]]) torch.float32
tensor([[1, 1, 1, 2, 2, 2]]) torch.int64
iou_aa=tensor([[1.0000]])
iou_ab=tensor([[1.0000]])
iou_bb=tensor([[0]])
iou_ba=tensor([[0]])

Expected behavior
All IoUs should be (in this case) values close to one. However, if boxes1.dtype is of type int
the line in the definition of box_iou():
iou_t = iou_t.to(dtype=box_dtype)
makes those IoUs to be 0. Maybe casting the IoU result back to integer should be avoided or at least warning message can be generated (iou_t is always in range [0.; 1.] just before type conversion).

Environment

================================
Printing MONAI config...

MONAI version: 1.4.0
Numpy version: 1.26.4
Pytorch version: 2.5.0
MONAI flags: HAS_EXT = False, USE_COMPILED = False, USE_META_DICT = False
MONAI rev id: 46a5272196a6c2590ca2589029eed8e4d56ff008
MONAI file: /home//anaconda3/envs/crc/lib/python3.9/site-packages/monai/init.py

Optional dependencies:
Pytorch Ignite version: 0.4.11
ITK version: 5.4.2
Nibabel version: 5.3.2
scikit-image version: 0.22.0
scipy version: 1.13.1
Pillow version: 10.4.0
Tensorboard version: 2.19.0
gdown version: 5.2.0
TorchVision version: 0.20.0
tqdm version: 4.66.5
lmdb version: 1.6.2
psutil version: 6.0.0
pandas version: 2.2.2
einops version: 0.8.1
transformers version: 4.40.2
mlflow version: 2.20.2
pynrrd version: 1.1.3
clearml version: 1.17.2rc0

For details about installing the optional dependencies, please visit:
https://docs.monai.io/en/latest/installation.html#installing-the-recommended-dependencies

================================
Printing system config...

System: Linux
Linux version: Ubuntu 22.04.5 LTS
Platform: Linux-6.8.0-51-generic-x86_64-with-glibc2.35
Processor: x86_64
Machine: x86_64
Python version: 3.9.20
Process name: python
Command: ['python', '-c', 'import monai; monai.config.print_debug_info()']
Num physical CPUs: 16
Num logical CPUs: 32
Num usable CPUs: 32
CPU freq. (MHz): 4467
Avg. sensor temp. (Celsius): UNKNOWN for given OS
Total physical memory (GB): 62.0
Available memory (GB): 40.0
Used memory (GB): 21.3

================================
Printing GPU config...

Num GPUs: 2
Has CUDA: True
CUDA version: 11.8
cuDNN enabled: True
NVIDIA_TF32_OVERRIDE: None
TORCH_ALLOW_TF32_CUBLAS_OVERRIDE: None
cuDNN version: 90100
Current device: 0
Library compiled for CUDA architectures: ['sm_50', 'sm_60', 'sm_61', 'sm_70', 'sm_75', 'sm_80', 'sm_86', 'sm_37', 'sm_90', 'compute_37']
GPU 0 Name: NVIDIA GeForce RTX 4090
GPU 0 Is integrated: False
GPU 0 Is multi GPU board: False
GPU 0 Multi processor count: 128
GPU 0 Total memory (GB): 23.6
GPU 0 CUDA capability (maj.min): 8.9
GPU 1 Name: NVIDIA GeForce RTX 4090
GPU 1 Is integrated: False
GPU 1 Is multi GPU board: False
GPU 1 Multi processor count: 128
GPU 1 Total memory (GB): 23.6
GPU 1 CUDA capability (maj.min): 8.9

Additional context

Start at the box_iou entry point in monai.data.box_utils and run the reproduction with float and integer boxes. Check the dtype conversion highlighted in the issue and add regression coverage for integer inputs. Done means integer-box IoUs remain close to one instead of becoming zero, with the intended behavior verified.