a PSicK @sddlmZmZddlZddlmZmZddlmZddlm Z ddl m Z ddl m Z d d lmZmZdeeeeefeeeed d dZGdddejZdS))ListUnionN)nnTensor)BroadcastingList2)_pair)_assert_has_ops)_log_api_usage_once)convert_boxes_to_roi_formatcheck_roi_boxes_shape?)inputboxes output_size spatial_scalereturncCsptjstjstttt||}t|}t |tj sJt |}tj j ||||d|d\}}|S)aU Performs Region of Interest (RoI) Pool operator described in Fast R-CNN Args: input (Tensor[N, C, H, W]): The input tensor, i.e. a batch with ``N`` elements. Each element contains ``C`` feature maps of dimensions ``H x W``. boxes (Tensor[K, 5] or List[Tensor[L, 4]]): the box coordinates in (x1, y1, x2, y2) format where the regions will be taken from. The coordinate must satisfy ``0 <= x1 < x2`` and ``0 <= y1 < y2``. If a single Tensor is passed, then the first column should contain the index of the corresponding element in the batch, i.e. a number in ``[0, N - 1]``. If a list of Tensors is passed, then each Tensor will correspond to the boxes for an element i in the batch. output_size (int or Tuple[int, int]): the size of the output after the cropping is performed, as (height, width) spatial_scale (float): a scaling factor that maps the box coordinates to the input coordinates. For example, if your boxes are defined on the scale of a 224x224 image and your input is a 112x112 feature map (resulting from a 0.5x scaling of the original image), you'll want to set this to 0.5. Default: 1.0 Returns: Tensor[K, C, output_size[0], output_size[1]]: The pooled RoIs. rr )torchjit is_scripting is_tracingr roi_poolrr r isinstancerr ops torchvision)rrrrroisoutput_rT/var/www/html/django/DPS/env/lib/python3.9/site-packages/torchvision/ops/roi_pool.pyr s "rcsLeZdZdZeeedfdd ZeeedddZ e dd d Z Z S) RoIPoolz See :func:`roi_pool`. )rrcs"tt|||_||_dSN)super__init__r rr)selfrr __class__rr r$;s zRoIPool.__init__)rrrcCst|||j|jSr")rrr)r%rrrrr forwardAszRoIPool.forward)rcCs"|jjd|jd|jd}|S)Nz (output_size=z, spatial_scale=))r'__name__rr)r%srrr __repr__DszRoIPool.__repr__) r* __module__ __qualname____doc__rintfloatr$rr(strr, __classcell__rrr&r r!6sr!)r)typingrrrrrtorch.jit.annotationsrZtorch.nn.modules.utilsrZtorchvision.extensionrutilsr _utilsr r r0r1rModuler!rrrr s      )