:jy ddlmZddlZddlZddlmZmZddlmZddlm Z ddl m Z ddl m Z d d lmZmZej"j$ dd ed eeeefd eededef dZGddej.Zy))UnionN)nnTensor)BroadcastingList2)_pair)_assert_has_ops)_log_api_usage_once)check_roi_boxes_shapeconvert_boxes_to_roi_formatinputboxes output_size spatial_scalereturnctjjs-tjjst t t t||}t|}t|tjs t|}tjjj ||||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_s m/home/mcse/projects/srt_converter/srt-converter-venv/lib/python3.12/site-packages/torchvision/ops/roi_pool.pyrrs< 99 ! ! #EII,@,@,BH%% D $K dELL )*40 %%..udM;WX>[fgh[ijIFA McbeZdZdZdeedeffd Zdede ee efdefdZ de fd Z xZS) RoIPoolz See :func:`roi_pool`. rrcTt|t|||_||_yN)super__init__r rr)selfrr __class__s rr&zRoIPool.__init__=s& D!&*r rrrcFt|||j|jSr$)rrr)r'rrs rforwardzRoIPool.forwardCstT%5%5t7I7IJJr cl|jjd|jd|jd}|S)Nz (output_size=z, spatial_scale=))r(__name__rr)r'ss r__repr__zRoIPool.__repr__Fs;~~&&'}T5E5E4FFVW[WiWiVjjk lr )r- __module__ __qualname____doc__rintfloatr&rrlistr*strr/ __classcell__)r(s@rr"r"8sY+$5c$:+5+ KVK5f1E+FK6K#r r")g?)typingrrtorch.fxrrtorch.jit.annotationsrtorch.nn.modules.utilsrtorchvision.extensionrutilsr _utilsr r fxwrapr5r3r4rModuler"r rrCs 3(1'F  & & f% &&#3'& &  &&Rbiir