%`i] ddlmZmZddlmZddlmZmZddl m Z GddeZ GddeZ Gd d eZ Gd d eZd S))AnyUnion) tv_tensors) functional Transform)CLAMPING_MODE_TYPEceZdZdZejfZdeeej fddffd Z dejde ee fdejfdZ xZS) ConvertBoundingBoxFormata_Convert bounding box coordinates to the given ``format``, eg from "CXCYWH" to "XYXY". Args: format (str or tv_tensors.BoundingBoxFormat): output bounding box format. Possible values are defined by :class:`~torchvision.tv_tensors.BoundingBoxFormat` and string values match the enums, e.g. "XYXY" or "XYWH" etc. formatreturnNcVt||_dSN)super__init__r )selfr __class__s s/home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/torchvision/transforms/v2/_meta.pyrz!ConvertBoundingBoxFormat.__init__s$  inptparamsc8tj||jS)N) new_format)Fconvert_bounding_box_formatr rrrs r transformz"ConvertBoundingBoxFormat.transforms,TdkJJJJr)__name__ __module__ __qualname____doc__r BoundingBoxes_transformed_typesrstrBoundingBoxFormatrdictrr __classcell__rs@rr r s%24uS**F%FGDKj6KS#XKS]SkKKKKKKKKrr ceZdZdZd deeefddffd Zej fZ dej de ee fdej fd Z xZS) ClampBoundingBoxesa Clamp bounding boxes to their corresponding image dimensions. Args: clamping_mode: Default is "auto" which relies on the input box' ``clamping_mode`` attribute. Read more in :ref:`clamping_mode_tuto` for more details on how to use this transform. auto clamping_moder NcVt||_dSr)rrr+rr+rs rrzClampBoundingBoxes.__init__$s' *rrrc8tj||jS)N)r+)rclamp_bounding_boxesr+rs rrzClampBoundingBoxes.transform*s%d$:LMMMMr)r*)rrrr rrr#rrr!r"r%rrr&r's@rr)r)s++e,>,C&D+RV++++++%24Nj6NS#XNS]SkNNNNNNNNrr)cZeZdZdZejfZdejdeee fdejfdZ dS)ClampKeyPointszClamp keypoints to their corresponding image dimensions. The clamping is done according to the keypoints' ``canvas_size`` meta-data. rrr c*tj|Sr)rclamp_keypointsrs rrzClampKeyPoints.transform6s &&&rN) rrrr r KeyPointsr"r%r#rrrrr1r1.sc %.0'j2'DcN'zOc''''''rr1cteZdZdZdeddffd ZejfZdejde e e fdejfdZ xZ S) SetClampingModea4Sets the ``clamping_mode`` attribute of the bounding boxes for future transforms. Args: clamping_mode: The clamping mode to set. Possible values are: "soft", "hard", or ``None``. Read more in :ref:`clamping_mode_tuto` for more details on how to use this transform. r+r Nct||_|jdvrtd|dS)N)Nsofthardz.clamping_mode must be soft, hard or None, got )rrr+ ValueErrorr-s rrzSetClampingMode.__init__EsO *  %; ; ;]m]]^^ ^ < ;rrrcF|}|j|_|Sr)cloner+)rrrouts rrzSetClampingMode.transformNs(,  . r)rrrr rrrr!r"r%r#rrr&r's@rr7r7:s_&8_T______%24j6S#XS]Skrr7N)typingrr torchvisionrtorchvision.transforms.v2rrr&torchvision.tv_tensors._bounding_boxesrr r)r1r7r5rrrCs""""""@@@@@@@@EEEEEEKKKKKyKKK&NNNNNNNN& ' ' ' ' 'Y ' ' 'ir