o oiR-@sddlmZmZmZmZmZddlZddlmZddlm Z ddl m Z ddgZ dee d e fd d Z Gd ddZGd ddeZGdddZdS))ListOptionalTupleUnioncastN)Size)Tensor)transform_points Keypoints Keypoints3D keypointsreturncCtNNotImplementedError)r rM/home/ubuntu/.local/lib/python3.10/site-packages/kornia/geometry/keypoints.py_merge_keypoint_listsrc @seZdZdZd2deeeefdeddfddZd ee e efddfd d Z d ee e efd dddfd dZ e deee dfeffddZe defddZe dejfddZe dejfddZ d3deeedfeefdeedfdeddfddZdeddfdd Zdeddfd!d"Zd3d#ededdfd$d%Zd#eddfd&d'Zededdfd(d)Zd3d*edeeeeffd+d,Zd4d-d.Zd/ejddfd0d1ZdS)5r z2D Keypoints containing Nx2 or BxNx2 points. Args: keypoints: Raw tensor or a list of Tensors with the Nx2 coordinates raise_if_not_floating_point: will raise if the Tensor isn't float Tr raise_if_not_floating_pointr NcCd|_t|trt|\}|_t|tstdt|d|s0|r,td|j | }t |j dkr<| d}d|jkrGdkrRnn |j ddd ks[td |j d|jdkrbd nd |_||_dS) N&Input keypoints is not a Tensor. Got: .+Coordinates must be in floating point. Got r)rr)rz1Keypoints shape must be (N, 2) or (B, N, 2). Got FT_N isinstancelistrr TypeErrortypeis_floating_point ValueErrordtypefloatlenshapereshapendim _is_batched_dataselfr rrrr__init__*   , zKeypoints.__init__keycCt||j|d}|SNFr"r,r.r1new_objrrr __getitem__EzKeypoints.__getitem__valuecC|j|j|<|Srr,r.r1r9rrr __setitem__I zKeypoints.__setitem__.cC|jjSrdatar(r.rrrr(MzKeypoints.shapecC|jSrr;rBrrrrAQzKeypoints.datacCr?)zReturns keypoints device.)r,devicerBrrrrFUzKeypoints.devicecCr?)zReturns keypoints dtype.)r,r%rBrrrr%ZrGzKeypoints.dtypeFindicesvaluesinplacecCsV|r|j}n|j}t|tr|||jn||||r"|S|}||_|Sr)r,clonerr index_put_rA)r.rHrIrJr,objrrr index_put_s   zKeypoints.index_put padding_sizecCsnt|jdkr|ddkstd|jd|jd|dddf7<|jd |ddd f7<|S zSPad a bounding keypoints. Args: padding_size: (B, 4) rz%Expected padding_size as (B, 4). Got r).r.N).rQrr'r(size RuntimeErrorr,r.rOrrrpadv z Keypoints.padcCsnt|jdkr|ddkstd|jd|jd|dddf8<|jd |ddd f8<|SrPrSrVrrrunpadrXzKeypoints.unpadMcCsbd|jkr dkrnn |jdddkrtd|jdt||j}|r,||_|St|dS) &Apply a transformation matrix to the 2D keypoints. Args: M: The transformation matrix to be applied, shape of :math:`(3, 3)` or :math:`(B, 3, 3)`. inplace: do transform in-place and return self. Returns: The transformed keypoints. rrN)rrzAThe transformation matrix shape must be (3, 3) or (B, 3, 3). Got rF)r*r(r$r r,r )r.rZrJtransformed_boxesrrrtransform_keypointss,   zKeypoints.transform_keypointscC|j|ddSz9Inplace version of :func:`Keypoints.transform_keypoints`.TrJr^r.rZrrrtransform_keypoints_zKeypoints.transform_keypoints_cC||Srrclsr rrr from_tensorrCzKeypoints.from_tensoras_padded_sequencecC|rt|jS)aCast :class:`Keypoints` to a tensor. ``mode`` controls which 2D keypoints format should be use to represent keypoints in the tensor. Args: as_padded_sequence: whether to keep the pads for a list of keypoints. This parameter is only valid if the keypoints are from a keypoint list. Returns: Keypoints tensor :math:`(B, N, 2)` rr,r.rjrrr to_tensor zKeypoints.to_tensorcCt|jdSr3)r r,rKrBrrrrKzKeypoints.cloner%cCs|j||_|Sr)r,r")r.r%rrrr"szKeypoints.typeTF)r r )__name__ __module__ __qualname____doc__rrrboolr/sliceintr7r=propertyrrr(rAtorchrFr%rNrWrYr^rd classmethodrirnrKr"rrrrr !s@$        cszeZdZUeed<eddeeeefde ddfddZ deffdd Z dd ed e ddffd d Z dddZ ZS)VideoKeypointstemporal_channel_sizeTboxesvalidate_boxesr cCsjt|tfs|dks|jddkrtd|d}|||d|dd|d}||_|S)NrRrrzOInput box type is not yet supported. Please input an `BxTxNx2` tensor directly.rQrr)rr dimr(r$rTviewr)rhrrroutrrrris & (zVideoKeypoints.from_tensorcs8tjdd}tt|}|jd|jg|jddRS)NF)rjrrQ)superrnrrrrr(r.r __class__rrrns  zVideoKeypoints.to_tensorFrZrJcs0tj||d}|r |St|jd}|j|_|S)NraF)rr^r~rAr)r.rZrJrrrrr^s  z"VideoKeypoints.transform_keypointscCst|jd}|j|_|Sr3)r~r,rKrrrrrrKszVideoKeypoints.clonerrrs)r r~)rtrurvrz__annotations__r}rrrrxrirnr^rK __classcell__rrrrr~s & r~c@s"eZdZdZd&deeeefdeddfddZd ee e efddfd d Z d ee e efd dddfd dZ e defddZe defddZdeddfddZdeddfddZd'dededdfddZdeddfddZededdfdd Zd'd!edeeeeffd"d#Zd(d$d%ZdS))r z3D Keypoints containing Nx3 or BxNx3 points. Args: keypoints: Raw tensor or a list of Tensors with the Nx3 coordinates raise_if_not_floating_point: will raise if the Tensor isn't float Tr rr NcCr) Nrrrr)rrrrr)rz1Keypoints shape must be (N, 3) or (B, N, 3). Got FTrr-rrrr/r0zKeypoints3D.__init__r1cCr2r3r4r5rrrr7 r8zKeypoints3D.__getitem__r9cCr:rr;r<rrrr=r>zKeypoints3D.__setitem__cCr?rr@rBrrrr(rCzKeypoints3D.shapecCrDrr;rBrrrrArEzKeypoints3D.datarOcCrzSPad a bounding keypoints. Args: padding_size: (B, 6) rrVrrrrWzKeypoints3D.padcCrrrrVrrrrY&rzKeypoints3D.unpadFrZrJcCr)r[r)r.rZrJrrrr^/s zKeypoints3D.transform_keypointscCr_r`rbrcrrrrd<rez Keypoints3D.transform_keypoints_cCrfrrrgrrrri@rCzKeypoints3D.from_tensorrjcCrk)aCast :class:`Keypoints` to a tensor. ``mode`` controls which 2D keypoints format should be use to represent keypoints in the tensor. Args: as_padded_sequence: whether to keep the pads for a list of keypoints. This parameter is only valid if the keypoints are from a keypoint list. Returns: Keypoints tensor :math:`(B, N, 3)` rlrmrrrrnDrozKeypoints3D.to_tensorcCrpr3)r r,rKrBrrrrKUrqzKeypoints3D.clonerrrs)r r )rtrurvrwrrrrxr/ryrzr7r=r{rr(rArWrYr^rdr}rirnrKrrrrr s"$     )typingrrrrrr|r kornia.corerkornia.geometryr __all__rr r~r rrrrs   &#