i |ddlmZmZddlZddlmZddlmcmZddZ Gddej Z dd ej d e d ed ej fd Zdd e dej d ed ej fdZ d de de dedejdejd ej f dZ d!dej deee e fdfdeedfdeded ej f dZdS)")TupleUnionNnorm_expexpp1c^|dddd}|dn|}|ddddddd| f}|dkr|dddddddfn|dddddd| df}|dkrH|dd d }||z }|tj|z} n|d kr||dd z } nl|d krtj|} nQ|dkrt j|} n6|dkrtj|} n|dkr|} ntd||dkrd|z} nQ|dkr|} n6|dkrtj|} n|dkr|} ntd|| | fS)aq Process network output to extract GS params and density values. Density could be view-dependent as SH coefficient Args: out: Network output tensor (B, C, H, W) activation: Activation type for 3D points conf_activation: Activation type for confidence values Returns: Tuple of (3D points tensor, confidence tensor) rNrT)dimkeepdimg:0yE>)minnormexprelusigmoidlinearzUnknown activation: rexpp0zUnknown conf_activation: ) permuterclamptorchexpm1rFrr ValueError) out activationconf_activationconf_dimfmapxyzconfd xyz_normedpts3dconf_outs K/home/robot-lab/lab/da3_repo/src/depth_anything_3/model/utils/head_utils.pyactivate_head_gsr's ;;q!Q " "D$qq(H qqq!!!QQQ ( " #C (A 4111aaa  4111aaa(8K3LDZ HHTH * * 0 0T 0 : :1W U[^^+ v  chh2th444 u   # v  s  y  c"" x  < <<==='!!txxzz> G # #88:: I % %=&& H $ $F_FFGGG (?c|eZdZUdZeedfed<deedfddffd Zdej dej fdZ xZ S) PermutezHnn.Module wrapper around Tensor.permute for cleaner nn.Sequential usage..dimsreturnNcVt||_dSN)super__init__r+)selfr+ __class__s r&r0zPermute.__init__Xs$  r(xc |j|jSr.)rr+)r1r3s r&forwardzPermute.forward\sqy$)$$r() __name__ __module__ __qualname____doc__rint__annotations__r0rTensorr5 __classcell__)r2s@r&r*r*SsRR S/U38_%%%,%%%%%%%%r(r*dpos_grid embed_dimomega_0r,c.|j\}}}|dksJ|d|}t|dz|dddf|}t|dz|dddf|}tj||gd} | |||S)a* Convert 2D position grid (HxWx2) to sinusoidal embeddings (HxWxC) Args: pos_grid: Tensor of shape (H, W, 2) containing 2D coordinates embed_dim: Output channel dimension for embeddings Returns: Tensor of shape (H, W, embed_dim) with positional embeddings rr Nr)rAr r )shapereshapemake_sincos_pos_embedrcatview) r?r@rAHWgrid_dimpos_flatemb_xemb_yembs r&position_grid_to_embedrP`s^NAq( q====H--H ")q.(111a4.' R R RE !)q.(111a4.' R R RE )UEN + + +C 88Aq) $ $$r(posc|dzdksJtj|dztj|j}||dz z}d||zz }|d}tjd||}tj|}tj|}tj||gd }| S) a" This function generates a 1D positional embedding from a given grid using sine and cosine functions. # noqa Args: - embed_dim: The embedding dimension. - pos: The position to generate the embedding from. Returns: - emb: The generated 1D positional embedding. rr)dtypedeviceg@?r zm,d->mdr rC) rarangefloat32rTrEeinsumsincosrGfloat)r@rQrAomegaremb_sinemb_cosrOs r&rFrF{s q=A     Lau}SZ P P PE Y_E '5. E ++b//C ,y#u - -CinnGinnG )Wg&A . . .C 99;;r(widthheight aspect_ratiorSrTc|t|t|z }|dzdzdz}||z }d|z }| |dz z|z }||dz z|z } | |dz z|z } ||dz z|z } tj|| |||} tj| | |||} tj| | d\}}tj||fd }|S) a Create a normalized UV grid of shape (width, height, 2). The grid spans horizontally and vertically according to an aspect ratio, ensuring the top-left corner is at (-x_span, -y_span) and the bottom-right corner is at (x_span, y_span), normalized by the diagonal of the plane. Args: width (int): Number of points horizontally. height (int): Number of points vertically. aspect_ratio (float, optional): Width-to-height ratio. Defaults to width/height. dtype (torch.dtype, optional): Data type of the resulting tensor. device (torch.device, optional): Device on which the tensor is created. Returns: torch.Tensor: A (width, height, 2) tensor of UV coordinates. NrrUg?r )stepsrSrTxy)indexingr rC)r[rlinspacemeshgridstack)r_r`rarSrT diag_factorspan_xspan_yleft_xright_xtop_ybottom_yx_coordsy_coordsuuvvuv_grids r&create_uv_gridrus 2U||eFmm3  ?S(S0K K 'F ; FW "U *F "U*G Gvz "V +E!$v-H~fgU%PVWWWH~eXV5QWXXXH^Hh > > >FBk2r(+++G Nr(bilinearTr3size scale_factormode align_cornerscF| Jdt|jd|zt|jd|zfd}ddz|jdz|jdz}||krUtj|||zdzd}fd |D}tj|d St j| S) zi Safe interpolation implementation to avoid INT_MAX overflow in torch.nn.functional.interpolate. Nz-Either size or scale_factor must be provided.r i`rr )chunksr cVg|]%}tj|&S)rwryrz)nn functional interpolate).0crzryrws r& z&custom_interpolate..sB    M % %ad] % [ [   r(rCr) r:rDrchunkrG contiguousrrr) r3rwrxryrzINT_MAXtotalr}outss ` `` r&custom_interpolaters |'')X'''AGBK,.//QWR[<5O1P1PQG Gd1g  *QWQZ 7E wQ(8A'=1EEE         y1%%%00222 = $ $QTM $ Z ZZr()rrN)r>)NNN)NNrvT)typingrrrtorch.nnrtorch.nn.functionalrrr'Moduler*r<r:r[rPrFrSrTrustrboolrr(r&rs   2222t % % % % %bi % % %>A%%l%'*%5:% \%%%%6Su|eV[Vb@ // / // ; / L /  \ ////n*.'+ [[ |[ c3h% &[t $[  [  [  \ [[[[[[r(