|hU1 &ddlmZddlZddlmZddlmZddlmZm Z m Z m Z m Z m Z ddlmZmZddlmZmZdd lmZdd lmZdd Zdd Zdd ZddZddZddZddZddZ ddZ dgddgdgdddggddfdZ!eeeeeeeeeeeed Z"d dZ#y)!)partialN)attempt_download_asset) MaskDecoder)FpnNeckHiera ImageEncoderImageEncoderViT MemoryEncoder PromptEncoder)MemoryAttentionMemoryAttentionLayer) SAM2ModelSAMModel)TinyViT)TwoWayTransformerc&tdddgd|S)z_Build and return a Segment Anything Model (SAM) h-size model with specified encoder parameters. encoder_embed_dim encoder_depthencoder_num_headsencoder_global_attn_indexes checkpoint _build_samr!s [/var/www/html/test/engine/venv/lib/python3.12/site-packages/ultralytics/models/sam/build.pybuild_sam_vit_hr& $3  c&tdddgd|S)z_Build and return a Segment Anything Model (SAM) l-size model with specified encoder parameters.r) rrr"r$s r%build_sam_vit_lr/"r'r(c&tdddgd|S)z_Build and return a Segment Anything Model (SAM) b-size model with specified encoder parameters. )r,r-rr"r$s r%build_sam_vit_br5-s $1  r(c0tgdgdgddd|S)z_Build and return a Mobile Segment Anything Model (Mobile-SAM) for efficient image segmentation.)@i@)r3r3r3)r3r, NT)rrrr mobile_samr!r"r$s r%build_mobile_samr>8s! -"'$(  r(c 6tdgddgdgdgd|S)zjBuild and return a Segment Anything Model 2 (SAM2) tiny-size model with specified architecture parameters.`)rr3rr3r)r,r r4r;rr1ir@rencoder_stagesrencoder_global_att_blocksencoder_window_specencoder_backbone_channel_listr! _build_sam2r$s r% build_sam2_trMDs$ #"+)&9 r(c 6tdgddgdgdgd|S)zeBuild and return a small-size Segment Anything Model 2 (SAM2) with specified architecture parameters.r@)rr3r-r3r)rr< rBrDrFrKr$s r% build_sam2_srPQs$ $"-)&9 r(c <tdgddgdgdddggd|S) zjBuild and return a Segment Anything Model 2 (SAM2) base-size model with specified architecture parameters.p)r3rrSr3)r2rrBrC)iirR)rrGrrHrIencoder_window_spatial_sizerJr!rKr$s r% build_sam2_brW^s+ $".)%'H&:  r(c 6tdgddgdgdgd|S)zeBuild and return a large-size Segment Anything Model 2 (SAM2) with specified architecture parameters.r3r:$r;r3)r!+r4r;rr4ii@i rYrFrKr$s r% build_sam2_lr`ls$ $".)&; r(cd}d}d}||z} |rtddd|||gddddd ddd n9t|||d ttjj d ||dd|d| } t | t|| | f||fdtdtd|dd|ddgdgd} |Ft|}t|d5} tj| } ddd| j | j| S#1swY,xYw)aT Build a Segment Anything Model (SAM) with specified encoder parameters. Args: encoder_embed_dim (int | List[int]): Embedding dimension for the encoder. encoder_depth (int | List[int]): Depth of the encoder. encoder_num_heads (int | List[int]): Number of attention heads in the encoder. encoder_global_attn_indexes (List[int] | None): Indexes for global attention in the encoder. checkpoint (str | None, optional): Path to the model checkpoint file. mobile_sam (bool, optional): Whether to build a Mobile-SAM model. Returns: (SAMModel): A Segment Anything Model instance with the specified architecture. Examples: >>> sam = _build_sam(768, 12, 12, [2, 5, 8, 11]) >>> sam = _build_sam([64, 128, 160, 320], [2, 2, 6, 2], [2, 4, 5, 10], None, mobile_sam=True) r*rrSi)rrrCrg@gFg?)img_sizein_chans num_classes embed_dimsdepths num_heads window_sizes mlp_ratio drop_ratedrop_path_rateuse_checkpointmbconv_expand_ratiolocal_conv_sizelayer_lr_decayr;gư>)epsTrC) depth embed_dimrcrj norm_layerrh patch_sizeqkv_bias use_rel_posglobal_attn_indexes window_size out_chans)rsimage_embedding_sizeinput_image_size mask_in_chansr3ir4)rr embedding_dimmlp_dimrh)num_multimask_outputs transformertransformer_dimiou_head_depthiou_head_hidden_dim)g33333^@gR]@gRY@)g(\2M@g(\L@gL@) image_encoderprompt_encoder mask_decoder pixel_mean pixel_stdNrb)rr rtorchnn LayerNormrr rrropenloadload_state_dicteval)rrrr r!r=prompt_embed_dim image_sizevit_patch_sizer{rsamf state_dicts r%r#r#ys[4JN%7$ ! ( '& # "'uxx11t<'% ;&  %B #$&"68L!M(*5  !"#).  - #  -)+ C.+J7 *d # 'qAJ ' J'HHJ J  ' 's <C==DrrZr3rr_rr^c Xtt||||||td|ddgdd}tdd d t } t d } |duxrd|v} t d7id|d| d| dddddddddd dd dd dd dd d d d!d d"d d#d d$d d%d d&d d'd d(d)d*dd+d d,d-d.| d/| d0| d1td d2d34} |It|}t|d55} tj| d6}ddd| j| j| S#1swY,xYw)8ae Build and return a Segment Anything Model 2 (SAM2) with specified architecture parameters. Args: encoder_embed_dim (int, optional): Embedding dimension for the encoder. encoder_stages (List[int], optional): Number of blocks in each stage of the encoder. encoder_num_heads (int, optional): Number of attention heads in the encoder. encoder_global_att_blocks (List[int], optional): Indices of global attention blocks in the encoder. encoder_backbone_channel_list (List[int], optional): Channel dimensions for each level of the encoder backbone. encoder_window_spatial_size (List[int], optional): Spatial size of the window for position embeddings. encoder_window_spec (List[int], optional): Window specifications for each stage of the encoder. checkpoint (str | None, optional): Path to the checkpoint file for loading pre-trained weights. Returns: (SAM2Model): A configured and initialized SAM2 model. Examples: >>> sam2_model = _build_sam2(encoder_embed_dim=96, encoder_stages=[1, 2, 7, 2]) >>> sam2_model.eval() )rsrhstagesglobal_att_blocks!window_pos_embed_bkg_spatial_size window_specrbr3rSnearest)d_modelbackbone_channel_listfpn_top_down_levelsfpn_interp_modelr)trunkneckscalpTr;)rpos_enc_at_input num_layerslayerr7)out_dimNzsam2.1rmemory_attentionmemory_encoder num_maskmemrrr*sigmoid_scale_for_mem_encg4@sigmoid_bias_for_mem_encg$$use_mask_input_as_output_without_samdirectly_add_no_mem_embeduse_high_res_features_in_sammultimask_output_in_samiou_prediction_use_sigmoiduse_obj_ptrs_in_encoderadd_tpos_enc_to_obj_ptrs"only_obj_ptrs_in_the_past_for_evalpred_obj_scorespred_obj_scores_mlpfixed_no_obj_ptrmultimask_output_for_trackinguse_multimask_token_for_obj_ptrmultimask_min_pt_numrmultimask_max_pt_numuse_mlp_for_obj_ptr_projcompile_image_encoderFno_obj_embed_spatialproj_tpos_enc_in_obj_ptrsuse_signed_tpos_enc_to_obj_ptrssam_mask_decoder_extra_argsg?g\(\?)dynamic_multimask_via_stability!dynamic_multimask_stability_delta"dynamic_multimask_stability_threshrmodel)r rrr rr rdictrrrrrr)rrGrrHrJrVrIr!rrr is_sam2_1sam2rrs r%rLrLs <!''!7.I+  "?!"A&  M"'sTVW_s_uv"2.N$&A8z+AI ! #! )! &!  !   !  #' ! "'! .2! #'! &*! !%! $(! !%! "&! ,0!  !! "!#! $%! &'+'! ()-)! *+! ,-! ."&/! 0$1! 2'3! 4#,5! 6)27! 8%),0.2/3% 9! DF+J7 *d # 0qAw/J 0 Z(IIK K  0 0s D  D)) zsam_h.ptzsam_l.ptsam_b.ptz mobile_sam.ptz sam2_t.ptz sam2_s.ptz sam2_b.ptz sam2_l.ptz sam2.1_t.ptz sam2.1_s.ptz sam2.1_b.ptz sam2.1_l.ptcd}t|}tjD])}|j|stj |}+|s"t |dtj||S)a Build and return a Segment Anything Model (SAM) based on the provided checkpoint. Args: ckpt (str | Path, optional): Path to the checkpoint file or name of a pre-defined SAM model. Returns: (SAMModel | SAM2Model): A configured and initialized SAM or SAM2 model instance. Raises: FileNotFoundError: If the provided checkpoint is not a supported SAM model. Examples: >>> sam_model = build_sam("sam_b.pt") >>> sam_model = build_sam("path/to/custom_checkpoint.pt") Notes: Supported pre-defined models include: - SAM: 'sam_h.pt', 'sam_l.pt', 'sam_b.pt', 'mobile_sam.pt' - SAM2: 'sam2_t.pt', 'sam2_s.pt', 'sam2_b.pt', 'sam2_l.pt' Nz7 is not a supported SAM model. Available models are: )str sam_model_mapkeysendswithgetFileNotFoundError)ckpt model_builderks r% build_samrGsx,M t9D    !1 == )--a0M1 4&(`anasasau`v wxx  r()N)NF)r)$ functoolsrrultralytics.utils.downloadsrmodules.decodersrmodules.encodersrrr r r r modules.memory_attentionr r modules.samrrmodules.tiny_encoderrmodules.transformerrr&r/r5r>rMrPrWr`r#rLrrrr(r%rs >)iiK,)2     $ \@ -"7!"A%\@ %  r(