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  1. sam2.1_hiera_t.yaml +121 -0
  2. sam2.1_hiera_tiny.pt +3 -0
sam2.1_hiera_t.yaml ADDED
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+ # @package _global_
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+
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+ # Model
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+ model:
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+ _target_: sam2.modeling.sam2_base.SAM2Base
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+ image_encoder:
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+ _target_: sam2.modeling.backbones.image_encoder.ImageEncoder
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+ scalp: 1
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+ trunk:
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+ _target_: sam2.modeling.backbones.hieradet.Hiera
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+ embed_dim: 96
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+ num_heads: 1
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+ stages: [1, 2, 7, 2]
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+ global_att_blocks: [5, 7, 9]
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+ window_pos_embed_bkg_spatial_size: [7, 7]
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+ neck:
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+ _target_: sam2.modeling.backbones.image_encoder.FpnNeck
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+ position_encoding:
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+ _target_: sam2.modeling.position_encoding.PositionEmbeddingSine
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+ num_pos_feats: 256
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+ normalize: true
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+ scale: null
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+ temperature: 10000
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+ d_model: 256
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+ backbone_channel_list: [768, 384, 192, 96]
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+ fpn_top_down_levels: [2, 3] # output level 0 and 1 directly use the backbone features
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+ fpn_interp_model: nearest
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+
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+ memory_attention:
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+ _target_: sam2.modeling.memory_attention.MemoryAttention
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+ d_model: 256
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+ pos_enc_at_input: true
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+ layer:
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+ _target_: sam2.modeling.memory_attention.MemoryAttentionLayer
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+ activation: relu
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+ dim_feedforward: 2048
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+ dropout: 0.1
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+ pos_enc_at_attn: false
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+ self_attention:
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+ _target_: sam2.modeling.sam.transformer.RoPEAttention
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+ rope_theta: 10000.0
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+ feat_sizes: [32, 32]
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+ embedding_dim: 256
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+ num_heads: 1
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+ downsample_rate: 1
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+ dropout: 0.1
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+ d_model: 256
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+ pos_enc_at_cross_attn_keys: true
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+ pos_enc_at_cross_attn_queries: false
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+ cross_attention:
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+ _target_: sam2.modeling.sam.transformer.RoPEAttention
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+ rope_theta: 10000.0
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+ feat_sizes: [32, 32]
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+ rope_k_repeat: True
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+ embedding_dim: 256
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+ num_heads: 1
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+ downsample_rate: 1
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+ dropout: 0.1
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+ kv_in_dim: 64
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+ num_layers: 4
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+
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+ memory_encoder:
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+ _target_: sam2.modeling.memory_encoder.MemoryEncoder
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+ out_dim: 64
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+ position_encoding:
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+ _target_: sam2.modeling.position_encoding.PositionEmbeddingSine
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+ num_pos_feats: 64
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+ normalize: true
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+ scale: null
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+ temperature: 10000
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+ mask_downsampler:
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+ _target_: sam2.modeling.memory_encoder.MaskDownSampler
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+ kernel_size: 3
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+ stride: 2
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+ padding: 1
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+ fuser:
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+ _target_: sam2.modeling.memory_encoder.Fuser
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+ layer:
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+ _target_: sam2.modeling.memory_encoder.CXBlock
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+ dim: 256
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+ kernel_size: 7
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+ padding: 3
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+ layer_scale_init_value: 1e-6
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+ use_dwconv: True # depth-wise convs
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+ num_layers: 2
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+
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+ num_maskmem: 7
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+ image_size: 1024
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+ # apply scaled sigmoid on mask logits for memory encoder, and directly feed input mask as output mask
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+ # SAM decoder
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+ sigmoid_scale_for_mem_enc: 20.0
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+ sigmoid_bias_for_mem_enc: -10.0
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+ use_mask_input_as_output_without_sam: true
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+ # Memory
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+ directly_add_no_mem_embed: true
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+ no_obj_embed_spatial: true
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+ # use high-resolution feature map in the SAM mask decoder
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+ use_high_res_features_in_sam: true
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+ # output 3 masks on the first click on initial conditioning frames
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+ multimask_output_in_sam: true
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+ # SAM heads
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+ iou_prediction_use_sigmoid: True
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+ # cross-attend to object pointers from other frames (based on SAM output tokens) in the encoder
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+ use_obj_ptrs_in_encoder: true
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+ add_tpos_enc_to_obj_ptrs: true
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+ proj_tpos_enc_in_obj_ptrs: true
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+ use_signed_tpos_enc_to_obj_ptrs: true
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+ only_obj_ptrs_in_the_past_for_eval: true
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+ # object occlusion prediction
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+ pred_obj_scores: true
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+ pred_obj_scores_mlp: true
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+ fixed_no_obj_ptr: true
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+ # multimask tracking settings
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+ multimask_output_for_tracking: true
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+ use_multimask_token_for_obj_ptr: true
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+ multimask_min_pt_num: 0
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+ multimask_max_pt_num: 1
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+ use_mlp_for_obj_ptr_proj: true
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+ # Compilation flag
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+ # HieraT does not currently support compilation, should always be set to False
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+ compile_image_encoder: False
sam2.1_hiera_tiny.pt ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:7402e0d864fa82708a20fbd15bc84245c2f26dff0eb43a4b5b93452deb34be69
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+ size 156008466