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Delete sam2/configs/sam2_hiera_l.yaml

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  1. sam2/configs/sam2_hiera_l.yaml +0 -117
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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: 144
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- num_heads: 2
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- stages: [2, 6, 36, 4]
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- global_att_blocks: [23, 33, 43]
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- window_pos_embed_bkg_spatial_size: [7, 7]
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- window_spec: [8, 4, 16, 8]
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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: [1152, 576, 288, 144]
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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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- 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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- # 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: false
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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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- compile_image_encoder: False