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base/base_refcoco+.pth

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base/base_refcoco.pth

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base/base_refcocog_g.pth

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base/base_refcocog_u.pth

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large/lagre_refcoco.pth

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large/large_refcoco+.pth

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large/large_refcocog_g.pth

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large/large_refcocog_u.pth

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mix/DETRIS_large_mixed.yaml

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+DATA:
+  dataset: refcoco
+  train_lmdb: datasets/lmdb/refcoco/train.lmdb
+  train_split: train
+  val_lmdb: datasets/lmdb/refcoco/val.lmdb
+  val_split: val
+  mask_root: datasets/masks/refcoco
+TRAIN:
+  visual_adapter_dim: 384
+  visual_adapter_layer: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23]
+  txt_adapter_dim: 384
+  txtual_adapter_layer: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
+  # Base Arch
+  clip_pretrain: pretrain/ViT-B-16.pt
+  dino_pretrain: pretrain/dinov2_vitl14_reg4_pretrain.pth
+  dino_name: dinov2-large
+  dino_layers: 24
+  output_dinov2: [8, 16]
+  model_name: CLIP-b-16
+  input_size: 448
+  word_len: 17
+  word_dim: 512
+  ladder_dim: 64
+  nhead: 8
+  multi_stage: 3
+  stride: [1, 1, 1]
+  vis_dim: 512
+  fpn_in: [1024, 1024, 1024] #dinov2 backbone
+  fpn_out: [256, 512, 1024]
+  sync_bn: True
+ 
+  # Decoder
+  num_layers: 3
+  num_head: 8
+  dim_ffn: 512
+  dropout: 0.1
+  intermediate: False 
+  # Training Setting
+  workers: 32  # data loader workers
+  workers_val: 16
+  epochs: 50
+  milestones: [35]
+  start_epoch: 0
+  batch_size: 32  # batch size for training
+  batch_size_val: 32  # batch size for validation during training, memory and speed tradeoff
+  base_lr: 0.0001
+  lr_decay: 0.1
+  lr_multi: 1
+  weight_decay: 0.
+  max_norm: 0.
+  manual_seed: 0
+  print_freq: 100
+  # Resume & Save
+  exp_name: DETRIS_large
+  output_folder: exp/refcoco
+  save_freq: 1
+  weight:  # path to initial weight (default: none)
+  resume:  # path to latest checkpoint (default: none)
+  evaluate: True  # evaluate on validation set, extra gpu memory needed and small batch_size_val is recommend
+
+TEST:
+  test_split: val-test
+  test_lmdb: datasets/lmdb/refcoco/val.lmdb
+  visualize: False

mix/mixed.pth

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