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Browse files- pretrained_models/classifier/final-model.rar +3 -0
- pretrained_models/classifier/pedestrian_classification.pth +3 -0
- pretrained_models/classifier/pedestrian_classificationv2.pth +3 -0
- pretrained_models/classifier/pedestrian_final.pth +3 -0
- pretrained_models/classifier/vehicle_classification.pth +3 -0
- pretrained_models/classifier/vehicle_classificationv2.pth +3 -0
- pretrained_models/classifier/vehicle_final.pth +3 -0
- pretrained_models/clip/ViT-B-32.pt +3 -0
- pretrained_models/depth/metric_video_depth_anything_vits.pth +3 -0
- pretrained_models/dino/dino_vitbase16_pretrain.pth +3 -0
- pretrained_models/fvd/i3d_pretrained_400.pt +3 -0
- pretrained_models/lpips/alexnet-owt-7be5be79.pth +3 -0
- pretrained_models/musiq/musiq_spaq_ckpt-358bb6af.pth +3 -0
- pretrained_models/perception/ada_track_detr3d_epoch24.pth +3 -0
- pretrained_models/perception/bevformer_base_seg_det_150.pth +3 -0
- pretrained_models/perception/sparseocc_r50_nuimg_704x256_8f_60e_v1.1.pth +3 -0
- pretrained_models/reid/pedestrian_reid.pth +3 -0
- pretrained_models/reid/vehicle_reid.pth +3 -0
- pretrained_models/segmentation/sam2.1_hiera_l.yaml +120 -0
- pretrained_models/segmentation/sam2.1_hiera_large.pt +3 -0
pretrained_models/classifier/final-model.rar
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pretrained_models/classifier/pedestrian_classification.pth
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pretrained_models/classifier/pedestrian_classificationv2.pth
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pretrained_models/classifier/pedestrian_final.pth
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pretrained_models/classifier/vehicle_classification.pth
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pretrained_models/classifier/vehicle_classificationv2.pth
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pretrained_models/classifier/vehicle_final.pth
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pretrained_models/clip/ViT-B-32.pt
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pretrained_models/depth/metric_video_depth_anything_vits.pth
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pretrained_models/dino/dino_vitbase16_pretrain.pth
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pretrained_models/fvd/i3d_pretrained_400.pt
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pretrained_models/lpips/alexnet-owt-7be5be79.pth
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pretrained_models/musiq/musiq_spaq_ckpt-358bb6af.pth
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pretrained_models/perception/ada_track_detr3d_epoch24.pth
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pretrained_models/perception/bevformer_base_seg_det_150.pth
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pretrained_models/perception/sparseocc_r50_nuimg_704x256_8f_60e_v1.1.pth
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pretrained_models/reid/pedestrian_reid.pth
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pretrained_models/reid/vehicle_reid.pth
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pretrained_models/segmentation/sam2.1_hiera_l.yaml
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# @package _global_
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| 2 |
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| 3 |
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# Model
|
| 4 |
+
model:
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| 5 |
+
_target_: sam2.modeling.sam2_base.SAM2Base
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| 6 |
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image_encoder:
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| 7 |
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_target_: sam2.modeling.backbones.image_encoder.ImageEncoder
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| 8 |
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scalp: 1
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| 9 |
+
trunk:
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| 10 |
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_target_: sam2.modeling.backbones.hieradet.Hiera
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| 11 |
+
embed_dim: 144
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| 12 |
+
num_heads: 2
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| 13 |
+
stages: [2, 6, 36, 4]
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| 14 |
+
global_att_blocks: [23, 33, 43]
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| 15 |
+
window_pos_embed_bkg_spatial_size: [7, 7]
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| 16 |
+
window_spec: [8, 4, 16, 8]
|
| 17 |
+
neck:
|
| 18 |
+
_target_: sam2.modeling.backbones.image_encoder.FpnNeck
|
| 19 |
+
position_encoding:
|
| 20 |
+
_target_: sam2.modeling.position_encoding.PositionEmbeddingSine
|
| 21 |
+
num_pos_feats: 256
|
| 22 |
+
normalize: true
|
| 23 |
+
scale: null
|
| 24 |
+
temperature: 10000
|
| 25 |
+
d_model: 256
|
| 26 |
+
backbone_channel_list: [1152, 576, 288, 144]
|
| 27 |
+
fpn_top_down_levels: [2, 3] # output level 0 and 1 directly use the backbone features
|
| 28 |
+
fpn_interp_model: nearest
|
| 29 |
+
|
| 30 |
+
memory_attention:
|
| 31 |
+
_target_: sam2.modeling.memory_attention.MemoryAttention
|
| 32 |
+
d_model: 256
|
| 33 |
+
pos_enc_at_input: true
|
| 34 |
+
layer:
|
| 35 |
+
_target_: sam2.modeling.memory_attention.MemoryAttentionLayer
|
| 36 |
+
activation: relu
|
| 37 |
+
dim_feedforward: 2048
|
| 38 |
+
dropout: 0.1
|
| 39 |
+
pos_enc_at_attn: false
|
| 40 |
+
self_attention:
|
| 41 |
+
_target_: sam2.modeling.sam.transformer.RoPEAttention
|
| 42 |
+
rope_theta: 10000.0
|
| 43 |
+
feat_sizes: [64, 64]
|
| 44 |
+
embedding_dim: 256
|
| 45 |
+
num_heads: 1
|
| 46 |
+
downsample_rate: 1
|
| 47 |
+
dropout: 0.1
|
| 48 |
+
d_model: 256
|
| 49 |
+
pos_enc_at_cross_attn_keys: true
|
| 50 |
+
pos_enc_at_cross_attn_queries: false
|
| 51 |
+
cross_attention:
|
| 52 |
+
_target_: sam2.modeling.sam.transformer.RoPEAttention
|
| 53 |
+
rope_theta: 10000.0
|
| 54 |
+
feat_sizes: [64, 64]
|
| 55 |
+
rope_k_repeat: True
|
| 56 |
+
embedding_dim: 256
|
| 57 |
+
num_heads: 1
|
| 58 |
+
downsample_rate: 1
|
| 59 |
+
dropout: 0.1
|
| 60 |
+
kv_in_dim: 64
|
| 61 |
+
num_layers: 4
|
| 62 |
+
|
| 63 |
+
memory_encoder:
|
| 64 |
+
_target_: sam2.modeling.memory_encoder.MemoryEncoder
|
| 65 |
+
out_dim: 64
|
| 66 |
+
position_encoding:
|
| 67 |
+
_target_: sam2.modeling.position_encoding.PositionEmbeddingSine
|
| 68 |
+
num_pos_feats: 64
|
| 69 |
+
normalize: true
|
| 70 |
+
scale: null
|
| 71 |
+
temperature: 10000
|
| 72 |
+
mask_downsampler:
|
| 73 |
+
_target_: sam2.modeling.memory_encoder.MaskDownSampler
|
| 74 |
+
kernel_size: 3
|
| 75 |
+
stride: 2
|
| 76 |
+
padding: 1
|
| 77 |
+
fuser:
|
| 78 |
+
_target_: sam2.modeling.memory_encoder.Fuser
|
| 79 |
+
layer:
|
| 80 |
+
_target_: sam2.modeling.memory_encoder.CXBlock
|
| 81 |
+
dim: 256
|
| 82 |
+
kernel_size: 7
|
| 83 |
+
padding: 3
|
| 84 |
+
layer_scale_init_value: 1e-6
|
| 85 |
+
use_dwconv: True # depth-wise convs
|
| 86 |
+
num_layers: 2
|
| 87 |
+
|
| 88 |
+
num_maskmem: 7
|
| 89 |
+
image_size: 1024
|
| 90 |
+
# apply scaled sigmoid on mask logits for memory encoder, and directly feed input mask as output mask
|
| 91 |
+
sigmoid_scale_for_mem_enc: 20.0
|
| 92 |
+
sigmoid_bias_for_mem_enc: -10.0
|
| 93 |
+
use_mask_input_as_output_without_sam: true
|
| 94 |
+
# Memory
|
| 95 |
+
directly_add_no_mem_embed: true
|
| 96 |
+
no_obj_embed_spatial: true
|
| 97 |
+
# use high-resolution feature map in the SAM mask decoder
|
| 98 |
+
use_high_res_features_in_sam: true
|
| 99 |
+
# output 3 masks on the first click on initial conditioning frames
|
| 100 |
+
multimask_output_in_sam: true
|
| 101 |
+
# SAM heads
|
| 102 |
+
iou_prediction_use_sigmoid: True
|
| 103 |
+
# cross-attend to object pointers from other frames (based on SAM output tokens) in the encoder
|
| 104 |
+
use_obj_ptrs_in_encoder: true
|
| 105 |
+
add_tpos_enc_to_obj_ptrs: true
|
| 106 |
+
proj_tpos_enc_in_obj_ptrs: true
|
| 107 |
+
use_signed_tpos_enc_to_obj_ptrs: true
|
| 108 |
+
only_obj_ptrs_in_the_past_for_eval: true
|
| 109 |
+
# object occlusion prediction
|
| 110 |
+
pred_obj_scores: true
|
| 111 |
+
pred_obj_scores_mlp: true
|
| 112 |
+
fixed_no_obj_ptr: true
|
| 113 |
+
# multimask tracking settings
|
| 114 |
+
multimask_output_for_tracking: true
|
| 115 |
+
use_multimask_token_for_obj_ptr: true
|
| 116 |
+
multimask_min_pt_num: 0
|
| 117 |
+
multimask_max_pt_num: 1
|
| 118 |
+
use_mlp_for_obj_ptr_proj: true
|
| 119 |
+
# Compilation flag
|
| 120 |
+
compile_image_encoder: False
|
pretrained_models/segmentation/sam2.1_hiera_large.pt
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oid sha256:2647878d5dfa5098f2f8649825738a9345572bae2d4350a2468587ece47dd318
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size 898083611
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