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rtdetr_swin_L_384_3x_coco.yml
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rtdetr_swin_L_384_3x_coco.yml
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_BASE_: [
'../datasets/coco_detection.yml',
'../runtime.yml',
'_base_/optimizer_6x.yml',
'_base_/rtdetr_r50vd.yml',
'_base_/rtdetr_reader.yml',
]
weights: output/rtdetr_swin_L_384_3x_coco/model_final
find_unused_parameters: True
log_iter: 100
snapshot_epoch: 2
pretrain_weights: https://bj.bcebos.com/v1/paddledet/models/dino_swin_large_384_4scale_3x_coco.pdparams
DETR:
backbone: SwinTransformer
neck: HybridEncoder
transformer: RTDETRTransformer
detr_head: DINOHead
post_process: DETRPostProcess
SwinTransformer:
arch: 'swin_L_384' # ['swin_T_224', 'swin_S_224', 'swin_B_224', 'swin_L_224', 'swin_B_384', 'swin_L_384']
ape: false
drop_path_rate: 0.2
patch_norm: true
out_indices: [1, 2, 3]
HybridEncoder:
hidden_dim: 256
use_encoder_idx: [2]
num_encoder_layers: 6 #
encoder_layer:
name: TransformerLayer
d_model: 256
nhead: 8
dim_feedforward: 2048 #
dropout: 0.
activation: 'gelu'
expansion: 1.0
RTDETRTransformer:
num_queries: 300
position_embed_type: sine
feat_strides: [8, 16, 32]
num_levels: 3
nhead: 8
num_decoder_layers: 6
dim_feedforward: 2048 #
dropout: 0.0
activation: relu
num_denoising: 100
label_noise_ratio: 0.5
box_noise_scale: 1.0
learnt_init_query: False
DINOHead:
loss:
name: DINOLoss
loss_coeff: {class: 1, bbox: 5, giou: 2}
aux_loss: True
use_vfl: True
matcher:
name: HungarianMatcher
matcher_coeff: {class: 2, bbox: 5, giou: 2}
DETRPostProcess:
num_top_queries: 300
epoch: 36
LearningRate:
base_lr: 0.0001
schedulers:
- !PiecewiseDecay
gamma: 0.1
milestones: [36]
use_warmup: false
OptimizerBuilder:
clip_grad_by_norm: 0.1
regularizer: false
optimizer:
type: AdamW
weight_decay: 0.0001
param_groups:
- params: ['absolute_pos_embed', 'relative_position_bias_table', 'norm']
weight_decay: 0.0