GD_Libero / config_cfg.py
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data_aug_scales = [192, 208, 224, 240]
data_aug_max_size = 240
data_aug_scales2_resize = [256]
data_aug_scales2_crop = [224, 224]
data_aug_scale_overlap = None
batch_size = 55
modelname = 'groundingdino'
backbone = 'swin_T_224_1k'
position_embedding = 'sine'
pe_temperatureH = 20
pe_temperatureW = 20
return_interm_indices = [1, 2, 3]
enc_layers = 6
dec_layers = 6
pre_norm = False
dim_feedforward = 2048
hidden_dim = 256
dropout = 0.0
nheads = 8
num_queries = 900
query_dim = 4
num_patterns = 0
num_feature_levels = 4
enc_n_points = 4
dec_n_points = 4
two_stage_type = 'standard'
two_stage_bbox_embed_share = False
two_stage_class_embed_share = False
transformer_activation = 'relu'
dec_pred_bbox_embed_share = True
dn_box_noise_scale = 1.0
dn_label_noise_ratio = 0.5
dn_label_coef = 1.0
dn_bbox_coef = 1.0
embed_init_tgt = True
dn_labelbook_size = 91
max_text_len = 256
text_encoder_type = './bert-base-uncased'
use_text_enhancer = True
use_fusion_layer = True
use_checkpoint = True
use_transformer_ckpt = True
use_text_cross_attention = True
text_dropout = 0.0
fusion_dropout = 0.0
fusion_droppath = 0.1
sub_sentence_present = True
max_labels = 30
lr = 0.001
backbone_freeze_keywords = None
freeze_keywords = []
lr_backbone = 1e-05
lr_backbone_names = ['backbone.0', 'bert']
lr_linear_proj_mult = 1e-05
lr_linear_proj_names = ['ref_point_head', 'sampling_offsets']
weight_decay = 0.0001
param_dict_type = 'ddetr_in_mmdet'
ddetr_lr_param = False
epochs = 50
lr_drop = 10
save_checkpoint_interval = 10
clip_max_norm = 0.1
onecyclelr = False
multi_step_lr = False
lr_drop_list = [10, 20, 30, 40]
frozen_weights = None
dilation = False
pdetr3_bbox_embed_diff_each_layer = False
pdetr3_refHW = -1
random_refpoints_xy = False
fix_refpoints_hw = -1
dabdetr_yolo_like_anchor_update = False
dabdetr_deformable_encoder = False
dabdetr_deformable_decoder = False
use_deformable_box_attn = False
box_attn_type = 'roi_align'
dec_layer_number = None
decoder_layer_noise = False
dln_xy_noise = 0.2
dln_hw_noise = 0.2
add_channel_attention = False
add_pos_value = False
two_stage_pat_embed = 0
two_stage_add_query_num = 0
two_stage_learn_wh = False
two_stage_default_hw = 0.05
two_stage_keep_all_tokens = False
num_select = 40
batch_norm_type = 'FrozenBatchNorm2d'
masks = False
aux_loss = True
set_cost_class = 1.0
set_cost_bbox = 5.0
set_cost_giou = 2.0
cls_loss_coef = 2.5
bbox_loss_coef = 5.0
giou_loss_coef = 2.0
enc_loss_coef = 1.0
interm_loss_coef = 1.0
no_interm_box_loss = False
mask_loss_coef = 1.0
dice_loss_coef = 1.0
focal_alpha = 0.25
focal_gamma = 2.5
decoder_sa_type = 'sa'
matcher_type = 'HungarianMatcher'
decoder_module_seq = ['sa', 'ca', 'ffn']
nms_iou_threshold = -1
dec_pred_class_embed_share = True
match_unstable_error = True
use_ema = True
ema_decay = 0.9997
ema_epoch = 0
use_detached_boxes_dec_out = False
use_coco_eval = False
dn_scalar = 100
label_list = [
'alphabet soup', 'basket', 'bbq sauce', 'black bowl', 'book', 'butter',
'cabinet', 'caddy', 'chocolate pudding', 'cream cheese', 'gripper',
'ketchup', 'left moka pot', 'left plate', 'microwave', 'milk', 'moka pot',
'orange juice', 'plate', 'right moka pot', 'right plate', 'salad dressing',
'stove', 'tomato sauce', 'white mug', 'wine bottle', 'wine rack',
'yellow and white mug'
]