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| [32mINFO [0m [32m2024-03-29 17:46:26,830 | [34mgit: | |
| sha: N/A, status: clean, branch: N/A | |
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| [32mINFO [0m [32m2024-03-29 17:46:26,830 | [34mCommand: main.py --output_dir ./debug -c config/cfg_fsc147_vit_b.py --datasets config/datasets_fsc147.json --pretrain_model_path checkpoints/groundingdino_swinb_cogcoor.pth --options text_encoder_type=checkpoints/bert-base-uncased[0m | |
| [32mINFO [0m [32m2024-03-29 17:46:26,831 | [34mFull config saved to ./debug/config_args_all.json[0m | |
| [32mINFO [0m [32m2024-03-29 17:46:26,831 | [34mworld size: 1[0m | |
| [32mINFO [0m [32m2024-03-29 17:46:26,831 | [34mrank: 0[0m | |
| [32mINFO [0m [32m2024-03-29 17:46:26,831 | [34mlocal_rank: 0[0m | |
| [32mINFO [0m [32m2024-03-29 17:46:26,831 | [34margs: Namespace(config_file='config/cfg_fsc147_vit_b.py', options={'text_encoder_type': 'checkpoints/bert-base-uncased'}, datasets='config/datasets_fsc147.json', remove_difficult=False, fix_size=False, output_dir='./debug', note='', device='cuda', seed=42, resume='', pretrain_model_path='checkpoints/groundingdino_swinb_cogcoor.pth', finetune_ignore=None, start_epoch=0, eval=False, num_workers=8, test=False, debug=False, find_unused_params=False, save_results=False, save_log=False, world_size=1, dist_url='env://', rank=0, local_rank=0, amp=False, distributed=False, data_aug_scales=[480, 512, 544, 576, 608, 640, 672, 704, 736, 768, 800], data_aug_max_size=1333, data_aug_scales2_resize=[400, 500, 600], data_aug_scales2_crop=[384, 600], data_aug_scale_overlap=None, batch_size=4, modelname='groundingdino', backbone='swin_B_384_22k', 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='checkpoints/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=90, lr=0.0001, backbone_freeze_keywords=None, freeze_keywords=['backbone.0', 'bert'], 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=30, lr_drop=10, save_checkpoint_interval=10, clip_max_norm=0.1, onecyclelr=False, multi_step_lr=False, lr_drop_list=[10, 20], 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=900, batch_norm_type='FrozenBatchNorm2d', masks=False, aux_loss=True, set_cost_class=5.0, set_cost_bbox=1.0, set_cost_giou=0.0, cls_loss_coef=5.0, bbox_loss_coef=1.0, giou_loss_coef=0.0, 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=2.0, 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_detached_boxes_dec_out=False, dn_scalar=100, box_threshold=0.23, text_threshold=0, use_coco_eval=False, label_list=['alcohol bottle', 'baguette roll', 'ball', 'banana', 'bead', 'bee', 'birthday candle', 'biscuit', 'boat', 'bottle', 'bowl', 'box', 'bread roll', 'brick', 'buffalo', 'bun', 'calamari ring', 'can', 'candle', 'cap', 'car', 'cartridge', 'cassette', 'cement bag', 'cereal', 'chewing gum piece', 'chopstick', 'clam', 'coffee bean', 'coin', 'cotton ball', 'cow', 'crane', 'crayon', 'croissant', 'crow', 'cup', 'cupcake', 'cupcake holder', 'fish', 'gemstone', 'go game piece', 'goat', 'goldfish snack', 'goose', 'ice cream', 'ice cream cone', 'instant noodle', 'jade stone', 'jeans', 'kidney bean', 'kitchen towel', 'lighter', 'lipstick', 'm&m piece', 'macaron', 'match', 'meat skewer', 'mini blind', 'mosaic tile', 'naan bread', 'nail', 'nut', 'onion ring', 'orange', 'pearl', 'pen', 'pencil', 'penguin', 'pepper', 'person', 'pigeon', 'plate', 'polka dot tile', 'potato', 'rice bag', 'roof tile', 'screw', 'shoe', 'spoon', 'spring roll', 'stair', 'stapler pin', 'straw', 'supermarket shelf', 'swan', 'tomato', 'watermelon', 'window', 'zebra'], val_label_list=['ant', 'bird', 'book', 'bottle cap', 'bullet', 'camel', 'chair', 'chicken wing', 'donut', 'donut holder', 'flamingo', 'flower', 'flower pot', 'grape', 'horse', 'kiwi', 'milk carton', 'oyster', 'oyster shell', 'package of fresh cut fruit', 'peach', 'pill', 'polka dot', 'prawn cracker', 'sausage', 'seagull', 'shallot', 'shirt', 'skateboard', 'toilet paper roll']) | |
| [0m | |
| [36mDEBUG [0m [36m2024-03-29 17:46:26,832 | [34mbuild model ... ...[0m | |
| [36mDEBUG [0m [36m2024-03-29 17:46:28,620 | [34mbuild model, done.[0m | |
| [32mINFO [0m [32m2024-03-29 17:46:28,622 | [34mnumber of params:236717952[0m | |
| [32mINFO [0m [32m2024-03-29 17:46:28,625 | [34mparams before freezing: | |
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| }[0m | |
| [36mDEBUG [0m [36m2024-03-29 17:46:28,636 | [34mbuild dataset ... ...[0m | |
| [36mDEBUG [0m [36m2024-03-29 17:46:29,266 | [34mbuild dataset, done.[0m | |
| [36mDEBUG [0m [36m2024-03-29 17:46:29,267 | [34mnumber of training dataset: 1, samples: 3659[0m | |
| [32mINFO [0m [32m2024-03-29 17:46:29,889 | [34mIgnore keys: [][0m | |
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