| 2025-07-07 11:27:50,676 - PropVG - INFO - dataset = 'MixedSeg' | |
| data_root = './data/seqtr_type/' | |
| img_norm_cfg = dict( | |
| mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375]) | |
| train_pipeline = [ | |
| dict( | |
| type='LoadImageAnnotationsFromFile_TO', | |
| max_token=20, | |
| with_mask=True, | |
| with_bbox=True, | |
| dataset='MixedSeg', | |
| use_token_type='beit3', | |
| refer_file='data/seqtr_type/annotations/mixed-seg/coco_all.json', | |
| object_area_filter=100, | |
| object_area_rate_filter=[0.05, 0.8]), | |
| dict(type='Resize', img_scale=(384, 384), keep_ratio=False), | |
| dict( | |
| type='Normalize', | |
| mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375]), | |
| dict(type='DefaultFormatBundle'), | |
| dict( | |
| type='CollectData', | |
| keys=[ | |
| 'img', 'ref_expr_inds', 'text_attention_mask', 'gt_mask_rle', | |
| 'gt_bbox' | |
| ], | |
| meta_keys=[ | |
| 'filename', 'expression', 'ori_shape', 'img_shape', 'pad_shape', | |
| 'scale_factor', 'gt_ori_mask', 'target', 'empty', | |
| 'refer_target_index' | |
| ]) | |
| ] | |
| val_pipeline = [ | |
| dict( | |
| type='LoadImageAnnotationsFromFile_TO', | |
| max_token=20, | |
| with_mask=True, | |
| with_bbox=True, | |
| dataset='MixedSeg', | |
| use_token_type='beit3', | |
| refer_file='data/seqtr_type/annotations/mixed-seg/coco_all.json', | |
| object_area_filter=100, | |
| object_area_rate_filter=[0.05, 0.8]), | |
| dict(type='Resize', img_scale=(384, 384), keep_ratio=False), | |
| dict( | |
| type='Normalize', | |
| mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375]), | |
| dict(type='DefaultFormatBundle'), | |
| dict( | |
| type='CollectData', | |
| keys=[ | |
| 'img', 'ref_expr_inds', 'text_attention_mask', 'gt_mask_rle', | |
| 'gt_bbox' | |
| ], | |
| meta_keys=[ | |
| 'filename', 'expression', 'ori_shape', 'img_shape', 'pad_shape', | |
| 'scale_factor', 'gt_ori_mask', 'target', 'empty', | |
| 'refer_target_index' | |
| ]) | |
| ] | |
| test_pipeline = [ | |
| dict( | |
| type='LoadImageAnnotationsFromFile_TO', | |
| max_token=20, | |
| with_mask=True, | |
| with_bbox=True, | |
| dataset='MixedSeg', | |
| use_token_type='beit3', | |
| refer_file='data/seqtr_type/annotations/mixed-seg/coco_all.json', | |
| object_area_filter=100, | |
| object_area_rate_filter=[0.05, 0.8]), | |
| dict(type='Resize', img_scale=(384, 384), keep_ratio=False), | |
| dict( | |
| type='Normalize', | |
| mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375]), | |
| dict(type='DefaultFormatBundle'), | |
| dict( | |
| type='CollectData', | |
| keys=[ | |
| 'img', 'ref_expr_inds', 'text_attention_mask', 'gt_mask_rle', | |
| 'gt_bbox' | |
| ], | |
| meta_keys=[ | |
| 'filename', 'expression', 'ori_shape', 'img_shape', 'pad_shape', | |
| 'scale_factor', 'gt_ori_mask', 'target', 'empty', | |
| 'refer_target_index' | |
| ]) | |
| ] | |
| word_emb_cfg = dict(type='GloVe') | |
| data = dict( | |
| samples_per_gpu=8, | |
| workers_per_gpu=4, | |
| train=dict( | |
| type='MixedSeg', | |
| which_set='train', | |
| img_source=['coco'], | |
| annsfile= | |
| './data/seqtr_type/annotations/mixed-seg/instances_nogoogle_withid.json', | |
| imgsfile='./data/seqtr_type/images/mscoco/train2014', | |
| pipeline=[ | |
| dict( | |
| type='LoadImageAnnotationsFromFile_TO', | |
| max_token=20, | |
| with_mask=True, | |
| with_bbox=True, | |
| dataset='MixedSeg', | |
| use_token_type='beit3', | |
| refer_file= | |
| 'data/seqtr_type/annotations/mixed-seg/coco_all.json', | |
| object_area_filter=100, | |
| object_area_rate_filter=[0.05, 0.8]), | |
| dict(type='Resize', img_scale=(384, 384), keep_ratio=False), | |
| dict( | |
| type='Normalize', | |
| mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375]), | |
| dict(type='DefaultFormatBundle'), | |
| dict( | |
| type='CollectData', | |
| keys=[ | |
| 'img', 'ref_expr_inds', 'text_attention_mask', | |
| 'gt_mask_rle', 'gt_bbox' | |
| ], | |
| meta_keys=[ | |
| 'filename', 'expression', 'ori_shape', 'img_shape', | |
| 'pad_shape', 'scale_factor', 'gt_ori_mask', 'target', | |
| 'empty', 'refer_target_index' | |
| ]) | |
| ], | |
| word_emb_cfg=dict(type='GloVe')), | |
| val_refcoco_unc=dict( | |
| type='MixedSeg', | |
| which_set='val_refcoco_unc', | |
| img_source=['coco'], | |
| annsfile= | |
| './data/seqtr_type/annotations/mixed-seg/instances_nogoogle_withid.json', | |
| imgsfile='./data/seqtr_type/images/mscoco/train2014', | |
| pipeline=[ | |
| dict( | |
| type='LoadImageAnnotationsFromFile_TO', | |
| max_token=20, | |
| with_mask=True, | |
| with_bbox=True, | |
| dataset='MixedSeg', | |
| use_token_type='beit3', | |
| refer_file= | |
| 'data/seqtr_type/annotations/mixed-seg/coco_all.json', | |
| object_area_filter=100, | |
| object_area_rate_filter=[0.05, 0.8]), | |
| dict(type='Resize', img_scale=(384, 384), keep_ratio=False), | |
| dict( | |
| type='Normalize', | |
| mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375]), | |
| dict(type='DefaultFormatBundle'), | |
| dict( | |
| type='CollectData', | |
| keys=[ | |
| 'img', 'ref_expr_inds', 'text_attention_mask', | |
| 'gt_mask_rle', 'gt_bbox' | |
| ], | |
| meta_keys=[ | |
| 'filename', 'expression', 'ori_shape', 'img_shape', | |
| 'pad_shape', 'scale_factor', 'gt_ori_mask', 'target', | |
| 'empty', 'refer_target_index' | |
| ]) | |
| ], | |
| word_emb_cfg=dict(type='GloVe')), | |
| testA_refcoco_unc=dict( | |
| type='MixedSeg', | |
| which_set='testA_refcoco_unc', | |
| img_source=['coco'], | |
| annsfile= | |
| './data/seqtr_type/annotations/mixed-seg/instances_nogoogle_withid.json', | |
| imgsfile='./data/seqtr_type/images/mscoco/train2014', | |
| pipeline=[ | |
| dict( | |
| type='LoadImageAnnotationsFromFile_TO', | |
| max_token=20, | |
| with_mask=True, | |
| with_bbox=True, | |
| dataset='MixedSeg', | |
| use_token_type='beit3', | |
| refer_file= | |
| 'data/seqtr_type/annotations/mixed-seg/coco_all.json', | |
| object_area_filter=100, | |
| object_area_rate_filter=[0.05, 0.8]), | |
| dict(type='Resize', img_scale=(384, 384), keep_ratio=False), | |
| dict( | |
| type='Normalize', | |
| mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375]), | |
| dict(type='DefaultFormatBundle'), | |
| dict( | |
| type='CollectData', | |
| keys=[ | |
| 'img', 'ref_expr_inds', 'text_attention_mask', | |
| 'gt_mask_rle', 'gt_bbox' | |
| ], | |
| meta_keys=[ | |
| 'filename', 'expression', 'ori_shape', 'img_shape', | |
| 'pad_shape', 'scale_factor', 'gt_ori_mask', 'target', | |
| 'empty', 'refer_target_index' | |
| ]) | |
| ], | |
| word_emb_cfg=dict(type='GloVe')), | |
| testB_refcoco_unc=dict( | |
| type='MixedSeg', | |
| which_set='testB_refcoco_unc', | |
| img_source=['coco'], | |
| annsfile= | |
| './data/seqtr_type/annotations/mixed-seg/instances_nogoogle_withid.json', | |
| imgsfile='./data/seqtr_type/images/mscoco/train2014', | |
| pipeline=[ | |
| dict( | |
| type='LoadImageAnnotationsFromFile_TO', | |
| max_token=20, | |
| with_mask=True, | |
| with_bbox=True, | |
| dataset='MixedSeg', | |
| use_token_type='beit3', | |
| refer_file= | |
| 'data/seqtr_type/annotations/mixed-seg/coco_all.json', | |
| object_area_filter=100, | |
| object_area_rate_filter=[0.05, 0.8]), | |
| dict(type='Resize', img_scale=(384, 384), keep_ratio=False), | |
| dict( | |
| type='Normalize', | |
| mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375]), | |
| dict(type='DefaultFormatBundle'), | |
| dict( | |
| type='CollectData', | |
| keys=[ | |
| 'img', 'ref_expr_inds', 'text_attention_mask', | |
| 'gt_mask_rle', 'gt_bbox' | |
| ], | |
| meta_keys=[ | |
| 'filename', 'expression', 'ori_shape', 'img_shape', | |
| 'pad_shape', 'scale_factor', 'gt_ori_mask', 'target', | |
| 'empty', 'refer_target_index' | |
| ]) | |
| ], | |
| word_emb_cfg=dict(type='GloVe')), | |
| val_refcocoplus_unc=dict( | |
| type='MixedSeg', | |
| which_set='val_refcocoplus_unc', | |
| img_source=['coco'], | |
| annsfile= | |
| './data/seqtr_type/annotations/mixed-seg/instances_nogoogle_withid.json', | |
| imgsfile='./data/seqtr_type/images/mscoco/train2014', | |
| pipeline=[ | |
| dict( | |
| type='LoadImageAnnotationsFromFile_TO', | |
| max_token=20, | |
| with_mask=True, | |
| with_bbox=True, | |
| dataset='MixedSeg', | |
| use_token_type='beit3', | |
| refer_file= | |
| 'data/seqtr_type/annotations/mixed-seg/coco_all.json', | |
| object_area_filter=100, | |
| object_area_rate_filter=[0.05, 0.8]), | |
| dict(type='Resize', img_scale=(384, 384), keep_ratio=False), | |
| dict( | |
| type='Normalize', | |
| mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375]), | |
| dict(type='DefaultFormatBundle'), | |
| dict( | |
| type='CollectData', | |
| keys=[ | |
| 'img', 'ref_expr_inds', 'text_attention_mask', | |
| 'gt_mask_rle', 'gt_bbox' | |
| ], | |
| meta_keys=[ | |
| 'filename', 'expression', 'ori_shape', 'img_shape', | |
| 'pad_shape', 'scale_factor', 'gt_ori_mask', 'target', | |
| 'empty', 'refer_target_index' | |
| ]) | |
| ], | |
| word_emb_cfg=dict(type='GloVe')), | |
| testA_refcocoplus_unc=dict( | |
| type='MixedSeg', | |
| which_set='testA_refcocoplus_unc', | |
| img_source=['coco'], | |
| annsfile= | |
| './data/seqtr_type/annotations/mixed-seg/instances_nogoogle_withid.json', | |
| imgsfile='./data/seqtr_type/images/mscoco/train2014', | |
| pipeline=[ | |
| dict( | |
| type='LoadImageAnnotationsFromFile_TO', | |
| max_token=20, | |
| with_mask=True, | |
| with_bbox=True, | |
| dataset='MixedSeg', | |
| use_token_type='beit3', | |
| refer_file= | |
| 'data/seqtr_type/annotations/mixed-seg/coco_all.json', | |
| object_area_filter=100, | |
| object_area_rate_filter=[0.05, 0.8]), | |
| dict(type='Resize', img_scale=(384, 384), keep_ratio=False), | |
| dict( | |
| type='Normalize', | |
| mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375]), | |
| dict(type='DefaultFormatBundle'), | |
| dict( | |
| type='CollectData', | |
| keys=[ | |
| 'img', 'ref_expr_inds', 'text_attention_mask', | |
| 'gt_mask_rle', 'gt_bbox' | |
| ], | |
| meta_keys=[ | |
| 'filename', 'expression', 'ori_shape', 'img_shape', | |
| 'pad_shape', 'scale_factor', 'gt_ori_mask', 'target', | |
| 'empty', 'refer_target_index' | |
| ]) | |
| ], | |
| word_emb_cfg=dict(type='GloVe')), | |
| testB_refcocoplus_unc=dict( | |
| type='MixedSeg', | |
| which_set='testB_refcocoplus_unc', | |
| img_source=['coco'], | |
| annsfile= | |
| './data/seqtr_type/annotations/mixed-seg/instances_nogoogle_withid.json', | |
| imgsfile='./data/seqtr_type/images/mscoco/train2014', | |
| pipeline=[ | |
| dict( | |
| type='LoadImageAnnotationsFromFile_TO', | |
| max_token=20, | |
| with_mask=True, | |
| with_bbox=True, | |
| dataset='MixedSeg', | |
| use_token_type='beit3', | |
| refer_file= | |
| 'data/seqtr_type/annotations/mixed-seg/coco_all.json', | |
| object_area_filter=100, | |
| object_area_rate_filter=[0.05, 0.8]), | |
| dict(type='Resize', img_scale=(384, 384), keep_ratio=False), | |
| dict( | |
| type='Normalize', | |
| mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375]), | |
| dict(type='DefaultFormatBundle'), | |
| dict( | |
| type='CollectData', | |
| keys=[ | |
| 'img', 'ref_expr_inds', 'text_attention_mask', | |
| 'gt_mask_rle', 'gt_bbox' | |
| ], | |
| meta_keys=[ | |
| 'filename', 'expression', 'ori_shape', 'img_shape', | |
| 'pad_shape', 'scale_factor', 'gt_ori_mask', 'target', | |
| 'empty', 'refer_target_index' | |
| ]) | |
| ], | |
| word_emb_cfg=dict(type='GloVe')), | |
| val_refcocog_umd=dict( | |
| type='MixedSeg', | |
| which_set='val_refcocog_umd', | |
| img_source=['coco'], | |
| annsfile= | |
| './data/seqtr_type/annotations/mixed-seg/instances_nogoogle_withid.json', | |
| imgsfile='./data/seqtr_type/images/mscoco/train2014', | |
| pipeline=[ | |
| dict( | |
| type='LoadImageAnnotationsFromFile_TO', | |
| max_token=20, | |
| with_mask=True, | |
| with_bbox=True, | |
| dataset='MixedSeg', | |
| use_token_type='beit3', | |
| refer_file= | |
| 'data/seqtr_type/annotations/mixed-seg/coco_all.json', | |
| object_area_filter=100, | |
| object_area_rate_filter=[0.05, 0.8]), | |
| dict(type='Resize', img_scale=(384, 384), keep_ratio=False), | |
| dict( | |
| type='Normalize', | |
| mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375]), | |
| dict(type='DefaultFormatBundle'), | |
| dict( | |
| type='CollectData', | |
| keys=[ | |
| 'img', 'ref_expr_inds', 'text_attention_mask', | |
| 'gt_mask_rle', 'gt_bbox' | |
| ], | |
| meta_keys=[ | |
| 'filename', 'expression', 'ori_shape', 'img_shape', | |
| 'pad_shape', 'scale_factor', 'gt_ori_mask', 'target', | |
| 'empty', 'refer_target_index' | |
| ]) | |
| ], | |
| word_emb_cfg=dict(type='GloVe')), | |
| test_refcocog_umd=dict( | |
| type='MixedSeg', | |
| which_set='test_refcocog_umd', | |
| img_source=['coco'], | |
| annsfile= | |
| './data/seqtr_type/annotations/mixed-seg/instances_nogoogle_withid.json', | |
| imgsfile='./data/seqtr_type/images/mscoco/train2014', | |
| pipeline=[ | |
| dict( | |
| type='LoadImageAnnotationsFromFile_TO', | |
| max_token=20, | |
| with_mask=True, | |
| with_bbox=True, | |
| dataset='MixedSeg', | |
| use_token_type='beit3', | |
| refer_file= | |
| 'data/seqtr_type/annotations/mixed-seg/coco_all.json', | |
| object_area_filter=100, | |
| object_area_rate_filter=[0.05, 0.8]), | |
| dict(type='Resize', img_scale=(384, 384), keep_ratio=False), | |
| dict( | |
| type='Normalize', | |
| mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375]), | |
| dict(type='DefaultFormatBundle'), | |
| dict( | |
| type='CollectData', | |
| keys=[ | |
| 'img', 'ref_expr_inds', 'text_attention_mask', | |
| 'gt_mask_rle', 'gt_bbox' | |
| ], | |
| meta_keys=[ | |
| 'filename', 'expression', 'ori_shape', 'img_shape', | |
| 'pad_shape', 'scale_factor', 'gt_ori_mask', 'target', | |
| 'empty', 'refer_target_index' | |
| ]) | |
| ], | |
| word_emb_cfg=dict(type='GloVe'))) | |
| ema = False | |
| ema_factor = 0.999 | |
| use_fp16 = False | |
| seed = 6666 | |
| deterministic = True | |
| log_level = 'INFO' | |
| log_interval = 50 | |
| save_interval = -1 | |
| resume_from = None | |
| load_from = 'work_dir/refcoco-mix/PropVG-refcoco-mix.pth' | |
| finetune_from = None | |
| evaluate_interval = 1 | |
| start_evaluate_epoch = 0 | |
| start_save_checkpoint = 20 | |
| max_token = 20 | |
| img_size = 384 | |
| patch_size = 16 | |
| model = dict( | |
| type='MIXRefUniModel_OMG', | |
| vis_enc=dict( | |
| type='BEIT3', | |
| img_size=384, | |
| patch_size=16, | |
| vit_type='base', | |
| drop_path_rate=0.1, | |
| vocab_size=64010, | |
| freeze_layer=-1, | |
| vision_embed_proj_interpolate=False, | |
| pretrain='pretrain_weights/beit3_base_patch16_224.zip'), | |
| lan_enc=None, | |
| fusion=None, | |
| head=dict( | |
| type='REFHead', | |
| input_channels=768, | |
| hidden_channels=256, | |
| num_queries=20, | |
| detr_loss=dict( | |
| criterion=dict(loss_class=1.0, loss_bbox=5.0, loss_giou=2.0), | |
| matcher=dict(cost_class=1.0, cost_bbox=5.0, cost_giou=2.0)), | |
| loss_weight=dict( | |
| mask=dict(dice=1.0, bce=1.0, nt=0.2, neg=0), | |
| bbox=0.1, | |
| allbbox=0.1, | |
| refer=1.0), | |
| MTD=dict(K=100)), | |
| post_params=dict( | |
| score_weighted=False, | |
| mask_threshold=0.5, | |
| score_threshold=0.7, | |
| with_nms=False, | |
| with_mask=True), | |
| process_visual=False, | |
| visualize_params=dict(row_columns=(4, 5)), | |
| visual_mode='test') | |
| grad_norm_clip = 0.15 | |
| lr = 0.0005 | |
| optimizer_config = dict( | |
| type='Adam', | |
| lr=0.0005, | |
| lr_vis_enc=5e-05, | |
| lr_lan_enc=0.0005, | |
| betas=(0.9, 0.98), | |
| eps=1e-09, | |
| weight_decay=0, | |
| amsgrad=True) | |
| scheduler_config = dict( | |
| type='MultiStepLRWarmUp', | |
| warmup_epochs=1, | |
| decay_steps=[21, 27], | |
| decay_ratio=0.1, | |
| max_epoch=30) | |
| launcher = 'pytorch' | |
| distributed = True | |
| rank = 0 | |
| world_size = 1 | |
| 2025-07-07 11:27:58,403 - PropVG - INFO - Mixed-val_refcoco_unc size: 10834 | |
| 2025-07-07 11:28:06,594 - PropVG - INFO - Mixed-testA_refcoco_unc size: 5657 | |
| 2025-07-07 11:28:15,164 - PropVG - INFO - Mixed-testB_refcoco_unc size: 5095 | |
| 2025-07-07 11:28:23,677 - PropVG - INFO - Mixed-val_refcocoplus_unc size: 10758 | |
| 2025-07-07 11:28:30,907 - PropVG - INFO - Mixed-testA_refcocoplus_unc size: 5726 | |
| 2025-07-07 11:28:38,494 - PropVG - INFO - Mixed-testB_refcocoplus_unc size: 4889 | |
| 2025-07-07 11:28:49,090 - PropVG - INFO - Mixed-val_refcocog_umd size: 4896 | |
| 2025-07-07 11:28:54,576 - PropVG - INFO - Mixed-test_refcocog_umd size: 9602 | |
| 2025-07-07 11:29:02,664 - PropVG - INFO - loaded checkpoint from work_dir/refcoco-mix/PropVG-refcoco-mix.pth | |
| 2025-07-07 11:29:02,665 - PropVG - INFO - PropVG - evaluating set val_refcoco_unc | |
| 2025-07-07 11:32:39,213 - PropVG - INFO - ------------ validate ------------ time: 216.54, DetACC: 92.70, mIoU: 81.96, oIoU: 81.80, MaskACC@0.5-0.9: [92.24, 90.71, 87.59, 79.79, 46.59]DetACC@0.5-0.9: [92.70, 91.43, 88.90, 83.85, 66.30] | |
| 2025-07-07 11:32:43,474 - PropVG - INFO - PropVG - evaluating set testA_refcoco_unc | |
| 2025-07-07 11:34:47,838 - PropVG - INFO - ------------ validate ------------ time: 124.36, DetACC: 95.07, mIoU: 83.58, oIoU: 83.74, MaskACC@0.5-0.9: [94.56, 93.48, 90.93, 82.91, 46.61]DetACC@0.5-0.9: [95.07, 93.99, 92.17, 88.17, 69.29] | |
| 2025-07-07 11:34:53,297 - PropVG - INFO - PropVG - evaluating set testB_refcoco_unc | |
| 2025-07-07 11:36:51,290 - PropVG - INFO - ------------ validate ------------ time: 117.99, DetACC: 89.58, mIoU: 80.02, oIoU: 79.33, MaskACC@0.5-0.9: [89.19, 86.99, 83.45, 76.76, 51.07]DetACC@0.5-0.9: [89.58, 87.56, 84.61, 79.14, 61.83] | |
| 2025-07-07 11:36:56,652 - PropVG - INFO - PropVG - evaluating set val_refcocoplus_unc | |
| 2025-07-07 11:40:28,540 - PropVG - INFO - ------------ validate ------------ time: 211.88, DetACC: 87.27, mIoU: 77.14, oIoU: 74.81, MaskACC@0.5-0.9: [86.67, 85.36, 82.52, 75.28, 44.34]DetACC@0.5-0.9: [87.27, 86.30, 84.09, 79.64, 63.62] | |
| 2025-07-07 11:40:36,392 - PropVG - INFO - PropVG - evaluating set testA_refcocoplus_unc | |
| 2025-07-07 11:42:43,800 - PropVG - INFO - ------------ validate ------------ time: 127.40, DetACC: 90.87, mIoU: 79.83, oIoU: 78.72, MaskACC@0.5-0.9: [90.13, 88.79, 86.57, 79.46, 45.04]DetACC@0.5-0.9: [90.87, 89.82, 87.81, 83.92, 66.33] | |
| 2025-07-07 11:42:48,169 - PropVG - INFO - PropVG - evaluating set testB_refcocoplus_unc | |
| 2025-07-07 11:44:41,261 - PropVG - INFO - ------------ validate ------------ time: 113.09, DetACC: 81.26, mIoU: 72.18, oIoU: 69.15, MaskACC@0.5-0.9: [80.18, 78.20, 74.78, 68.68, 45.88]DetACC@0.5-0.9: [81.26, 79.40, 76.95, 72.20, 56.78] | |
| 2025-07-07 11:44:45,751 - PropVG - INFO - PropVG - evaluating set val_refcocog_umd | |
| 2025-07-07 11:46:42,173 - PropVG - INFO - ------------ validate ------------ time: 116.42, DetACC: 88.15, mIoU: 76.97, oIoU: 75.54, MaskACC@0.5-0.9: [86.17, 83.58, 79.43, 72.16, 44.87]DetACC@0.5-0.9: [88.15, 85.97, 82.90, 78.00, 63.09] | |
| 2025-07-07 11:46:46,257 - PropVG - INFO - PropVG - evaluating set test_refcocog_umd | |
| 2025-07-07 11:50:06,821 - PropVG - INFO - ------------ validate ------------ time: 200.56, DetACC: 88.30, mIoU: 77.72, oIoU: 77.40, MaskACC@0.5-0.9: [87.14, 85.01, 80.84, 72.78, 45.79]DetACC@0.5-0.9: [88.30, 86.71, 83.98, 79.07, 65.00] | |
| 2025-07-07 11:50:11,168 - PropVG - INFO - sucessfully save the results to work_dir/refcoco-mix/refer_output_thr0.7_no-nms_no-sw_0.5_100.xlsx !!! | |