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| # dataset settings | |
| custom_imports = dict(imports=[ | |
| 'openpsg.datasets', | |
| 'openpsg.datasets.pipelines', | |
| ], | |
| allow_failed_imports=False) | |
| dataset_type = 'SceneGraphDataset' | |
| ann_file = 'data/vg/data_openpsg.json' | |
| img_dir = 'data/vg/VG_100K' | |
| img_norm_cfg = dict(mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375], | |
| to_rgb=True) | |
| train_pipeline = [ | |
| dict(type='LoadImageFromFile'), | |
| dict(type='LoadSceneGraphAnnotations', with_bbox=True), | |
| dict(type='Resize', img_scale=(1333, 800), keep_ratio=True), | |
| dict(type='RandomFlip', flip_ratio=0.5), | |
| dict(type='Normalize', **img_norm_cfg), | |
| dict(type='Pad', size_divisor=32), | |
| dict(type='DefaultFormatBundle'), | |
| dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels']), | |
| ] | |
| test_pipeline = [ | |
| dict(type='LoadImageFromFile'), | |
| dict(type='MultiScaleFlipAug', | |
| img_scale=(1333, 800), | |
| flip=False, | |
| transforms=[ | |
| dict(type='Resize', keep_ratio=True), | |
| dict(type='RandomFlip'), | |
| dict(type='Normalize', **img_norm_cfg), | |
| dict(type='Pad', size_divisor=32), | |
| dict(type='ImageToTensor', keys=['img']), | |
| dict(type='Collect', keys=['img']), | |
| ]) | |
| ] | |
| data = dict(samples_per_gpu=2, | |
| workers_per_gpu=2, | |
| train=dict(type=dataset_type, | |
| ann_file=ann_file, | |
| img_prefix=img_dir, | |
| pipeline=train_pipeline, | |
| split='train'), | |
| val=dict(type=dataset_type, | |
| ann_file=ann_file, | |
| img_prefix=img_dir, | |
| pipeline=test_pipeline, | |
| split='test'), | |
| test=dict(type=dataset_type, | |
| ann_file=ann_file, | |
| img_prefix=img_dir, | |
| pipeline=test_pipeline, | |
| split='test')) | |
| evaluation = dict(interval=1, metric='bbox') | |