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# dataset settings
dataset_type = 'SceneGraphDataset'
ann_file = '/mnt/ssd/gzj/data/VisualGenome/data_openpsg.json'
img_dir = '/mnt/ssd/gzj/data/VisualGenome/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, with_rel=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='SceneGraphFormatBundle'),
dict(type='Collect',
keys=['img', 'gt_bboxes', 'gt_labels', 'gt_rels', 'gt_relmaps']),
]
test_pipeline = [
dict(type='LoadImageFromFile'),
# Since the forward process may need gt info, annos must be loaded.
dict(type='LoadSceneGraphAnnotations', with_bbox=True, with_rel=True),
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),
# NOTE: Do not change the img to DC.
dict(type='ImageToTensor', keys=['img']),
dict(type='ToTensor', keys=['gt_bboxes', 'gt_labels']),
dict(type='ToDataContainer',
fields=(dict(key='gt_bboxes'), dict(key='gt_labels'))),
dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels']),
])
]
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'))
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