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flickr30k_caption.py 2.32 KB
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# data settings

data_preprocessor = dict(
    type='MultiModalDataPreprocessor',
    mean=[122.770938, 116.7460125, 104.09373615],
    std=[68.5005327, 66.6321579, 70.32316305],
    to_rgb=True,
)

train_pipeline = [
    dict(type='LoadImageFromFile'),
    dict(
        type='RandomResizedCrop',
        scale=384,
        interpolation='bicubic',
        backend='pillow'),
    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
    dict(type='CleanCaption', keys='gt_caption'),
    dict(
        type='PackInputs',
        algorithm_keys=['gt_caption'],
        meta_keys=['image_id'],
    ),
]

test_pipeline = [
    dict(type='LoadImageFromFile'),
    dict(
        type='Resize',
        scale=(384, 384),
        interpolation='bicubic',
        backend='pillow'),
    dict(type='PackInputs', meta_keys=['image_id']),
]

train_dataloader = dict(
    batch_size=32,
    num_workers=5,
    dataset=dict(
        type='Flickr30kCaption',
        data_root='data/flickr30k',
        ann_file='annotations/dataset_flickr30k.json',
        data_prefix='images',
        split='train',
        pipeline=train_pipeline),
    sampler=dict(type='DefaultSampler', shuffle=True),
    persistent_workers=True,
    drop_last=True,
)

val_dataloader = dict(
    batch_size=16,
    num_workers=5,
    dataset=dict(
        type='Flickr30kCaption',
        data_root='data/flickr30k',
        ann_file='annotations/dataset_flickr30k.json',
        data_prefix='images',
        split='val',
        pipeline=test_pipeline,
    ),
    sampler=dict(type='DefaultSampler', shuffle=False),
    persistent_workers=True,
)

# refer tools/dataset_converters/convert_flickr30k_ann.py
val_evaluator = dict(
    type='COCOCaption',
    ann_file='data/flickr30k_val_gt.json',
)

# # If you want standard test, please manually configure the test dataset
test_dataloader = dict(
    batch_size=16,
    num_workers=5,
    dataset=dict(
        type='Flickr30kCaption',
        data_root='data/flickr30k',
        ann_file='annotations/dataset_flickr30k.json',
        data_prefix='images',
        split='test',
        pipeline=test_pipeline,
    ),
    sampler=dict(type='DefaultSampler', shuffle=False),
    persistent_workers=True,
)

# refer tools/dataset_converters/convert_flickr30k_ann.py
test_evaluator = dict(
    type='COCOCaption',
    ann_file='data/flickr30k_test_gt.json',
)