93 lines
2.3 KiB
Python
93 lines
2.3 KiB
Python
# data settings
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data_preprocessor = dict(
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type='MultiModalDataPreprocessor',
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mean=[122.770938, 116.7460125, 104.09373615],
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std=[68.5005327, 66.6321579, 70.32316305],
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to_rgb=True,
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)
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train_pipeline = [
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dict(type='LoadImageFromFile'),
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dict(
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type='RandomResizedCrop',
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scale=384,
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interpolation='bicubic',
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backend='pillow'),
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dict(type='RandomFlip', prob=0.5, direction='horizontal'),
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dict(type='CleanCaption', keys='gt_caption'),
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dict(
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type='PackInputs',
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algorithm_keys=['gt_caption'],
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meta_keys=['image_id'],
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),
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]
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test_pipeline = [
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dict(type='LoadImageFromFile'),
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dict(
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type='Resize',
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scale=(384, 384),
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interpolation='bicubic',
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backend='pillow'),
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dict(type='PackInputs', meta_keys=['image_id']),
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]
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train_dataloader = dict(
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batch_size=32,
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num_workers=5,
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dataset=dict(
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type='Flickr30kCaption',
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data_root='data/flickr30k',
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ann_file='annotations/dataset_flickr30k.json',
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data_prefix='images',
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split='train',
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pipeline=train_pipeline),
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sampler=dict(type='DefaultSampler', shuffle=True),
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persistent_workers=True,
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drop_last=True,
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)
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val_dataloader = dict(
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batch_size=16,
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num_workers=5,
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dataset=dict(
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type='Flickr30kCaption',
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data_root='data/flickr30k',
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ann_file='annotations/dataset_flickr30k.json',
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data_prefix='images',
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split='val',
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pipeline=test_pipeline,
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),
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sampler=dict(type='DefaultSampler', shuffle=False),
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persistent_workers=True,
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)
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# refer tools/dataset_converters/convert_flickr30k_ann.py
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val_evaluator = dict(
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type='COCOCaption',
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ann_file='data/flickr30k_val_gt.json',
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)
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# # If you want standard test, please manually configure the test dataset
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test_dataloader = dict(
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batch_size=16,
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num_workers=5,
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dataset=dict(
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type='Flickr30kCaption',
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data_root='data/flickr30k',
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ann_file='annotations/dataset_flickr30k.json',
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data_prefix='images',
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split='test',
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pipeline=test_pipeline,
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),
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sampler=dict(type='DefaultSampler', shuffle=False),
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persistent_workers=True,
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)
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# refer tools/dataset_converters/convert_flickr30k_ann.py
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test_evaluator = dict(
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type='COCOCaption',
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ann_file='data/flickr30k_test_gt.json',
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)
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