82 lines
2.0 KiB
Python
82 lines
2.0 KiB
Python
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# data settings
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data_preprocessor = dict(
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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(
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type='PackInputs',
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algorithm_keys=['question', 'gt_answer', 'gt_answer_weight'],
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meta_keys=['question_id', '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=(480, 480),
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interpolation='bicubic',
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backend='pillow'),
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dict(
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type='CleanCaption',
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keys=['question'],
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),
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dict(
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type='PackInputs',
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algorithm_keys=['question', 'gt_answer', 'gt_answer_weight'],
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meta_keys=['question_id', 'image_id'],
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),
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]
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train_dataloader = dict(
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batch_size=16,
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num_workers=8,
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dataset=dict(
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type='GQA',
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data_root='data/gqa',
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data_prefix='images',
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ann_file='annotations/train_balanced_questions.json',
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pipeline=test_pipeline),
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sampler=dict(type='DefaultSampler', shuffle=False),
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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=8,
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dataset=dict(
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type='GQA',
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data_root='data/gqa',
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data_prefix='images',
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ann_file='annotations/testdev_balanced_questions.json',
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pipeline=test_pipeline),
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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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val_evaluator = dict(type='GQAAcc')
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test_dataloader = dict(
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batch_size=16,
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num_workers=8,
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dataset=dict(
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type='GQA',
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data_root='data/gqa',
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data_prefix='images',
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ann_file='annotations/testdev_balanced_questions.json',
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pipeline=test_pipeline),
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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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test_evaluator = val_evaluator
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