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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', color_type='color_ignore_orientation'),
dict(type='LoadAnnotations', with_bbox=True, with_mask=True),
dict(
type='ScaleAspectJitter',
img_scale=None,
keep_ratio=False,
resize_type='indep_sample_in_range',
scale_range=(640, 2560)),
dict(type='RandomFlip', flip_ratio=0.5),
dict(type='Normalize', **img_norm_cfg),
dict(
type='RandomCropInstances',
target_size=(640, 640),
mask_type='union_all',
instance_key='gt_masks'),
dict(type='Pad', size_divisor=32),
dict(type='DefaultFormatBundle'),
dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels', 'gt_masks']),
]
# for ctw1500
img_scale_ctw1500 = (1600, 1600)
test_pipeline_ctw1500 = [
dict(type='LoadImageFromFile', color_type='color_ignore_orientation'),
dict(
type='MultiScaleFlipAug',
img_scale=img_scale_ctw1500, # used by Resize
flip=False,
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(type='Normalize', **img_norm_cfg),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img']),
])
]
# for icdar2015
img_scale_icdar2015 = (1920, 1920)
test_pipeline_icdar2015 = [
dict(type='LoadImageFromFile', color_type='color_ignore_orientation'),
dict(
type='MultiScaleFlipAug',
img_scale=img_scale_icdar2015, # used by Resize
flip=False,
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(type='Normalize', **img_norm_cfg),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img']),
])
]
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