Xianbao QIAN
add Dockerfile
378b1f2
img_norm_cfg = dict(
mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
# for icdar2015
leval_prop_range_icdar2015 = ((0, 0.4), (0.3, 0.7), (0.6, 1.0))
train_pipeline_icdar2015 = [
dict(type='LoadImageFromFile', color_type='color_ignore_orientation'),
dict(
type='LoadTextAnnotations',
with_bbox=True,
with_mask=True,
poly2mask=False),
dict(
type='ColorJitter',
brightness=32.0 / 255,
saturation=0.5,
contrast=0.5),
dict(type='Normalize', **img_norm_cfg),
dict(type='RandomScaling', size=800, scale=(3. / 4, 5. / 2)),
dict(
type='RandomCropFlip', crop_ratio=0.5, iter_num=1, min_area_ratio=0.2),
dict(
type='RandomCropPolyInstances',
instance_key='gt_masks',
crop_ratio=0.8,
min_side_ratio=0.3),
dict(
type='RandomRotatePolyInstances',
rotate_ratio=0.5,
max_angle=30,
pad_with_fixed_color=False),
dict(type='SquareResizePad', target_size=800, pad_ratio=0.6),
dict(type='RandomFlip', flip_ratio=0.5, direction='horizontal'),
dict(type='Pad', size_divisor=32),
dict(
type='FCENetTargets',
fourier_degree=5,
level_proportion_range=leval_prop_range_icdar2015),
dict(
type='CustomFormatBundle',
keys=['p3_maps', 'p4_maps', 'p5_maps'],
visualize=dict(flag=False, boundary_key=None)),
dict(type='Collect', keys=['img', 'p3_maps', 'p4_maps', 'p5_maps'])
]
img_scale_icdar2015 = (2260, 2260)
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='Normalize', **img_norm_cfg),
dict(type='Pad', size_divisor=32),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img']),
])
]
# for ctw1500
leval_prop_range_ctw1500 = ((0, 0.25), (0.2, 0.65), (0.55, 1.0))
train_pipeline_ctw1500 = [
dict(type='LoadImageFromFile', color_type='color_ignore_orientation'),
dict(
type='LoadTextAnnotations',
with_bbox=True,
with_mask=True,
poly2mask=False),
dict(
type='ColorJitter',
brightness=32.0 / 255,
saturation=0.5,
contrast=0.5),
dict(type='Normalize', **img_norm_cfg),
dict(type='RandomScaling', size=800, scale=(3. / 4, 5. / 2)),
dict(
type='RandomCropFlip', crop_ratio=0.5, iter_num=1, min_area_ratio=0.2),
dict(
type='RandomCropPolyInstances',
instance_key='gt_masks',
crop_ratio=0.8,
min_side_ratio=0.3),
dict(
type='RandomRotatePolyInstances',
rotate_ratio=0.5,
max_angle=30,
pad_with_fixed_color=False),
dict(type='SquareResizePad', target_size=800, pad_ratio=0.6),
dict(type='RandomFlip', flip_ratio=0.5, direction='horizontal'),
dict(type='Pad', size_divisor=32),
dict(
type='FCENetTargets',
fourier_degree=5,
level_proportion_range=leval_prop_range_ctw1500),
dict(
type='CustomFormatBundle',
keys=['p3_maps', 'p4_maps', 'p5_maps'],
visualize=dict(flag=False, boundary_key=None)),
dict(type='Collect', keys=['img', 'p3_maps', 'p4_maps', 'p5_maps'])
]
img_scale_ctw1500 = (1080, 736)
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='Normalize', **img_norm_cfg),
dict(type='Pad', size_divisor=32),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img']),
])
]