dino_train_pipeline = [
dict(type='LoadImageFromFile', backend_args=None),
dict(type='LoadAnnotations', with_bbox=True, with_mask=True),
dict(type='RandomFlip', prob=1.0),
dict(
type='RandomChoice',
transforms=[
[
dict(
type='RandomChoiceResize',
scales=[(480, 1333), (512, 1333), (544, 1333), (576, 1333),
(608, 1333), (640, 1333), (672, 1333), (704, 1333),
(736, 1333), (768, 1333), (800, 1333)],
# scales=(480,1333),
keep_ratio=True)
],
[
dict(
type='RandomChoiceResize',
# The radio of all image in train dataset < 7
# follow the original implement
scales=[(400, 4200), (500, 4200), (600, 4200)],
keep_ratio=True),
dict(
type='RandomCrop',
crop_type='absolute_range',
crop_size=(384, 600),
allow_negative_crop=True),
dict(
type='RandomChoiceResize',
scales=[(480, 1333), (512, 1333), (544, 1333), (576, 1333),
(608, 1333), (640, 1333), (672, 1333), (704, 1333),
(736, 1333), (768, 1333), (800, 1333)],
keep_ratio=True)
]
]),
dict(type='PackDetInputs',
meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape',
'scale_factor', 'flip', 'flip_direction', 'crop_index', 'scale_factor_list', 'random_choice_idx',
'pre_pad_size', 'pre_crop_size', 'pre_resize_shape_list'
)
)
]数据增强后效果(使用数据集的label、bbox、mask来模拟模型输出的效果)
还原到原图上效果
trm_det_train_pipeline = [
dict(backend_args=None, type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True, with_mask=True),
# dict(
# type='CachedMosaic',
# img_scale=(640, 640),
# pad_val=114.0,
# max_cached_images=20,
# random_pop=False),
dict(
type='RandomResize',
scale=(1280, 1280),
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=(640, 640)),
dict(type='YOLOXHSVRandomAug'),
dict(type='RandomFlip', prob=1.0),
dict(type='Pad', size=(800, 800), pad_val=dict(img=(114, 114, 114))),
dict(type='PackDetInputs',
meta_keys=(
'img_id', 'img_path', 'ori_shape', 'img_shape',
'scale_factor', 'flip', 'flip_direction', 'crop_index', 'scale_factor_list',
'pre_pad_size', 'pre_crop_size'
)
)
]模拟模型输出结果
还原到原图上效果
mask_rcnn_train_pipeline = [
dict(type='LoadImageFromFile', backend_args=None),
dict(type='LoadAnnotations', with_bbox=True, with_mask=True),
dict(type='Resize', scale=(1333, 800), keep_ratio=True),
dict(type='RandomFlip', prob=1.0),
dict(type='PackDetInputs',
meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape',
'scale_factor', 'flip', 'flip_direction', 'crop_index', 'scale_factor_list',
'pre_pad_size', 'pre_crop_size'
)
)
]模拟模型输出结果
还原到原图上效果
