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# TODO: Need to solve the problem of multiple backend_args parameters
# _backend_args = dict(
# backend='petrel',
# path_mapping=dict({
# './data/': 's3://openmmlab/datasets/detection/',
# 'data/': 's3://openmmlab/datasets/detection/'
# }))
_backend_args = None
tta_model = dict(
type='mmdet.DetTTAModel',
tta_cfg=dict(nms=dict(type='nms', iou_threshold=0.65), max_per_img=300))
img_scales = [(640, 640), (320, 320), (960, 960)]
# LoadImageFromFile
# / | \
# (RatioResize,LetterResize) (RatioResize,LetterResize) (RatioResize,LetterResize) # noqa
# / \ / \ / \
# RandomFlip RandomFlip RandomFlip RandomFlip RandomFlip RandomFlip # noqa
# | | | | | |
# LoadAnn LoadAnn LoadAnn LoadAnn LoadAnn LoadAnn
# | | | | | |
# PackDetIn PackDetIn PackDetIn PackDetIn PackDetIn PackDetIn # noqa
_multiscale_resize_transforms = [
dict(
type='Compose',
transforms=[
dict(type='YOLOv5KeepRatioResize', scale=s),
dict(
type='LetterResize',
scale=s,
allow_scale_up=False,
pad_val=dict(img=114))
]) for s in img_scales
]
tta_pipeline = [
dict(type='LoadImageFromFile', backend_args=_backend_args),
dict(
type='TestTimeAug',
transforms=[
_multiscale_resize_transforms,
[
dict(type='mmdet.RandomFlip', prob=1.),
dict(type='mmdet.RandomFlip', prob=0.)
], [dict(type='mmdet.LoadAnnotations', with_bbox=True)],
[
dict(
type='mmdet.PackDetInputs',
meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape',
'scale_factor', 'pad_param', 'flip',
'flip_direction'))
]
])
]
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