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Running
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T4
File size: 2,205 Bytes
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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
# / | \
# Resize Resize Resize # noqa
# / \ / \ / \
# RandomFlip RandomFlip RandomFlip RandomFlip RandomFlip RandomFlip # noqa
# | | | | | |
# LoadAnn LoadAnn LoadAnn LoadAnn LoadAnn LoadAnn
# | | | | | |
# PackDetIn PackDetIn PackDetIn PackDetIn PackDetIn PackDetIn # noqa
tta_pipeline = [
dict(type='LoadImageFromFile', backend_args=_backend_args),
dict(
type='TestTimeAug',
transforms=[
[
dict(type='mmdet.Resize', scale=s, keep_ratio=True)
for s in img_scales
],
[
# ``RandomFlip`` must be placed before ``Pad``, otherwise
# bounding box coordinates after flipping cannot be
# recovered correctly.
dict(type='mmdet.RandomFlip', prob=1.),
dict(type='mmdet.RandomFlip', prob=0.)
],
[
dict(
type='mmdet.Pad',
pad_to_square=True,
pad_val=dict(img=(114.0, 114.0, 114.0))),
],
[
dict(
type='mmdet.PackDetInputs',
meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape',
'scale_factor', 'flip', 'flip_direction'))
]
])
]
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