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[Refactor] Support TTA #2184

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merged 20 commits into from
Dec 30, 2022
Merged

[Refactor] Support TTA #2184

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c9a51ee
tta init
xiexinch Oct 13, 2022
34607db
use mmcv transform
xiexinch Oct 13, 2022
af22643
Merge remote-tracking branch 'upstream/dev-1.x' into tta
xiexinch Nov 15, 2022
a56af2f
test city
xiexinch Nov 18, 2022
b9ebfe5
Merge remote-tracking branch 'upstream/dev-1.x' into tta
xiexinch Nov 18, 2022
6bc603c
add multiscale
xiexinch Nov 18, 2022
0e7e918
fix merge
xiexinch Nov 19, 2022
6244bfe
add softmax to post process
xiexinch Nov 21, 2022
6d7e7af
add ut
xiexinch Nov 22, 2022
7b0f94e
add tta pipeline to other datasets
xiexinch Nov 22, 2022
059fc0d
remove softmax
xiexinch Nov 22, 2022
f61e5ee
add encoder_decoder_tta ut
xiexinch Nov 28, 2022
df06a80
add encoder_decoder_tta ut
xiexinch Nov 28, 2022
ee3c0ed
rename
xiexinch Dec 28, 2022
ba54baa
rename file
xiexinch Dec 28, 2022
7c20f67
rename config
xiexinch Dec 28, 2022
061862c
rm aug_test
xiexinch Dec 28, 2022
fd611c2
move flip to post process
xiexinch Dec 29, 2022
570626f
fix channel
xiexinch Dec 29, 2022
bb46d9b
Merge remote-tracking branch 'upstream/dev-1.x' into tta
xiexinch Dec 29, 2022
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16 changes: 16 additions & 0 deletions configs/_base_/datasets/ade20k.py
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Expand Up @@ -23,6 +23,22 @@
dict(type='LoadAnnotations', reduce_zero_label=True),
dict(type='PackSegInputs')
]
img_ratios = [0.5, 0.75, 1.0, 1.25, 1.5, 1.75]
tta_pipeline = [
dict(type='LoadImageFromFile', file_client_args=dict(backend='disk')),
dict(
type='TestTimeAug',
transforms=[
[
dict(type='Resize', scale_factor=r, keep_ratio=True)
for r in img_ratios
],
[
dict(type='RandomFlip', prob=0., direction='horizontal'),
dict(type='RandomFlip', prob=1., direction='horizontal')
], [dict(type='LoadAnnotations')], [dict(type='PackSegInputs')]
])
]
train_dataloader = dict(
batch_size=4,
num_workers=4,
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16 changes: 16 additions & 0 deletions configs/_base_/datasets/ade20k_640x640.py
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Expand Up @@ -23,6 +23,22 @@
dict(type='LoadAnnotations', reduce_zero_label=True),
dict(type='PackSegInputs')
]
img_ratios = [0.5, 0.75, 1.0, 1.25, 1.5, 1.75]
tta_pipeline = [
dict(type='LoadImageFromFile', file_client_args=dict(backend='disk')),
dict(
type='TestTimeAug',
transforms=[
[
dict(type='Resize', scale_factor=r, keep_ratio=True)
for r in img_ratios
],
[
dict(type='RandomFlip', prob=0., direction='horizontal'),
dict(type='RandomFlip', prob=1., direction='horizontal')
], [dict(type='LoadAnnotations')], [dict(type='PackSegInputs')]
])
]
train_dataloader = dict(
batch_size=4,
num_workers=4,
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16 changes: 16 additions & 0 deletions configs/_base_/datasets/chase_db1.py
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Expand Up @@ -24,6 +24,22 @@
dict(type='LoadAnnotations'),
dict(type='PackSegInputs')
]
img_ratios = [0.5, 0.75, 1.0, 1.25, 1.5, 1.75]
tta_pipeline = [
dict(type='LoadImageFromFile', file_client_args=dict(backend='disk')),
dict(
type='TestTimeAug',
transforms=[
[
dict(type='Resize', scale_factor=r, keep_ratio=True)
for r in img_ratios
],
[
dict(type='RandomFlip', prob=0., direction='horizontal'),
dict(type='RandomFlip', prob=1., direction='horizontal')
], [dict(type='LoadAnnotations')], [dict(type='PackSegInputs')]
])
]

train_dataloader = dict(
batch_size=4,
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16 changes: 16 additions & 0 deletions configs/_base_/datasets/cityscapes.py
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Expand Up @@ -23,6 +23,22 @@
dict(type='LoadAnnotations'),
dict(type='PackSegInputs')
]
img_ratios = [0.5, 0.75, 1.0, 1.25, 1.5, 1.75]
tta_pipeline = [
dict(type='LoadImageFromFile', file_client_args=dict(backend='disk')),
dict(
type='TestTimeAug',
transforms=[
[
dict(type='Resize', scale_factor=r, keep_ratio=True)
for r in img_ratios
],
[
dict(type='RandomFlip', prob=0., direction='horizontal'),
dict(type='RandomFlip', prob=1., direction='horizontal')
], [dict(type='LoadAnnotations')], [dict(type='PackSegInputs')]
])
]
train_dataloader = dict(
batch_size=2,
num_workers=2,
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16 changes: 16 additions & 0 deletions configs/_base_/datasets/coco-stuff10k.py
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Expand Up @@ -23,6 +23,22 @@
dict(type='LoadAnnotations', reduce_zero_label=True),
dict(type='PackSegInputs')
]
img_ratios = [0.5, 0.75, 1.0, 1.25, 1.5, 1.75]
tta_pipeline = [
dict(type='LoadImageFromFile', file_client_args=dict(backend='disk')),
dict(
type='TestTimeAug',
transforms=[
[
dict(type='Resize', scale_factor=r, keep_ratio=True)
for r in img_ratios
],
[
dict(type='RandomFlip', prob=0., direction='horizontal'),
dict(type='RandomFlip', prob=1., direction='horizontal')
], [dict(type='LoadAnnotations')], [dict(type='PackSegInputs')]
])
]
train_dataloader = dict(
batch_size=4,
num_workers=4,
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16 changes: 16 additions & 0 deletions configs/_base_/datasets/coco-stuff164k.py
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Original file line number Diff line number Diff line change
Expand Up @@ -23,6 +23,22 @@
dict(type='LoadAnnotations'),
dict(type='PackSegInputs')
]
img_ratios = [0.5, 0.75, 1.0, 1.25, 1.5, 1.75]
tta_pipeline = [
dict(type='LoadImageFromFile', file_client_args=dict(backend='disk')),
dict(
type='TestTimeAug',
transforms=[
[
dict(type='Resize', scale_factor=r, keep_ratio=True)
for r in img_ratios
],
[
dict(type='RandomFlip', prob=0., direction='horizontal'),
dict(type='RandomFlip', prob=1., direction='horizontal')
], [dict(type='LoadAnnotations')], [dict(type='PackSegInputs')]
])
]
train_dataloader = dict(
batch_size=4,
num_workers=4,
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16 changes: 16 additions & 0 deletions configs/_base_/datasets/drive.py
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Original file line number Diff line number Diff line change
Expand Up @@ -24,6 +24,22 @@
dict(type='LoadAnnotations'),
dict(type='PackSegInputs')
]
img_ratios = [0.5, 0.75, 1.0, 1.25, 1.5, 1.75]
tta_pipeline = [
dict(type='LoadImageFromFile', file_client_args=dict(backend='disk')),
dict(
type='TestTimeAug',
transforms=[
[
dict(type='Resize', scale_factor=r, keep_ratio=True)
for r in img_ratios
],
[
dict(type='RandomFlip', prob=0., direction='horizontal'),
dict(type='RandomFlip', prob=1., direction='horizontal')
], [dict(type='LoadAnnotations')], [dict(type='PackSegInputs')]
])
]
train_dataloader = dict(
batch_size=4,
num_workers=4,
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16 changes: 16 additions & 0 deletions configs/_base_/datasets/hrf.py
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Original file line number Diff line number Diff line change
Expand Up @@ -24,6 +24,22 @@
dict(type='LoadAnnotations'),
dict(type='PackSegInputs')
]
img_ratios = [0.5, 0.75, 1.0, 1.25, 1.5, 1.75]
tta_pipeline = [
dict(type='LoadImageFromFile', file_client_args=dict(backend='disk')),
dict(
type='TestTimeAug',
transforms=[
[
dict(type='Resize', scale_factor=r, keep_ratio=True)
for r in img_ratios
],
[
dict(type='RandomFlip', prob=0., direction='horizontal'),
dict(type='RandomFlip', prob=1., direction='horizontal')
], [dict(type='LoadAnnotations')], [dict(type='PackSegInputs')]
])
]
train_dataloader = dict(
batch_size=4,
num_workers=4,
Expand Down
16 changes: 16 additions & 0 deletions configs/_base_/datasets/isaid.py
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Expand Up @@ -30,6 +30,22 @@
dict(type='LoadAnnotations'),
dict(type='PackSegInputs')
]
img_ratios = [0.5, 0.75, 1.0, 1.25, 1.5, 1.75]
tta_pipeline = [
dict(type='LoadImageFromFile', file_client_args=dict(backend='disk')),
dict(
type='TestTimeAug',
transforms=[
[
dict(type='Resize', scale_factor=r, keep_ratio=True)
for r in img_ratios
],
[
dict(type='RandomFlip', prob=0., direction='horizontal'),
dict(type='RandomFlip', prob=1., direction='horizontal')
], [dict(type='LoadAnnotations')], [dict(type='PackSegInputs')]
])
]
train_dataloader = dict(
batch_size=4,
num_workers=4,
Expand Down
16 changes: 16 additions & 0 deletions configs/_base_/datasets/loveda.py
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Expand Up @@ -23,6 +23,22 @@
dict(type='LoadAnnotations', reduce_zero_label=True),
dict(type='PackSegInputs')
]
img_ratios = [0.5, 0.75, 1.0, 1.25, 1.5, 1.75]
tta_pipeline = [
dict(type='LoadImageFromFile', file_client_args=dict(backend='disk')),
dict(
type='TestTimeAug',
transforms=[
[
dict(type='Resize', scale_factor=r, keep_ratio=True)
for r in img_ratios
],
[
dict(type='RandomFlip', prob=0., direction='horizontal'),
dict(type='RandomFlip', prob=1., direction='horizontal')
], [dict(type='LoadAnnotations')], [dict(type='PackSegInputs')]
])
]
train_dataloader = dict(
batch_size=4,
num_workers=4,
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16 changes: 16 additions & 0 deletions configs/_base_/datasets/pascal_context_59.py
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Expand Up @@ -26,6 +26,22 @@
dict(type='LoadAnnotations', reduce_zero_label=True),
dict(type='PackSegInputs')
]
img_ratios = [0.5, 0.75, 1.0, 1.25, 1.5, 1.75]
tta_pipeline = [
dict(type='LoadImageFromFile', file_client_args=dict(backend='disk')),
dict(
type='TestTimeAug',
transforms=[
[
dict(type='Resize', scale_factor=r, keep_ratio=True)
for r in img_ratios
],
[
dict(type='RandomFlip', prob=0., direction='horizontal'),
dict(type='RandomFlip', prob=1., direction='horizontal')
], [dict(type='LoadAnnotations')], [dict(type='PackSegInputs')]
])
]
train_dataloader = dict(
batch_size=4,
num_workers=4,
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16 changes: 16 additions & 0 deletions configs/_base_/datasets/pascal_voc12.py
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Expand Up @@ -23,6 +23,22 @@
dict(type='LoadAnnotations'),
dict(type='PackSegInputs')
]
img_ratios = [0.5, 0.75, 1.0, 1.25, 1.5, 1.75]
tta_pipeline = [
dict(type='LoadImageFromFile', file_client_args=dict(backend='disk')),
dict(
type='TestTimeAug',
transforms=[
[
dict(type='Resize', scale_factor=r, keep_ratio=True)
for r in img_ratios
],
[
dict(type='RandomFlip', prob=0., direction='horizontal'),
dict(type='RandomFlip', prob=1., direction='horizontal')
], [dict(type='LoadAnnotations')], [dict(type='PackSegInputs')]
])
]
train_dataloader = dict(
batch_size=4,
num_workers=4,
Expand Down
17 changes: 16 additions & 1 deletion configs/_base_/datasets/pascal_voc12_aug.py
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Expand Up @@ -25,7 +25,22 @@
dict(type='LoadAnnotations'),
dict(type='PackSegInputs')
]

img_ratios = [0.5, 0.75, 1.0, 1.25, 1.5, 1.75]
tta_pipeline = [
dict(type='LoadImageFromFile', file_client_args=dict(backend='disk')),
dict(
type='TestTimeAug',
transforms=[
[
dict(type='Resize', scale_factor=r, keep_ratio=True)
for r in img_ratios
],
[
dict(type='RandomFlip', prob=0., direction='horizontal'),
dict(type='RandomFlip', prob=1., direction='horizontal')
], [dict(type='LoadAnnotations')], [dict(type='PackSegInputs')]
])
]
dataset_train = dict(
type=dataset_type,
data_root=data_root,
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16 changes: 16 additions & 0 deletions configs/_base_/datasets/potsdam.py
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Expand Up @@ -23,6 +23,22 @@
dict(type='LoadAnnotations', reduce_zero_label=True),
dict(type='PackSegInputs')
]
img_ratios = [0.5, 0.75, 1.0, 1.25, 1.5, 1.75]
tta_pipeline = [
dict(type='LoadImageFromFile', file_client_args=dict(backend='disk')),
dict(
type='TestTimeAug',
transforms=[
[
dict(type='Resize', scale_factor=r, keep_ratio=True)
for r in img_ratios
],
[
dict(type='RandomFlip', prob=0., direction='horizontal'),
dict(type='RandomFlip', prob=1., direction='horizontal')
], [dict(type='LoadAnnotations')], [dict(type='PackSegInputs')]
])
]
train_dataloader = dict(
batch_size=4,
num_workers=4,
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16 changes: 16 additions & 0 deletions configs/_base_/datasets/stare.py
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Expand Up @@ -24,6 +24,22 @@
dict(type='LoadAnnotations'),
dict(type='PackSegInputs')
]
img_ratios = [0.5, 0.75, 1.0, 1.25, 1.5, 1.75]
tta_pipeline = [
dict(type='LoadImageFromFile', file_client_args=dict(backend='disk')),
dict(
type='TestTimeAug',
transforms=[
[
dict(type='Resize', scale_factor=r, keep_ratio=True)
for r in img_ratios
],
[
dict(type='RandomFlip', prob=0., direction='horizontal'),
dict(type='RandomFlip', prob=1., direction='horizontal')
], [dict(type='LoadAnnotations')], [dict(type='PackSegInputs')]
])
]
train_dataloader = dict(
batch_size=4,
num_workers=4,
Expand Down
16 changes: 16 additions & 0 deletions configs/_base_/datasets/vaihingen.py
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Expand Up @@ -23,6 +23,22 @@
dict(type='LoadAnnotations', reduce_zero_label=True),
dict(type='PackSegInputs')
]
img_ratios = [0.5, 0.75, 1.0, 1.25, 1.5, 1.75]
tta_pipeline = [
dict(type='LoadImageFromFile', file_client_args=dict(backend='disk')),
dict(
type='TestTimeAug',
transforms=[
[
dict(type='Resize', scale_factor=r, keep_ratio=True)
for r in img_ratios
],
[
dict(type='RandomFlip', prob=0., direction='horizontal'),
dict(type='RandomFlip', prob=1., direction='horizontal')
], [dict(type='LoadAnnotations')], [dict(type='PackSegInputs')]
])
]
train_dataloader = dict(
batch_size=4,
num_workers=4,
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2 changes: 2 additions & 0 deletions configs/_base_/default_runtime.py
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Expand Up @@ -11,3 +11,5 @@
log_level = 'INFO'
load_from = None
resume = False

tta_model = dict(type='SegTTAModel')
5 changes: 4 additions & 1 deletion mmseg/models/segmentors/__init__.py
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Expand Up @@ -2,5 +2,8 @@
from .base import BaseSegmentor
from .cascade_encoder_decoder import CascadeEncoderDecoder
from .encoder_decoder import EncoderDecoder
from .seg_tta import SegTTAModel

__all__ = ['BaseSegmentor', 'EncoderDecoder', 'CascadeEncoderDecoder']
__all__ = [
'BaseSegmentor', 'EncoderDecoder', 'CascadeEncoderDecoder', 'SegTTAModel'
]
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