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Commit e3c1b855 authored by Kai Chen's avatar Kai Chen
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refactoring for sampler and assigner

parent 65a2e5ea
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Showing with 156 additions and 108 deletions
configs/cascade_mask_rcnn_r101_fpn_1x.py
View file @ e3c1b855
...@@ -77,17 +77,17 @@ model = dict( ...@@ -77,17 +77,17 @@ model = dict(
train_cfg = dict( train_cfg = dict(
rpn=dict( rpn=dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.7, pos_iou_thr=0.7,
neg_iou_thr=0.3, neg_iou_thr=0.3,
min_pos_iou=0.3, min_pos_iou=0.3,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=256, num=256,
pos_fraction=0.5, pos_fraction=0.5,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=False, add_gt_as_proposals=False),
pos_balance_sampling=False,
neg_balance_thr=0),
allowed_border=0, allowed_border=0,
pos_weight=-1, pos_weight=-1,
smoothl1_beta=1 / 9.0, smoothl1_beta=1 / 9.0,
...@@ -95,49 +95,49 @@ train_cfg = dict( ...@@ -95,49 +95,49 @@ train_cfg = dict(
rcnn=[ rcnn=[
dict( dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.5, pos_iou_thr=0.5,
neg_iou_thr=0.5, neg_iou_thr=0.5,
min_pos_iou=0.5, min_pos_iou=0.5,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=512, num=512,
pos_fraction=0.25, pos_fraction=0.25,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=True, add_gt_as_proposals=True),
pos_balance_sampling=False,
neg_balance_thr=0),
mask_size=28, mask_size=28,
pos_weight=-1, pos_weight=-1,
debug=False), debug=False),
dict( dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.6, pos_iou_thr=0.6,
neg_iou_thr=0.6, neg_iou_thr=0.6,
min_pos_iou=0.6, min_pos_iou=0.6,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=512, num=512,
pos_fraction=0.25, pos_fraction=0.25,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=True, add_gt_as_proposals=True),
pos_balance_sampling=False,
neg_balance_thr=0),
mask_size=28, mask_size=28,
pos_weight=-1, pos_weight=-1,
debug=False), debug=False),
dict( dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.7, pos_iou_thr=0.7,
neg_iou_thr=0.7, neg_iou_thr=0.7,
min_pos_iou=0.7, min_pos_iou=0.7,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=512, num=512,
pos_fraction=0.25, pos_fraction=0.25,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=True, add_gt_as_proposals=True),
pos_balance_sampling=False,
neg_balance_thr=0),
mask_size=28, mask_size=28,
pos_weight=-1, pos_weight=-1,
debug=False) debug=False)
......
configs/cascade_mask_rcnn_r50_fpn_1x.py
View file @ e3c1b855
...@@ -77,17 +77,17 @@ model = dict( ...@@ -77,17 +77,17 @@ model = dict(
train_cfg = dict( train_cfg = dict(
rpn=dict( rpn=dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.7, pos_iou_thr=0.7,
neg_iou_thr=0.3, neg_iou_thr=0.3,
min_pos_iou=0.3, min_pos_iou=0.3,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=256, num=256,
pos_fraction=0.5, pos_fraction=0.5,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=False, add_gt_as_proposals=False),
pos_balance_sampling=False,
neg_balance_thr=0),
allowed_border=0, allowed_border=0,
pos_weight=-1, pos_weight=-1,
smoothl1_beta=1 / 9.0, smoothl1_beta=1 / 9.0,
...@@ -95,49 +95,49 @@ train_cfg = dict( ...@@ -95,49 +95,49 @@ train_cfg = dict(
rcnn=[ rcnn=[
dict( dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.5, pos_iou_thr=0.5,
neg_iou_thr=0.5, neg_iou_thr=0.5,
min_pos_iou=0.5, min_pos_iou=0.5,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=512, num=512,
pos_fraction=0.25, pos_fraction=0.25,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=True, add_gt_as_proposals=True),
pos_balance_sampling=False,
neg_balance_thr=0),
mask_size=28, mask_size=28,
pos_weight=-1, pos_weight=-1,
debug=False), debug=False),
dict( dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.6, pos_iou_thr=0.6,
neg_iou_thr=0.6, neg_iou_thr=0.6,
min_pos_iou=0.6, min_pos_iou=0.6,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=512, num=512,
pos_fraction=0.25, pos_fraction=0.25,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=True, add_gt_as_proposals=True),
pos_balance_sampling=False,
neg_balance_thr=0),
mask_size=28, mask_size=28,
pos_weight=-1, pos_weight=-1,
debug=False), debug=False),
dict( dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.7, pos_iou_thr=0.7,
neg_iou_thr=0.7, neg_iou_thr=0.7,
min_pos_iou=0.7, min_pos_iou=0.7,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=512, num=512,
pos_fraction=0.25, pos_fraction=0.25,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=True, add_gt_as_proposals=True),
pos_balance_sampling=False,
neg_balance_thr=0),
mask_size=28, mask_size=28,
pos_weight=-1, pos_weight=-1,
debug=False) debug=False)
......
configs/cascade_rcnn_r101_fpn_1x.py
View file @ e3c1b855
...@@ -66,17 +66,17 @@ model = dict( ...@@ -66,17 +66,17 @@ model = dict(
train_cfg = dict( train_cfg = dict(
rpn=dict( rpn=dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.7, pos_iou_thr=0.7,
neg_iou_thr=0.3, neg_iou_thr=0.3,
min_pos_iou=0.3, min_pos_iou=0.3,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=256, num=256,
pos_fraction=0.5, pos_fraction=0.5,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=False, add_gt_as_proposals=False),
pos_balance_sampling=False,
neg_balance_thr=0),
allowed_border=0, allowed_border=0,
pos_weight=-1, pos_weight=-1,
smoothl1_beta=1 / 9.0, smoothl1_beta=1 / 9.0,
...@@ -84,47 +84,47 @@ train_cfg = dict( ...@@ -84,47 +84,47 @@ train_cfg = dict(
rcnn=[ rcnn=[
dict( dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.5, pos_iou_thr=0.5,
neg_iou_thr=0.5, neg_iou_thr=0.5,
min_pos_iou=0.5, min_pos_iou=0.5,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=512, num=512,
pos_fraction=0.25, pos_fraction=0.25,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=True, add_gt_as_proposals=True),
pos_balance_sampling=False,
neg_balance_thr=0),
pos_weight=-1, pos_weight=-1,
debug=False), debug=False),
dict( dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.6, pos_iou_thr=0.6,
neg_iou_thr=0.6, neg_iou_thr=0.6,
min_pos_iou=0.6, min_pos_iou=0.6,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=512, num=512,
pos_fraction=0.25, pos_fraction=0.25,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=True, add_gt_as_proposals=True),
pos_balance_sampling=False,
neg_balance_thr=0),
pos_weight=-1, pos_weight=-1,
debug=False), debug=False),
dict( dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.7, pos_iou_thr=0.7,
neg_iou_thr=0.7, neg_iou_thr=0.7,
min_pos_iou=0.7, min_pos_iou=0.7,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=512, num=512,
pos_fraction=0.25, pos_fraction=0.25,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=True, add_gt_as_proposals=True),
pos_balance_sampling=False,
neg_balance_thr=0),
pos_weight=-1, pos_weight=-1,
debug=False) debug=False)
], ],
......
configs/cascade_rcnn_r50_fpn_1x.py
View file @ e3c1b855
...@@ -66,17 +66,17 @@ model = dict( ...@@ -66,17 +66,17 @@ model = dict(
train_cfg = dict( train_cfg = dict(
rpn=dict( rpn=dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.7, pos_iou_thr=0.7,
neg_iou_thr=0.3, neg_iou_thr=0.3,
min_pos_iou=0.3, min_pos_iou=0.3,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=256, num=256,
pos_fraction=0.5, pos_fraction=0.5,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=False, add_gt_as_proposals=False),
pos_balance_sampling=False,
neg_balance_thr=0),
allowed_border=0, allowed_border=0,
pos_weight=-1, pos_weight=-1,
smoothl1_beta=1 / 9.0, smoothl1_beta=1 / 9.0,
...@@ -84,47 +84,47 @@ train_cfg = dict( ...@@ -84,47 +84,47 @@ train_cfg = dict(
rcnn=[ rcnn=[
dict( dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.5, pos_iou_thr=0.5,
neg_iou_thr=0.5, neg_iou_thr=0.5,
min_pos_iou=0.5, min_pos_iou=0.5,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=512, num=512,
pos_fraction=0.25, pos_fraction=0.25,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=True, add_gt_as_proposals=True),
pos_balance_sampling=False,
neg_balance_thr=0),
pos_weight=-1, pos_weight=-1,
debug=False), debug=False),
dict( dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.6, pos_iou_thr=0.6,
neg_iou_thr=0.6, neg_iou_thr=0.6,
min_pos_iou=0.6, min_pos_iou=0.6,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=512, num=512,
pos_fraction=0.25, pos_fraction=0.25,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=True, add_gt_as_proposals=True),
pos_balance_sampling=False,
neg_balance_thr=0),
pos_weight=-1, pos_weight=-1,
debug=False), debug=False),
dict( dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.7, pos_iou_thr=0.7,
neg_iou_thr=0.7, neg_iou_thr=0.7,
min_pos_iou=0.7, min_pos_iou=0.7,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=512, num=512,
pos_fraction=0.25, pos_fraction=0.25,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=True, add_gt_as_proposals=True),
pos_balance_sampling=False,
neg_balance_thr=0),
pos_weight=-1, pos_weight=-1,
debug=False) debug=False)
], ],
......
configs/fast_mask_rcnn_r101_fpn_1x.py
View file @ e3c1b855
...@@ -44,17 +44,17 @@ model = dict( ...@@ -44,17 +44,17 @@ model = dict(
train_cfg = dict( train_cfg = dict(
rcnn=dict( rcnn=dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.5, pos_iou_thr=0.5,
neg_iou_thr=0.5, neg_iou_thr=0.5,
min_pos_iou=0.5, min_pos_iou=0.5,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=512, num=512,
pos_fraction=0.25, pos_fraction=0.25,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=True, add_gt_as_proposals=True),
pos_balance_sampling=False,
neg_balance_thr=0),
mask_size=28, mask_size=28,
pos_weight=-1, pos_weight=-1,
debug=False)) debug=False))
......
configs/fast_mask_rcnn_r50_fpn_1x.py
View file @ e3c1b855
...@@ -44,17 +44,17 @@ model = dict( ...@@ -44,17 +44,17 @@ model = dict(
train_cfg = dict( train_cfg = dict(
rcnn=dict( rcnn=dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.5, pos_iou_thr=0.5,
neg_iou_thr=0.5, neg_iou_thr=0.5,
min_pos_iou=0.5, min_pos_iou=0.5,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=512, num=512,
pos_fraction=0.25, pos_fraction=0.25,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=True, add_gt_as_proposals=True),
pos_balance_sampling=False,
neg_balance_thr=0),
mask_size=28, mask_size=28,
pos_weight=-1, pos_weight=-1,
debug=False)) debug=False))
......
configs/fast_rcnn_r101_fpn_1x.py
View file @ e3c1b855
...@@ -33,17 +33,17 @@ model = dict( ...@@ -33,17 +33,17 @@ model = dict(
train_cfg = dict( train_cfg = dict(
rcnn=dict( rcnn=dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.5, pos_iou_thr=0.5,
neg_iou_thr=0.5, neg_iou_thr=0.5,
min_pos_iou=0.5, min_pos_iou=0.5,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=512, num=512,
pos_fraction=0.25, pos_fraction=0.25,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=True, add_gt_as_proposals=True),
pos_balance_sampling=False,
neg_balance_thr=0),
pos_weight=-1, pos_weight=-1,
debug=False)) debug=False))
test_cfg = dict( test_cfg = dict(
......
configs/fast_rcnn_r50_fpn_1x.py
View file @ e3c1b855
...@@ -33,17 +33,17 @@ model = dict( ...@@ -33,17 +33,17 @@ model = dict(
train_cfg = dict( train_cfg = dict(
rcnn=dict( rcnn=dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.5, pos_iou_thr=0.5,
neg_iou_thr=0.5, neg_iou_thr=0.5,
min_pos_iou=0.5, min_pos_iou=0.5,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=512, num=512,
pos_fraction=0.25, pos_fraction=0.25,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=True, add_gt_as_proposals=True),
pos_balance_sampling=False,
neg_balance_thr=0),
pos_weight=-1, pos_weight=-1,
debug=False)) debug=False))
test_cfg = dict( test_cfg = dict(
......
configs/faster_rcnn_r101_fpn_1x.py
View file @ e3c1b855
...@@ -43,34 +43,34 @@ model = dict( ...@@ -43,34 +43,34 @@ model = dict(
train_cfg = dict( train_cfg = dict(
rpn=dict( rpn=dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.7, pos_iou_thr=0.7,
neg_iou_thr=0.3, neg_iou_thr=0.3,
min_pos_iou=0.3, min_pos_iou=0.3,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=256, num=256,
pos_fraction=0.5, pos_fraction=0.5,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=False, add_gt_as_proposals=False),
pos_balance_sampling=False,
neg_balance_thr=0),
allowed_border=0, allowed_border=0,
pos_weight=-1, pos_weight=-1,
smoothl1_beta=1 / 9.0, smoothl1_beta=1 / 9.0,
debug=False), debug=False),
rcnn=dict( rcnn=dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.5, pos_iou_thr=0.5,
neg_iou_thr=0.5, neg_iou_thr=0.5,
min_pos_iou=0.5, min_pos_iou=0.5,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=512, num=512,
pos_fraction=0.25, pos_fraction=0.25,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=True, add_gt_as_proposals=True),
pos_balance_sampling=False,
neg_balance_thr=0),
pos_weight=-1, pos_weight=-1,
debug=False)) debug=False))
test_cfg = dict( test_cfg = dict(
......
configs/faster_rcnn_r50_fpn_1x.py
View file @ e3c1b855
...@@ -43,34 +43,34 @@ model = dict( ...@@ -43,34 +43,34 @@ model = dict(
train_cfg = dict( train_cfg = dict(
rpn=dict( rpn=dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.7, pos_iou_thr=0.7,
neg_iou_thr=0.3, neg_iou_thr=0.3,
min_pos_iou=0.3, min_pos_iou=0.3,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=256, num=256,
pos_fraction=0.5, pos_fraction=0.5,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=False, add_gt_as_proposals=False),
pos_balance_sampling=False,
neg_balance_thr=0),
allowed_border=0, allowed_border=0,
pos_weight=-1, pos_weight=-1,
smoothl1_beta=1 / 9.0, smoothl1_beta=1 / 9.0,
debug=False), debug=False),
rcnn=dict( rcnn=dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.5, pos_iou_thr=0.5,
neg_iou_thr=0.5, neg_iou_thr=0.5,
min_pos_iou=0.5, min_pos_iou=0.5,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=512, num=512,
pos_fraction=0.25, pos_fraction=0.25,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=True, add_gt_as_proposals=True),
pos_balance_sampling=False,
neg_balance_thr=0),
pos_weight=-1, pos_weight=-1,
debug=False)) debug=False))
test_cfg = dict( test_cfg = dict(
......
configs/mask_rcnn_r101_fpn_1x.py
View file @ e3c1b855
...@@ -54,34 +54,34 @@ model = dict( ...@@ -54,34 +54,34 @@ model = dict(
train_cfg = dict( train_cfg = dict(
rpn=dict( rpn=dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.7, pos_iou_thr=0.7,
neg_iou_thr=0.3, neg_iou_thr=0.3,
min_pos_iou=0.3, min_pos_iou=0.3,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=256, num=256,
pos_fraction=0.5, pos_fraction=0.5,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=False, add_gt_as_proposals=False),
pos_balance_sampling=False,
neg_balance_thr=0),
allowed_border=0, allowed_border=0,
pos_weight=-1, pos_weight=-1,
smoothl1_beta=1 / 9.0, smoothl1_beta=1 / 9.0,
debug=False), debug=False),
rcnn=dict( rcnn=dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.5, pos_iou_thr=0.5,
neg_iou_thr=0.5, neg_iou_thr=0.5,
min_pos_iou=0.5, min_pos_iou=0.5,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=512, num=512,
pos_fraction=0.25, pos_fraction=0.25,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=True, add_gt_as_proposals=True),
pos_balance_sampling=False,
neg_balance_thr=0),
mask_size=28, mask_size=28,
pos_weight=-1, pos_weight=-1,
debug=False)) debug=False))
......
configs/mask_rcnn_r50_fpn_1x.py
View file @ e3c1b855
...@@ -54,34 +54,34 @@ model = dict( ...@@ -54,34 +54,34 @@ model = dict(
train_cfg = dict( train_cfg = dict(
rpn=dict( rpn=dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.7, pos_iou_thr=0.7,
neg_iou_thr=0.3, neg_iou_thr=0.3,
min_pos_iou=0.3, min_pos_iou=0.3,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=256, num=256,
pos_fraction=0.5, pos_fraction=0.5,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=False, add_gt_as_proposals=False),
pos_balance_sampling=False,
neg_balance_thr=0),
allowed_border=0, allowed_border=0,
pos_weight=-1, pos_weight=-1,
smoothl1_beta=1 / 9.0, smoothl1_beta=1 / 9.0,
debug=False), debug=False),
rcnn=dict( rcnn=dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.5, pos_iou_thr=0.5,
neg_iou_thr=0.5, neg_iou_thr=0.5,
min_pos_iou=0.5, min_pos_iou=0.5,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=512, num=512,
pos_fraction=0.25, pos_fraction=0.25,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=True, add_gt_as_proposals=True),
pos_balance_sampling=False,
neg_balance_thr=0),
mask_size=28, mask_size=28,
pos_weight=-1, pos_weight=-1,
debug=False)) debug=False))
......
configs/retinanet_r101_fpn_1x.py
View file @ e3c1b855
...@@ -31,7 +31,11 @@ model = dict( ...@@ -31,7 +31,11 @@ model = dict(
# training and testing settings # training and testing settings
train_cfg = dict( train_cfg = dict(
assigner=dict( assigner=dict(
pos_iou_thr=0.5, neg_iou_thr=0.4, min_pos_iou=0, ignore_iof_thr=-1), type='MaxIoUAssigner',
pos_iou_thr=0.5,
neg_iou_thr=0.4,
min_pos_iou=0,
ignore_iof_thr=-1),
smoothl1_beta=0.11, smoothl1_beta=0.11,
gamma=2.0, gamma=2.0,
alpha=0.25, alpha=0.25,
......
configs/retinanet_r50_fpn_1x.py
View file @ e3c1b855
...@@ -31,7 +31,11 @@ model = dict( ...@@ -31,7 +31,11 @@ model = dict(
# training and testing settings # training and testing settings
train_cfg = dict( train_cfg = dict(
assigner=dict( assigner=dict(
pos_iou_thr=0.5, neg_iou_thr=0.4, min_pos_iou=0, ignore_iof_thr=-1), type='MaxIoUAssigner',
pos_iou_thr=0.5,
neg_iou_thr=0.4,
min_pos_iou=0,
ignore_iof_thr=-1),
smoothl1_beta=0.11, smoothl1_beta=0.11,
gamma=2.0, gamma=2.0,
alpha=0.25, alpha=0.25,
......
configs/rpn_r101_fpn_1x.py
View file @ e3c1b855
...@@ -28,17 +28,17 @@ model = dict( ...@@ -28,17 +28,17 @@ model = dict(
train_cfg = dict( train_cfg = dict(
rpn=dict( rpn=dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.7, pos_iou_thr=0.7,
neg_iou_thr=0.3, neg_iou_thr=0.3,
min_pos_iou=0.3, min_pos_iou=0.3,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=256, num=256,
pos_fraction=0.5, pos_fraction=0.5,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=False, add_gt_as_proposals=False),
pos_balance_sampling=False,
neg_balance_thr=0),
allowed_border=0, allowed_border=0,
pos_weight=-1, pos_weight=-1,
smoothl1_beta=1 / 9.0, smoothl1_beta=1 / 9.0,
......
configs/rpn_r50_fpn_1x.py
View file @ e3c1b855
...@@ -28,17 +28,17 @@ model = dict( ...@@ -28,17 +28,17 @@ model = dict(
train_cfg = dict( train_cfg = dict(
rpn=dict( rpn=dict(
assigner=dict( assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.7, pos_iou_thr=0.7,
neg_iou_thr=0.3, neg_iou_thr=0.3,
min_pos_iou=0.3, min_pos_iou=0.3,
ignore_iof_thr=-1), ignore_iof_thr=-1),
sampler=dict( sampler=dict(
type='RandomSampler',
num=256, num=256,
pos_fraction=0.5, pos_fraction=0.5,
neg_pos_ub=-1, neg_pos_ub=-1,
add_gt_as_proposals=False, add_gt_as_proposals=False),
pos_balance_sampling=False,
neg_balance_thr=0),
allowed_border=0, allowed_border=0,
pos_weight=-1, pos_weight=-1,
smoothl1_beta=1 / 9.0, smoothl1_beta=1 / 9.0,
......
mmdet/core/anchor/anchor_target.py
View file @ e3c1b855
import torch import torch
from ..bbox import assign_and_sample, BBoxAssigner, SamplingResult, bbox2delta from ..bbox import assign_and_sample, build_assigner, PseudoSampler, bbox2delta
from ..utils import multi_apply from ..utils import multi_apply
...@@ -107,16 +107,12 @@ def anchor_target_single(flat_anchors, ...@@ -107,16 +107,12 @@ def anchor_target_single(flat_anchors,
assign_result, sampling_result = assign_and_sample( assign_result, sampling_result = assign_and_sample(
anchors, gt_bboxes, None, None, cfg) anchors, gt_bboxes, None, None, cfg)
else: else:
bbox_assigner = BBoxAssigner(**cfg.assigner) bbox_assigner = build_assigner(cfg.assigner)
assign_result = bbox_assigner.assign(anchors, gt_bboxes, None, assign_result = bbox_assigner.assign(anchors, gt_bboxes, None,
gt_labels) gt_labels)
pos_inds = torch.nonzero( bbox_sampler = PseudoSampler()
assign_result.gt_inds > 0).squeeze(-1).unique() sampling_result = bbox_sampler.sample(assign_result, anchors,
neg_inds = torch.nonzero( gt_bboxes)
assign_result.gt_inds == 0).squeeze(-1).unique()
gt_flags = anchors.new_zeros(anchors.shape[0], dtype=torch.uint8)
sampling_result = SamplingResult(pos_inds, neg_inds, anchors,
gt_bboxes, assign_result, gt_flags)
num_valid_anchors = anchors.shape[0] num_valid_anchors = anchors.shape[0]
bbox_targets = torch.zeros_like(anchors) bbox_targets = torch.zeros_like(anchors)
......
mmdet/core/bbox/__init__.py
View file @ e3c1b855
from .geometry import bbox_overlaps from .geometry import bbox_overlaps
from .assignment import BBoxAssigner, AssignResult from .assigners import BaseAssigner, MaxIoUAssigner, AssignResult
from .sampling import (BBoxSampler, SamplingResult, assign_and_sample, from .samplers import (BaseSampler, PseudoSampler, RandomSampler,
random_choice) InstanceBalancedPosSampler, IoUBalancedNegSampler,
CombinedSampler, SamplingResult)
from .assign_sampling import build_assigner, build_sampler, assign_and_sample
from .transforms import (bbox2delta, delta2bbox, bbox_flip, bbox_mapping, from .transforms import (bbox2delta, delta2bbox, bbox_flip, bbox_mapping,
bbox_mapping_back, bbox2roi, roi2bbox, bbox2result) bbox_mapping_back, bbox2roi, roi2bbox, bbox2result)
from .bbox_target import bbox_target from .bbox_target import bbox_target
__all__ = [ __all__ = [
'bbox_overlaps', 'BBoxAssigner', 'AssignResult', 'BBoxSampler', 'bbox_overlaps', 'BaseAssigner', 'MaxIoUAssigner', 'AssignResult',
'SamplingResult', 'assign_and_sample', 'random_choice', 'bbox2delta', 'BaseSampler', 'PseudoSampler', 'RandomSampler',
'delta2bbox', 'bbox_flip', 'bbox_mapping', 'bbox_mapping_back', 'bbox2roi', 'InstanceBalancedPosSampler', 'IoUBalancedNegSampler', 'CombinedSampler',
'roi2bbox', 'bbox2result', 'bbox_target' 'SamplingResult', 'build_assigner', 'build_sampler', 'assign_and_sample',
'bbox2delta', 'delta2bbox', 'bbox_flip', 'bbox_mapping',
'bbox_mapping_back', 'bbox2roi', 'roi2bbox', 'bbox2result', 'bbox_target'
] ]
mmdet/core/bbox/assign_sampling.py 0 → 100644
View file @ e3c1b855
import mmcv
from . import assigners, samplers
def build_assigner(cfg, default_args=None):
if isinstance(cfg, assigners.BaseAssigner):
return cfg
elif isinstance(cfg, dict):
return mmcv.runner.obj_from_dict(
cfg, assigners, default_args=default_args)
else:
raise TypeError('Invalid type {} for building a sampler'.format(
type(cfg)))
def build_sampler(cfg, default_args=None):
if isinstance(cfg, samplers.BaseSampler):
return cfg
elif isinstance(cfg, dict):
return mmcv.runner.obj_from_dict(
cfg, samplers, default_args=default_args)
else:
raise TypeError('Invalid type {} for building a sampler'.format(
type(cfg)))
def assign_and_sample(bboxes, gt_bboxes, gt_bboxes_ignore, gt_labels, cfg):
bbox_assigner = build_assigner(cfg.assigner)
bbox_sampler = build_sampler(cfg.sampler)
assign_result = bbox_assigner.assign(bboxes, gt_bboxes, gt_bboxes_ignore,
gt_labels)
sampling_result = bbox_sampler.sample(assign_result, bboxes, gt_bboxes,
gt_labels)
return assign_result, sampling_result
mmdet/core/bbox/assigners/__init__.py 0 → 100644
View file @ e3c1b855
from .base_assigner import BaseAssigner
from .max_iou_assigner import MaxIoUAssigner
from .assign_result import AssignResult
__all__ = ['BaseAssigner', 'MaxIoUAssigner', 'AssignResult']
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