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PaddleDetection
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5afa83e5
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体验新版 GitCode,发现更多精彩内容 >>
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5afa83e5
编写于
1月 13, 2021
作者:
G
Guanghua Yu
提交者:
GitHub
1月 13, 2021
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电子邮件补丁
差异文件
fix framework warning in solov2 (#2052)
上级
8dfbd86a
变更
5
隐藏空白更改
内联
并排
Showing
5 changed file
with
37 addition
and
21 deletion
+37
-21
ppdet/core/workspace.py
ppdet/core/workspace.py
+6
-1
ppdet/modeling/anchor_heads/solov2_head.py
ppdet/modeling/anchor_heads/solov2_head.py
+9
-7
ppdet/modeling/backbones/fpn.py
ppdet/modeling/backbones/fpn.py
+2
-1
ppdet/modeling/losses/solov2_loss.py
ppdet/modeling/losses/solov2_loss.py
+6
-4
ppdet/modeling/ops.py
ppdet/modeling/ops.py
+14
-8
未找到文件。
ppdet/core/workspace.py
浏览文件 @
5afa83e5
...
@@ -24,6 +24,11 @@ import yaml
...
@@ -24,6 +24,11 @@ import yaml
import
copy
import
copy
import
collections
import
collections
try
:
collectionsAbc
=
collections
.
abc
except
AttributeError
:
collectionsAbc
=
collections
from
.config.schema
import
SchemaDict
,
SharedConfig
,
extract_schema
from
.config.schema
import
SchemaDict
,
SharedConfig
,
extract_schema
from
.config.yaml_helpers
import
serializable
from
.config.yaml_helpers
import
serializable
...
@@ -115,7 +120,7 @@ def dict_merge(dct, merge_dct):
...
@@ -115,7 +120,7 @@ def dict_merge(dct, merge_dct):
"""
"""
for
k
,
v
in
merge_dct
.
items
():
for
k
,
v
in
merge_dct
.
items
():
if
(
k
in
dct
and
isinstance
(
dct
[
k
],
dict
)
and
if
(
k
in
dct
and
isinstance
(
dct
[
k
],
dict
)
and
isinstance
(
merge_dct
[
k
],
collections
.
Mapping
)):
isinstance
(
merge_dct
[
k
],
collections
Abc
.
Mapping
)):
dict_merge
(
dct
[
k
],
merge_dct
[
k
])
dict_merge
(
dct
[
k
],
merge_dct
[
k
])
else
:
else
:
dct
[
k
]
=
merge_dct
[
k
]
dct
[
k
]
=
merge_dct
[
k
]
...
...
ppdet/modeling/anchor_heads/solov2_head.py
浏览文件 @
5afa83e5
...
@@ -132,8 +132,9 @@ class SOLOv2Head(object):
...
@@ -132,8 +132,9 @@ class SOLOv2Head(object):
def
_points_nms
(
self
,
heat
,
kernel
=
2
):
def
_points_nms
(
self
,
heat
,
kernel
=
2
):
hmax
=
fluid
.
layers
.
pool2d
(
hmax
=
fluid
.
layers
.
pool2d
(
input
=
heat
,
pool_size
=
kernel
,
pool_type
=
'max'
,
pool_padding
=
1
)
input
=
heat
,
pool_size
=
kernel
,
pool_type
=
'max'
,
pool_padding
=
1
)
keep
=
fluid
.
layers
.
cast
((
hmax
[:,
:,
:
-
1
,
:
-
1
]
==
heat
),
'float32'
)
keep
=
fluid
.
layers
.
cast
(
return
heat
*
keep
paddle
.
equal
(
hmax
[:,
:,
:
-
1
,
:
-
1
],
heat
),
'float32'
)
return
paddle
.
multiply
(
heat
,
keep
)
def
_split_feats
(
self
,
feats
):
def
_split_feats
(
self
,
feats
):
return
(
paddle
.
nn
.
functional
.
interpolate
(
return
(
paddle
.
nn
.
functional
.
interpolate
(
...
@@ -376,7 +377,7 @@ class SOLOv2Head(object):
...
@@ -376,7 +377,7 @@ class SOLOv2Head(object):
strides
.
append
(
strides
.
append
(
fluid
.
layers
.
fill_constant
(
fluid
.
layers
.
fill_constant
(
shape
=
[
int
(
size_trans
[
_ind
])],
shape
=
[
int
(
size_trans
[
_ind
])],
dtype
=
"
in
t32"
,
dtype
=
"
floa
t32"
,
value
=
self
.
segm_strides
[
_ind
]))
value
=
self
.
segm_strides
[
_ind
]))
strides
=
fluid
.
layers
.
concat
(
strides
)
strides
=
fluid
.
layers
.
concat
(
strides
)
strides
=
fluid
.
layers
.
gather
(
strides
,
index
=
inds
[:,
0
])
strides
=
fluid
.
layers
.
gather
(
strides
,
index
=
inds
[:,
0
])
...
@@ -389,7 +390,7 @@ class SOLOv2Head(object):
...
@@ -389,7 +390,7 @@ class SOLOv2Head(object):
seg_masks
=
fluid
.
layers
.
cast
(
seg_masks
,
'float32'
)
seg_masks
=
fluid
.
layers
.
cast
(
seg_masks
,
'float32'
)
sum_masks
=
fluid
.
layers
.
reduce_sum
(
seg_masks
,
dim
=
[
1
,
2
])
sum_masks
=
fluid
.
layers
.
reduce_sum
(
seg_masks
,
dim
=
[
1
,
2
])
keep
=
fluid
.
layers
.
where
(
sum_masks
>
strides
)
keep
=
fluid
.
layers
.
where
(
paddle
.
greater_than
(
sum_masks
,
strides
)
)
keep
=
fluid
.
layers
.
squeeze
(
keep
,
axes
=
[
1
])
keep
=
fluid
.
layers
.
squeeze
(
keep
,
axes
=
[
1
])
# Prevent empty and increase fake data
# Prevent empty and increase fake data
keep_other
=
fluid
.
layers
.
concat
([
keep_other
=
fluid
.
layers
.
concat
([
...
@@ -409,9 +410,10 @@ class SOLOv2Head(object):
...
@@ -409,9 +410,10 @@ class SOLOv2Head(object):
cate_scores
=
fluid
.
layers
.
gather
(
cate_scores
,
index
=
keep_scores
)
cate_scores
=
fluid
.
layers
.
gather
(
cate_scores
,
index
=
keep_scores
)
# mask scoring.
# mask scoring.
seg_mul
=
fluid
.
layers
.
cast
(
seg_preds
*
seg_masks
,
'float32'
)
seg_mul
=
fluid
.
layers
.
cast
(
seg_scores
=
fluid
.
layers
.
reduce_sum
(
seg_mul
,
dim
=
[
1
,
2
])
/
sum_masks
paddle
.
multiply
(
seg_preds
,
seg_masks
),
'float32'
)
cate_scores
*=
seg_scores
seg_scores
=
paddle
.
divide
(
paddle
.
sum
(
seg_mul
,
axis
=
[
1
,
2
]),
sum_masks
)
cate_scores
=
paddle
.
multiply
(
cate_scores
,
seg_scores
)
# Matrix NMS
# Matrix NMS
seg_preds
,
cate_scores
,
cate_labels
=
self
.
mask_nms
(
seg_preds
,
cate_scores
,
cate_labels
=
self
.
mask_nms
(
...
...
ppdet/modeling/backbones/fpn.py
浏览文件 @
5afa83e5
...
@@ -18,6 +18,7 @@ from __future__ import print_function
...
@@ -18,6 +18,7 @@ from __future__ import print_function
from
collections
import
OrderedDict
from
collections
import
OrderedDict
import
copy
import
copy
import
paddle
from
paddle
import
fluid
from
paddle
import
fluid
from
paddle.fluid.param_attr
import
ParamAttr
from
paddle.fluid.param_attr
import
ParamAttr
from
paddle.fluid.initializer
import
Xavier
from
paddle.fluid.initializer
import
Xavier
...
@@ -105,7 +106,7 @@ class FPN(object):
...
@@ -105,7 +106,7 @@ class FPN(object):
out_shape
=
[
body_input
.
shape
[
2
],
body_input
.
shape
[
3
]],
out_shape
=
[
body_input
.
shape
[
2
],
body_input
.
shape
[
3
]],
name
=
topdown_name
)
name
=
topdown_name
)
return
lateral
+
topdown
return
paddle
.
add
(
lateral
,
topdown
)
def
get_output
(
self
,
body_dict
):
def
get_output
(
self
,
body_dict
):
"""
"""
...
...
ppdet/modeling/losses/solov2_loss.py
浏览文件 @
5afa83e5
...
@@ -48,10 +48,12 @@ class SOLOv2Loss(object):
...
@@ -48,10 +48,12 @@ class SOLOv2Loss(object):
target
=
fluid
.
layers
.
reshape
(
target
=
fluid
.
layers
.
reshape
(
target
,
shape
=
(
fluid
.
layers
.
shape
(
target
)[
0
],
-
1
))
target
,
shape
=
(
fluid
.
layers
.
shape
(
target
)[
0
],
-
1
))
target
=
fluid
.
layers
.
cast
(
target
,
'float32'
)
target
=
fluid
.
layers
.
cast
(
target
,
'float32'
)
a
=
fluid
.
layers
.
reduce_sum
(
input
*
target
,
dim
=
1
)
a
=
fluid
.
layers
.
reduce_sum
(
paddle
.
multiply
(
input
,
target
),
dim
=
1
)
b
=
fluid
.
layers
.
reduce_sum
(
input
*
input
,
dim
=
1
)
+
0.001
b
=
fluid
.
layers
.
reduce_sum
(
c
=
fluid
.
layers
.
reduce_sum
(
target
*
target
,
dim
=
1
)
+
0.001
paddle
.
multiply
(
input
,
input
),
dim
=
1
)
+
0.001
d
=
(
2
*
a
)
/
(
b
+
c
)
c
=
fluid
.
layers
.
reduce_sum
(
paddle
.
multiply
(
target
,
target
),
dim
=
1
)
+
0.001
d
=
paddle
.
divide
((
2
*
a
),
paddle
.
add
(
b
,
c
))
return
1
-
d
return
1
-
d
def
__call__
(
self
,
ins_pred_list
,
ins_label_list
,
cate_preds
,
cate_labels
,
def
__call__
(
self
,
ins_pred_list
,
ins_label_list
,
cate_preds
,
cate_labels
,
...
...
ppdet/modeling/ops.py
浏览文件 @
5afa83e5
...
@@ -1642,8 +1642,12 @@ class MaskMatrixNMS(object):
...
@@ -1642,8 +1642,12 @@ class MaskMatrixNMS(object):
sum_masks
,
expand_times
=
[
n_samples
]),
sum_masks
,
expand_times
=
[
n_samples
]),
shape
=
[
n_samples
,
n_samples
])
shape
=
[
n_samples
,
n_samples
])
# iou.
# iou.
iou_matrix
=
(
inter_matrix
/
(
sum_masks_x
+
fluid
.
layers
.
transpose
(
iou_matrix
=
paddle
.
divide
(
inter_matrix
,
sum_masks_x
,
[
1
,
0
])
-
inter_matrix
))
paddle
.
subtract
(
paddle
.
add
(
sum_masks_x
,
fluid
.
layers
.
transpose
(
sum_masks_x
,
[
1
,
0
])),
inter_matrix
))
iou_matrix
=
paddle
.
triu
(
iou_matrix
,
diagonal
=
1
)
iou_matrix
=
paddle
.
triu
(
iou_matrix
,
diagonal
=
1
)
# label_specific matrix.
# label_specific matrix.
cate_labels_x
=
fluid
.
layers
.
reshape
(
cate_labels_x
=
fluid
.
layers
.
reshape
(
...
@@ -1651,12 +1655,14 @@ class MaskMatrixNMS(object):
...
@@ -1651,12 +1655,14 @@ class MaskMatrixNMS(object):
cate_labels
,
expand_times
=
[
n_samples
]),
cate_labels
,
expand_times
=
[
n_samples
]),
shape
=
[
n_samples
,
n_samples
])
shape
=
[
n_samples
,
n_samples
])
label_matrix
=
fluid
.
layers
.
cast
(
label_matrix
=
fluid
.
layers
.
cast
(
(
cate_labels_x
==
fluid
.
layers
.
transpose
(
cate_labels_x
,
[
1
,
0
])),
paddle
.
equal
(
cate_labels_x
,
fluid
.
layers
.
transpose
(
cate_labels_x
,
[
1
,
0
])),
'float32'
)
'float32'
)
label_matrix
=
paddle
.
triu
(
label_matrix
,
diagonal
=
1
)
label_matrix
=
paddle
.
triu
(
label_matrix
,
diagonal
=
1
)
# IoU compensation
# IoU compensation
compensate_iou
=
paddle
.
max
((
iou_matrix
*
label_matrix
),
axis
=
0
)
compensate_iou
=
paddle
.
max
(
paddle
.
multiply
(
iou_matrix
,
label_matrix
),
axis
=
0
)
compensate_iou
=
fluid
.
layers
.
reshape
(
compensate_iou
=
fluid
.
layers
.
reshape
(
fluid
.
layers
.
expand
(
fluid
.
layers
.
expand
(
compensate_iou
,
expand_times
=
[
n_samples
]),
compensate_iou
,
expand_times
=
[
n_samples
]),
...
@@ -1664,15 +1670,15 @@ class MaskMatrixNMS(object):
...
@@ -1664,15 +1670,15 @@ class MaskMatrixNMS(object):
compensate_iou
=
fluid
.
layers
.
transpose
(
compensate_iou
,
[
1
,
0
])
compensate_iou
=
fluid
.
layers
.
transpose
(
compensate_iou
,
[
1
,
0
])
# IoU decay
# IoU decay
decay_iou
=
iou_matrix
*
label_matrix
decay_iou
=
paddle
.
multiply
(
iou_matrix
,
label_matrix
)
# matrix nms
# matrix nms
if
self
.
kernel
==
'gaussian'
:
if
self
.
kernel
==
'gaussian'
:
decay_matrix
=
fluid
.
layers
.
exp
(
-
1
*
self
.
sigma
*
(
decay_iou
**
2
))
decay_matrix
=
fluid
.
layers
.
exp
(
-
1
*
self
.
sigma
*
(
decay_iou
**
2
))
compensate_matrix
=
fluid
.
layers
.
exp
(
-
1
*
self
.
sigma
*
compensate_matrix
=
fluid
.
layers
.
exp
(
-
1
*
self
.
sigma
*
(
compensate_iou
**
2
))
(
compensate_iou
**
2
))
decay_coefficient
=
paddle
.
min
(
decay_matrix
/
compensate_matrix
,
decay_coefficient
=
paddle
.
min
(
axis
=
0
)
paddle
.
divide
(
decay_matrix
,
compensate_matrix
),
axis
=
0
)
elif
self
.
kernel
==
'linear'
:
elif
self
.
kernel
==
'linear'
:
decay_matrix
=
(
1
-
decay_iou
)
/
(
1
-
compensate_iou
)
decay_matrix
=
(
1
-
decay_iou
)
/
(
1
-
compensate_iou
)
decay_coefficient
=
paddle
.
min
(
decay_matrix
,
axis
=
0
)
decay_coefficient
=
paddle
.
min
(
decay_matrix
,
axis
=
0
)
...
@@ -1680,7 +1686,7 @@ class MaskMatrixNMS(object):
...
@@ -1680,7 +1686,7 @@ class MaskMatrixNMS(object):
raise
NotImplementedError
raise
NotImplementedError
# update the score.
# update the score.
cate_scores
=
cate_scores
*
decay_coefficient
cate_scores
=
paddle
.
multiply
(
cate_scores
,
decay_coefficient
)
keep
=
fluid
.
layers
.
where
(
cate_scores
>=
self
.
update_threshold
)
keep
=
fluid
.
layers
.
where
(
cate_scores
>=
self
.
update_threshold
)
keep
=
fluid
.
layers
.
squeeze
(
keep
,
axes
=
[
1
])
keep
=
fluid
.
layers
.
squeeze
(
keep
,
axes
=
[
1
])
...
...
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