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PaddleDetection
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af4ef80e
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PaddleDetection
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af4ef80e
编写于
3月 05, 2019
作者:
D
dengkaipeng
浏览文件
操作
浏览文件
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电子邮件补丁
差异文件
fix API.spec not add defaults. test=develop
上级
0d1a9996
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
66 addition
and
13 deletion
+66
-13
paddle/fluid/API.spec
paddle/fluid/API.spec
+1
-1
paddle/fluid/operators/detection/yolov3_loss_op.cc
paddle/fluid/operators/detection/yolov3_loss_op.cc
+2
-1
paddle/fluid/operators/detection/yolov3_loss_op.h
paddle/fluid/operators/detection/yolov3_loss_op.h
+26
-2
python/paddle/fluid/tests/unittests/test_yolov3_loss_op.py
python/paddle/fluid/tests/unittests/test_yolov3_loss_op.py
+37
-9
未找到文件。
paddle/fluid/API.spec
浏览文件 @
af4ef80e
...
...
@@ -327,7 +327,7 @@ paddle.fluid.layers.generate_mask_labels (ArgSpec(args=['im_info', 'gt_classes',
paddle.fluid.layers.iou_similarity (ArgSpec(args=['x', 'y', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '587845f60c5d97ffdf2dfd21da52eca1'))
paddle.fluid.layers.box_coder (ArgSpec(args=['prior_box', 'prior_box_var', 'target_box', 'code_type', 'box_normalized', 'name', 'axis'], varargs=None, keywords=None, defaults=('encode_center_size', True, None, 0)), ('document', '032d0f4b7d8f6235ee5d91e473344f0e'))
paddle.fluid.layers.polygon_box_transform (ArgSpec(args=['input', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '0e5ac2507723a0b5adec473f9556799b'))
paddle.fluid.layers.yolov3_loss (ArgSpec(args=['x', 'gtbox', 'gtlabel', 'anchors', 'anchor_mask', 'class_num', 'ignore_thresh', 'downsample_ratio', 'name'
], varargs=None, keywords=None, defaults=(None,
)), ('document', '991e934c3e09abf0edec7c9c978b4691'))
paddle.fluid.layers.yolov3_loss (ArgSpec(args=['x', 'gtbox', 'gtlabel', 'anchors', 'anchor_mask', 'class_num', 'ignore_thresh', 'downsample_ratio', 'name'
, 'gtscore', 'use_label_smooth'], varargs=None, keywords=None, defaults=(None, None, True
)), ('document', '991e934c3e09abf0edec7c9c978b4691'))
paddle.fluid.layers.box_clip (ArgSpec(args=['input', 'im_info', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '397e9e02b451d99c56e20f268fa03f2e'))
paddle.fluid.layers.multiclass_nms (ArgSpec(args=['bboxes', 'scores', 'score_threshold', 'nms_top_k', 'keep_top_k', 'nms_threshold', 'normalized', 'nms_eta', 'background_label', 'name'], varargs=None, keywords=None, defaults=(0.3, True, 1.0, 0, None)), ('document', 'ca7d1107b6c5d2d6d8221039a220fde0'))
paddle.fluid.layers.distribute_fpn_proposals (ArgSpec(args=['fpn_rois', 'min_level', 'max_level', 'refer_level', 'refer_scale', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '7bb011ec26bace2bc23235aa4a17647d'))
...
...
paddle/fluid/operators/detection/yolov3_loss_op.cc
浏览文件 @
af4ef80e
...
...
@@ -128,7 +128,8 @@ class Yolov3LossOpMaker : public framework::OpProtoAndCheckerMaker {
"The score of GTLabel, This is a 2-D tensor in same shape "
"GTLabel, and score values should in range (0, 1). This "
"input is for GTLabel score can be not 1.0 in image mixup "
"augmentation."
);
"augmentation."
)
.
AsDispensable
();
AddOutput
(
"Loss"
,
"The output yolov3 loss tensor, "
"This is a 1-D tensor with shape of [N]"
);
...
...
paddle/fluid/operators/detection/yolov3_loss_op.h
浏览文件 @
af4ef80e
...
...
@@ -289,7 +289,6 @@ class Yolov3LossKernel : public framework::OpKernel<T> {
const
T
*
input_data
=
input
->
data
<
T
>
();
const
T
*
gt_box_data
=
gt_box
->
data
<
T
>
();
const
int
*
gt_label_data
=
gt_label
->
data
<
int
>
();
const
T
*
gt_score_data
=
gt_score
->
data
<
T
>
();
T
*
loss_data
=
loss
->
mutable_data
<
T
>
({
n
},
ctx
.
GetPlace
());
memset
(
loss_data
,
0
,
loss
->
numel
()
*
sizeof
(
T
));
T
*
obj_mask_data
=
...
...
@@ -298,6 +297,19 @@ class Yolov3LossKernel : public framework::OpKernel<T> {
int
*
gt_match_mask_data
=
gt_match_mask
->
mutable_data
<
int
>
({
n
,
b
},
ctx
.
GetPlace
());
const
T
*
gt_score_data
;
if
(
!
gt_score
)
{
Tensor
_gt_score
;
_gt_score
.
mutable_data
<
T
>
({
n
,
b
},
ctx
.
GetPlace
());
math
::
SetConstant
<
platform
::
CPUDeviceContext
,
T
>
()(
ctx
.
template
device_context
<
platform
::
CPUDeviceContext
>(),
&
_gt_score
,
static_cast
<
T
>
(
1.0
));
gt_score
=
&
_gt_score
;
gt_score_data
=
_gt_score
.
data
<
T
>
();
}
else
{
gt_score_data
=
gt_score
->
data
<
T
>
();
}
// calc valid gt box mask, avoid calc duplicately in following code
Tensor
gt_valid_mask
;
bool
*
gt_valid_mask_data
=
...
...
@@ -432,7 +444,6 @@ class Yolov3LossGradKernel : public framework::OpKernel<T> {
const
T
*
input_data
=
input
->
data
<
T
>
();
const
T
*
gt_box_data
=
gt_box
->
data
<
T
>
();
const
int
*
gt_label_data
=
gt_label
->
data
<
int
>
();
const
T
*
gt_score_data
=
gt_score
->
data
<
T
>
();
const
T
*
loss_grad_data
=
loss_grad
->
data
<
T
>
();
const
T
*
obj_mask_data
=
objness_mask
->
data
<
T
>
();
const
int
*
gt_match_mask_data
=
gt_match_mask
->
data
<
int
>
();
...
...
@@ -440,6 +451,19 @@ class Yolov3LossGradKernel : public framework::OpKernel<T> {
input_grad
->
mutable_data
<
T
>
({
n
,
c
,
h
,
w
},
ctx
.
GetPlace
());
memset
(
input_grad_data
,
0
,
input_grad
->
numel
()
*
sizeof
(
T
));
const
T
*
gt_score_data
;
if
(
!
gt_score
)
{
Tensor
_gt_score
;
_gt_score
.
mutable_data
<
T
>
({
n
,
b
},
ctx
.
GetPlace
());
math
::
SetConstant
<
platform
::
CPUDeviceContext
,
T
>
()(
ctx
.
template
device_context
<
platform
::
CPUDeviceContext
>(),
&
_gt_score
,
static_cast
<
T
>
(
1.0
));
gt_score
=
&
_gt_score
;
gt_score_data
=
_gt_score
.
data
<
T
>
();
}
else
{
gt_score_data
=
gt_score
->
data
<
T
>
();
}
for
(
int
i
=
0
;
i
<
n
;
i
++
)
{
for
(
int
t
=
0
;
t
<
b
;
t
++
)
{
int
mask_idx
=
gt_match_mask_data
[
i
*
b
+
t
];
...
...
python/paddle/fluid/tests/unittests/test_yolov3_loss_op.py
浏览文件 @
af4ef80e
...
...
@@ -168,7 +168,6 @@ class TestYolov3LossOp(OpTest):
x
=
logit
(
np
.
random
.
uniform
(
0
,
1
,
self
.
x_shape
).
astype
(
'float32'
))
gtbox
=
np
.
random
.
random
(
size
=
self
.
gtbox_shape
).
astype
(
'float32'
)
gtlabel
=
np
.
random
.
randint
(
0
,
self
.
class_num
,
self
.
gtbox_shape
[:
2
])
gtscore
=
np
.
random
.
random
(
self
.
gtbox_shape
[:
2
]).
astype
(
'float32'
)
gtmask
=
np
.
random
.
randint
(
0
,
2
,
self
.
gtbox_shape
[:
2
])
gtbox
=
gtbox
*
gtmask
[:,
:,
np
.
newaxis
]
gtlabel
=
gtlabel
*
gtmask
...
...
@@ -186,8 +185,13 @@ class TestYolov3LossOp(OpTest):
'X'
:
x
,
'GTBox'
:
gtbox
.
astype
(
'float32'
),
'GTLabel'
:
gtlabel
.
astype
(
'int32'
),
'GTScore'
:
gtscore
.
astype
(
'float32'
)
}
gtscore
=
np
.
ones
(
self
.
gtbox_shape
[:
2
]).
astype
(
'float32'
)
if
self
.
gtscore
:
gtscore
=
np
.
random
.
random
(
self
.
gtbox_shape
[:
2
]).
astype
(
'float32'
)
self
.
inputs
[
'GTScore'
]
=
gtscore
loss
,
objness
,
gt_matches
=
YOLOv3Loss
(
x
,
gtbox
,
gtlabel
,
gtscore
,
self
.
attrs
)
self
.
outputs
=
{
...
...
@@ -202,11 +206,7 @@ class TestYolov3LossOp(OpTest):
def
test_check_grad_ignore_gtbox
(
self
):
place
=
core
.
CPUPlace
()
self
.
check_grad_with_place
(
place
,
[
'X'
],
'Loss'
,
no_grad_set
=
set
([
"GTBox"
,
"GTLabel"
,
"GTScore"
]),
max_relative_error
=
0.2
)
self
.
check_grad_with_place
(
place
,
[
'X'
],
'Loss'
,
max_relative_error
=
0.2
)
def
initTestCase
(
self
):
self
.
anchors
=
[
...
...
@@ -215,17 +215,45 @@ class TestYolov3LossOp(OpTest):
]
self
.
anchor_mask
=
[
0
,
1
,
2
]
self
.
class_num
=
5
self
.
ignore_thresh
=
0.
5
self
.
ignore_thresh
=
0.
7
self
.
downsample_ratio
=
32
self
.
x_shape
=
(
3
,
len
(
self
.
anchor_mask
)
*
(
5
+
self
.
class_num
),
5
,
5
)
self
.
gtbox_shape
=
(
3
,
5
,
4
)
self
.
gtscore
=
True
self
.
use_label_smooth
=
True
class
TestYolov3LossWithoutLabelSmooth
(
TestYolov3LossOp
):
def
set_label_smooth
(
self
):
def
initTestCase
(
self
):
self
.
anchors
=
[
10
,
13
,
16
,
30
,
33
,
23
,
30
,
61
,
62
,
45
,
59
,
119
,
116
,
90
,
156
,
198
,
373
,
326
]
self
.
anchor_mask
=
[
0
,
1
,
2
]
self
.
class_num
=
5
self
.
ignore_thresh
=
0.7
self
.
downsample_ratio
=
32
self
.
x_shape
=
(
3
,
len
(
self
.
anchor_mask
)
*
(
5
+
self
.
class_num
),
5
,
5
)
self
.
gtbox_shape
=
(
3
,
5
,
4
)
self
.
gtscore
=
True
self
.
use_label_smooth
=
False
class
TestYolov3LossNoGTScore
(
TestYolov3LossOp
):
def
initTestCase
(
self
):
self
.
anchors
=
[
10
,
13
,
16
,
30
,
33
,
23
,
30
,
61
,
62
,
45
,
59
,
119
,
116
,
90
,
156
,
198
,
373
,
326
]
self
.
anchor_mask
=
[
0
,
1
,
2
]
self
.
class_num
=
5
self
.
ignore_thresh
=
0.7
self
.
downsample_ratio
=
32
self
.
x_shape
=
(
3
,
len
(
self
.
anchor_mask
)
*
(
5
+
self
.
class_num
),
5
,
5
)
self
.
gtbox_shape
=
(
3
,
5
,
4
)
self
.
gtscore
=
False
self
.
use_label_smooth
=
True
if
__name__
==
"__main__"
:
unittest
.
main
()
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