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b83e39ef
编写于
2月 15, 2021
作者:
F
Feng Ni
提交者:
GitHub
2月 15, 2021
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差异文件
[dygraph] from_config for hrnet, test=dygraph (#2218)
* from_config hrnet, test=dygraph * update hrnet modelzoo, test=dygraph
上级
28e5a3ab
变更
5
隐藏空白更改
内联
并排
Showing
5 changed file
with
82 addition
and
67 deletion
+82
-67
dygraph/configs/hrnet/README.md
dygraph/configs/hrnet/README.md
+4
-4
dygraph/configs/hrnet/_base_/faster_rcnn_hrnetv2p_w18.yml
dygraph/configs/hrnet/_base_/faster_rcnn_hrnetv2p_w18.yml
+31
-51
dygraph/configs/hrnet/faster_rcnn_hrnetv2p_w18_1x_coco.yml
dygraph/configs/hrnet/faster_rcnn_hrnetv2p_w18_1x_coco.yml
+3
-0
dygraph/ppdet/modeling/backbones/hrnet.py
dygraph/ppdet/modeling/backbones/hrnet.py
+11
-0
dygraph/ppdet/modeling/necks/hrfpn.py
dygraph/ppdet/modeling/necks/hrfpn.py
+33
-12
未找到文件。
dygraph/configs/hrnet/README.md
浏览文件 @
b83e39ef
...
...
@@ -28,7 +28,7 @@
## Model Zoo
| Backbone | Type |
deformable Conv |
Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs |
| :---------------------- | :------------- | :---
: | :---
----: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: |
| HRNetV2p_W18 | Faster |
False | 2 | 1x | - | 35.7
| - |
[
model
](
https://paddlemodels.bj.bcebos.com/object_detection/dygraph/faster_rcnn_hrnetv2p_w18_1x_coco.pdparams
)
|
[
config
](
https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/hrnet/faster_rcnn_hrnetv2p_w18_1x_coco.yml
)
|
| HRNetV2p_W18 | Faster |
False | 2 | 2x | - | 37.7
| - |
[
model
](
https://paddlemodels.bj.bcebos.com/object_detection/dygraph/faster_rcnn_hrnetv2p_w18_2x_coco.pdparams
)
|
[
config
](
https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/hrnet/faster_rcnn_hrnetv2p_w18_2x_coco.yml
)
|
| Backbone | Type | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs |
| :---------------------- | :------------- | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: |
| HRNetV2p_W18 | Faster |
1 | 1x | - | 36.8
| - |
[
model
](
https://paddlemodels.bj.bcebos.com/object_detection/dygraph/faster_rcnn_hrnetv2p_w18_1x_coco.pdparams
)
|
[
config
](
https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/hrnet/faster_rcnn_hrnetv2p_w18_1x_coco.yml
)
|
| HRNetV2p_W18 | Faster |
1 | 2x | - | 39.0
| - |
[
model
](
https://paddlemodels.bj.bcebos.com/object_detection/dygraph/faster_rcnn_hrnetv2p_w18_2x_coco.pdparams
)
|
[
config
](
https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/hrnet/faster_rcnn_hrnetv2p_w18_2x_coco.yml
)
|
dygraph/configs/hrnet/_base_/faster_rcnn_hrnetv2p_w18.yml
浏览文件 @
b83e39ef
architecture
:
FasterRCNN
pretrain_weights
:
https://paddle-imagenet-models-name.bj.bcebos.com/HRNet_W18_C_pretrained.tar
weights
:
output/faster_rcnn_hrnetv2p_w18_1x_coco/model_final
load_static_weights
:
True
# Model Achitecture
FasterRCNN
:
# model anchor info flow
anchor
:
Anchor
proposal
:
Proposal
# model feat info flow
backbone
:
HRNet
neck
:
HRFPN
rpn_head
:
RPNHead
...
...
@@ -26,65 +20,51 @@ HRFPN:
share_conv
:
false
RPNHead
:
rpn_feat
:
name
:
RPNFeat
feat_in
:
256
feat_out
:
256
anchor_per_position
:
3
rpn_channel
:
256
Anchor
:
anchor_generator
:
name
:
AnchorGeneratorRPN
aspect_ratios
:
[
0.5
,
1.0
,
2.0
]
anchor_start_size
:
32
stride
:
[
4.
,
4.
]
anchor_target_generator
:
name
:
AnchorTargetGeneratorRPN
anchor_sizes
:
[[
32
],
[
64
],
[
128
],
[
256
],
[
512
]]
strides
:
[
4
,
8
,
16
,
32
,
64
]
rpn_target_assign
:
batch_size_per_im
:
256
fg_fraction
:
0.5
negative_overlap
:
0.3
positive_overlap
:
0.7
straddle_thresh
:
0.0
Proposal
:
proposal_generator
:
name
:
ProposalGenerator
use_random
:
True
train_proposal
:
min_size
:
0.0
nms_thresh
:
0.7
pre_nms_top_n
:
2000
post_nms_top_n
:
2000
topk_after_collect
:
True
test_proposal
:
min_size
:
0.0
nms_thresh
:
0.7
train_pre_nms_top_n
:
2000
train_post_nms_top_n
:
2000
infer_pre_nms_top_n
:
1000
infer_post_nms_top_n
:
1000
proposal_target_generator
:
name
:
ProposalTargetGenerator
batch_size_per_im
:
512
bbox_reg_weights
:
[
0.1
,
0.1
,
0.2
,
0.2
]
bg_thresh_hi
:
[
0.5
,]
bg_thresh_lo
:
[
0.0
,]
fg_thresh
:
[
0.5
,]
fg_fraction
:
0.25
pre_nms_top_n
:
1000
post_nms_top_n
:
1000
BBoxHead
:
bbox_feat
:
name
:
BBoxFeat
roi_extractor
:
name
:
RoIAlign
resolution
:
7
sampling_ratio
:
2
head_feat
:
name
:
TwoFCHead
in_dim
:
256
mlp_dim
:
1024
in_feat
:
1024
head
:
TwoFCHead
roi_extractor
:
resolution
:
7
sampling_ratio
:
0
aligned
:
True
bbox_assigner
:
BBoxAssigner
BBoxAssigner
:
batch_size_per_im
:
512
bg_thresh
:
0.5
fg_thresh
:
0.5
fg_fraction
:
0.25
use_random
:
True
TwoFCHead
:
mlp_dim
:
1024
BBoxPostProcess
:
decode
:
name
:
RCNNBox
num_classes
:
81
batch_size
:
1
decode
:
RCNNBox
nms
:
name
:
MultiClassNMS
keep_top_k
:
100
score_threshold
:
0.05
nms_threshold
:
0.5
normalized
:
true
dygraph/configs/hrnet/faster_rcnn_hrnetv2p_w18_1x_coco.yml
浏览文件 @
b83e39ef
...
...
@@ -6,6 +6,9 @@ _BASE_: [
'
../runtime.yml'
,
]
weights
:
output/faster_rcnn_hrnetv2p_w18_1x_coco/model_final
epoch
:
12
LearningRate
:
base_lr
:
0.02
schedulers
:
...
...
dygraph/ppdet/modeling/backbones/hrnet.py
浏览文件 @
b83e39ef
...
...
@@ -22,6 +22,7 @@ from numbers import Integral
import
math
from
ppdet.core.workspace
import
register
,
serializable
from
..shape_spec
import
ShapeSpec
__all__
=
[
'HRNet'
]
...
...
@@ -577,6 +578,8 @@ class HRNet(nn.Layer):
channels_2
,
channels_3
,
channels_4
=
self
.
channels
[
width
]
num_modules_2
,
num_modules_3
,
num_modules_4
=
1
,
4
,
3
self
.
_out_channels
=
channels_4
self
.
_out_strides
=
[
4
,
8
,
16
,
32
]
self
.
conv_layer1_1
=
ConvNormLayer
(
ch_in
=
3
,
...
...
@@ -666,3 +669,11 @@ class HRNet(nn.Layer):
res
.
append
(
layer
)
return
res
@
property
def
out_shape
(
self
):
return
[
ShapeSpec
(
channels
=
self
.
_out_channels
[
i
],
stride
=
self
.
_out_strides
[
i
])
for
i
in
self
.
return_idx
]
dygraph/ppdet/modeling/necks/hrfpn.py
浏览文件 @
b83e39ef
...
...
@@ -18,6 +18,7 @@ from paddle import ParamAttr
import
paddle.nn
as
nn
from
paddle.regularizer
import
L2Decay
from
ppdet.core.workspace
import
register
,
serializable
from
..shape_spec
import
ShapeSpec
__all__
=
[
'HRFPN'
]
...
...
@@ -26,23 +27,28 @@ __all__ = ['HRFPN']
class
HRFPN
(
nn
.
Layer
):
"""
Args:
in_channel
(in
t): number of input feature channels from backbone
in_channel
s (lis
t): number of input feature channels from backbone
out_channel (int): number of output feature channels
share_conv (bool): whether to share conv for different layers' reduction
spatial_scale (list): feature map scaling factor
spatial_scales (list): feature map scaling factor
extra_stage (int): add extra stage for returning HRFPN fpn_feats
"""
def
__init__
(
self
,
in_channel
=
270
,
out_channel
=
256
,
share_conv
=
False
,
spatial_scale
=
[
1.
/
4
,
1.
/
8
,
1.
/
16
,
1.
/
32
,
1.
/
64
],
):
def
__init__
(
self
,
in_channels
=
[
18
,
36
,
72
,
144
]
,
out_channel
=
256
,
share_conv
=
False
,
extra_stage
=
1
,
spatial_scales
=
[
1.
/
4
,
1.
/
8
,
1.
/
16
,
1.
/
32
]
):
super
(
HRFPN
,
self
).
__init__
()
in_channel
=
sum
(
in_channels
)
self
.
in_channel
=
in_channel
self
.
out_channel
=
out_channel
self
.
share_conv
=
share_conv
self
.
spatial_scale
=
spatial_scale
for
i
in
range
(
extra_stage
):
spatial_scales
=
spatial_scales
+
[
spatial_scales
[
-
1
]
/
2.
]
self
.
spatial_scales
=
spatial_scales
self
.
num_out
=
len
(
self
.
spatial_scales
)
self
.
reduction
=
nn
.
Conv2D
(
in_channels
=
in_channel
,
...
...
@@ -50,7 +56,7 @@ class HRFPN(nn.Layer):
kernel_size
=
1
,
weight_attr
=
ParamAttr
(
name
=
'hrfpn_reduction_weights'
),
bias_attr
=
False
)
self
.
num_out
=
len
(
self
.
spatial_scale
)
if
share_conv
:
self
.
fpn_conv
=
nn
.
Conv2D
(
in_channels
=
out_channel
,
...
...
@@ -106,5 +112,20 @@ class HRFPN(nn.Layer):
conv
=
conv_func
(
outs
[
i
])
outputs
.
append
(
conv
)
fpn_feat
=
[
outputs
[
k
]
for
k
in
range
(
self
.
num_out
)]
return
fpn_feat
,
self
.
spatial_scale
fpn_feats
=
[
outputs
[
k
]
for
k
in
range
(
self
.
num_out
)]
return
fpn_feats
@
classmethod
def
from_config
(
cls
,
cfg
,
input_shape
):
return
{
'in_channels'
:
[
i
.
channels
for
i
in
input_shape
],
'spatial_scales'
:
[
1.0
/
i
.
stride
for
i
in
input_shape
],
}
@
property
def
out_shape
(
self
):
return
[
ShapeSpec
(
channels
=
self
.
out_channel
,
stride
=
1.
/
s
)
for
s
in
self
.
spatial_scales
]
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