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PaddleDetection
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f331f0a1
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f331f0a1
编写于
5月 08, 2021
作者:
Z
zhiboniu
提交者:
GitHub
5月 08, 2021
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差异文件
add configs of hrhrnet&hrnet (#2817)
上级
00775c89
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3
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3 changed file
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configs/keypoint/higherhrnet/higherhrnet_hrnet_w32_512.yml
configs/keypoint/higherhrnet/higherhrnet_hrnet_w32_512.yml
+135
-0
configs/keypoint/higherhrnet/higherhrnet_hrnet_w32_512_swahr.yml
.../keypoint/higherhrnet/higherhrnet_hrnet_w32_512_swahr.yml
+135
-0
configs/keypoint/hrnet/hrnet_coco_256x192.yml
configs/keypoint/hrnet/hrnet_coco_256x192.yml
+143
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configs/keypoint/higherhrnet/higherhrnet_hrnet_w32_512.yml
0 → 100644
浏览文件 @
f331f0a1
use_gpu
:
true
log_iter
:
1
save_dir
:
output
snapshot_epoch
:
10
weights
:
output/higherhrnet_hrnet_v1_512/290
epoch
:
300
num_joints
:
&num_joints
17
flip_perm
:
&flip_perm
[
0
,
2
,
1
,
4
,
3
,
6
,
5
,
8
,
7
,
10
,
9
,
12
,
11
,
14
,
13
,
16
,
15
]
input_size
:
&input_size
512
hm_size
:
&hm_size
128
hm_size_2x
:
&hm_size_2x
256
max_people
:
&max_people
30
metric
:
COCO
IouType
:
keypoints
num_classes
:
1
#####model
architecture
:
HigherHRNet
pretrain_weights
:
https://paddledet.bj.bcebos.com/models/pretrained/Trunc_HRNet_W32_C_pretrained.pdparams
HigherHRNet
:
backbone
:
HRNet
hrhrnet_head
:
HrHRNetHead
post_process
:
HrHRNetPostProcess
flip_perm
:
*flip_perm
eval_flip
:
true
HRNet
:
width
:
&width
32
freeze_at
:
-1
freeze_norm
:
false
return_idx
:
[
0
]
HrHRNetHead
:
num_joints
:
*num_joints
width
:
*width
loss
:
HrHRNetLoss
swahr
:
false
HrHRNetLoss
:
num_joints
:
*num_joints
swahr
:
false
#####optimizer
LearningRate
:
base_lr
:
0.001
schedulers
:
-
!PiecewiseDecay
milestones
:
[
200
,
260
]
gamma
:
0.1
-
!LinearWarmup
start_factor
:
0.001
steps
:
1000
OptimizerBuilder
:
optimizer
:
type
:
Adam
regularizer
:
#####data
TrainDataset
:
!KeypointBottomUpCocoDataset
image_dir
:
train2017
anno_path
:
annotations/person_keypoints_train2017.json
dataset_dir
:
dataset/coco
num_joints
:
*num_joints
EvalDataset
:
!KeypointBottomUpCocoDataset
image_dir
:
val2017
anno_path
:
annotations/person_keypoints_val2017.json
dataset_dir
:
dataset/coco
num_joints
:
*num_joints
test_mode
:
true
TestDataset
:
!ImageFolder
anno_path
:
dataset/coco/keypoint_imagelist.txt
worker_num
:
8
global_mean
:
&global_mean
[
0.485
,
0.456
,
0.406
]
global_std
:
&global_std
[
0.229
,
0.224
,
0.225
]
TrainReader
:
sample_transforms
:
-
RandomAffine
:
max_degree
:
30
scale
:
[
0.75
,
1.5
]
max_shift
:
0.2
trainsize
:
*input_size
hmsize
:
[
*hm_size
,
*hm_size_2x
]
-
KeyPointFlip
:
flip_prob
:
0.5
flip_permutation
:
*flip_perm
hmsize
:
[
*hm_size
,
*hm_size_2x
]
-
ToHeatmaps
:
num_joints
:
*num_joints
hmsize
:
[
*hm_size
,
*hm_size_2x
]
sigma
:
2
-
TagGenerate
:
num_joints
:
*num_joints
max_people
:
*max_people
-
NormalizePermute
:
mean
:
*global_mean
std
:
*global_std
batch_size
:
20
shuffle
:
true
drop_last
:
true
use_shared_memory
:
true
EvalReader
:
sample_transforms
:
-
EvalAffine
:
size
:
*input_size
-
NormalizeImage
:
mean
:
*global_mean
std
:
*global_std
is_scale
:
true
-
Permute
:
{}
batch_size
:
1
drop_empty
:
false
TestReader
:
sample_transforms
:
-
Decode
:
{}
-
EvalAffine
:
size
:
*input_size
-
NormalizeImage
:
mean
:
*global_mean
std
:
*global_std
is_scale
:
true
-
Permute
:
{}
batch_size
:
1
configs/keypoint/higherhrnet/higherhrnet_hrnet_w32_512_swahr.yml
0 → 100644
浏览文件 @
f331f0a1
use_gpu
:
true
log_iter
:
10
save_dir
:
output
snapshot_epoch
:
10
weights
:
output/higherhrnet_hrnet_v1_512/model_final
epoch
:
300
num_joints
:
&num_joints
17
flip_perm
:
&flip_perm
[
0
,
2
,
1
,
4
,
3
,
6
,
5
,
8
,
7
,
10
,
9
,
12
,
11
,
14
,
13
,
16
,
15
]
input_size
:
&input_size
512
hm_size
:
&hm_size
128
hm_size_2x
:
&hm_size_2x
256
max_people
:
&max_people
30
metric
:
COCO
IouType
:
keypoints
num_classes
:
1
#####model
architecture
:
HigherHRNet
pretrain_weights
:
https://paddledet.bj.bcebos.com/models/pretrained/Trunc_HRNet_W32_C_pretrained.pdparams
HigherHRNet
:
backbone
:
HRNet
hrhrnet_head
:
HrHRNetHead
post_process
:
HrHRNetPostProcess
flip_perm
:
*flip_perm
eval_flip
:
true
HRNet
:
width
:
&width
32
freeze_at
:
-1
freeze_norm
:
false
return_idx
:
[
0
]
HrHRNetHead
:
num_joints
:
*num_joints
width
:
*width
loss
:
HrHRNetLoss
swahr
:
true
HrHRNetLoss
:
num_joints
:
*num_joints
swahr
:
true
#####optimizer
LearningRate
:
base_lr
:
0.001
schedulers
:
-
!PiecewiseDecay
milestones
:
[
200
,
260
]
gamma
:
0.1
-
!LinearWarmup
start_factor
:
0.001
steps
:
1000
OptimizerBuilder
:
optimizer
:
type
:
Adam
regularizer
:
#####data
TrainDataset
:
!KeypointBottomUpCocoDataset
image_dir
:
train2017
anno_path
:
annotations/person_keypoints_train2017.json
dataset_dir
:
dataset/coco
num_joints
:
*num_joints
EvalDataset
:
!KeypointBottomUpCocoDataset
image_dir
:
val2017
anno_path
:
annotations/person_keypoints_val2017.json
dataset_dir
:
dataset/coco
num_joints
:
*num_joints
test_mode
:
true
TestDataset
:
!ImageFolder
anno_path
:
dataset/coco/keypoint_imagelist.txt
worker_num
:
8
global_mean
:
&global_mean
[
0.485
,
0.456
,
0.406
]
global_std
:
&global_std
[
0.229
,
0.224
,
0.225
]
TrainReader
:
sample_transforms
:
-
RandomAffine
:
max_degree
:
30
scale
:
[
0.75
,
1.5
]
max_shift
:
0.2
trainsize
:
*input_size
hmsize
:
[
*hm_size
,
*hm_size_2x
]
-
KeyPointFlip
:
flip_prob
:
0.5
flip_permutation
:
*flip_perm
hmsize
:
[
*hm_size
,
*hm_size_2x
]
-
ToHeatmaps
:
num_joints
:
*num_joints
hmsize
:
[
*hm_size
,
*hm_size_2x
]
sigma
:
2
-
TagGenerate
:
num_joints
:
*num_joints
max_people
:
*max_people
-
NormalizePermute
:
mean
:
*global_mean
std
:
*global_std
batch_size
:
16
shuffle
:
true
drop_last
:
true
use_shared_memory
:
true
EvalReader
:
sample_transforms
:
-
EvalAffine
:
size
:
*input_size
-
NormalizeImage
:
mean
:
*global_mean
std
:
*global_std
is_scale
:
true
-
Permute
:
{}
batch_size
:
1
drop_empty
:
false
TestReader
:
sample_transforms
:
-
Decode
:
{}
-
EvalAffine
:
size
:
*input_size
-
NormalizeImage
:
mean
:
*global_mean
std
:
*global_std
is_scale
:
true
-
Permute
:
{}
batch_size
:
1
configs/keypoint/hrnet/hrnet_coco_256x192.yml
0 → 100644
浏览文件 @
f331f0a1
use_gpu
:
true
log_iter
:
5
save_dir
:
output
snapshot_epoch
:
10
weights
:
output/hrnet_coco_256x192/50
epoch
:
210
num_joints
:
&num_joints
17
pixel_std
:
&pixel_std
200
metric
:
KeyPointTopDownCOCOEval
num_classes
:
1
train_height
:
&train_height
256
train_width
:
&train_width
192
trainsize
:
&trainsize
[
*train_width
,
*train_height
]
hmsize
:
&hmsize
[
48
,
64
]
flip_perm
:
&flip_perm
[[
1
,
2
],
[
3
,
4
],
[
5
,
6
],
[
7
,
8
],
[
9
,
10
],
[
11
,
12
],
[
13
,
14
],
[
15
,
16
]]
#####model
architecture
:
TopDownHRNet
pretrain_weights
:
https://paddledet.bj.bcebos.com/models/pretrained/Trunc_HRNet_W32_C_pretrained.pdparams
TopDownHRNet
:
backbone
:
HRNet
post_process
:
HRNetPostProcess
flip_perm
:
*flip_perm
num_joints
:
*num_joints
width
:
&width
32
loss
:
KeyPointMSELoss
HRNet
:
width
:
*width
freeze_at
:
-1
freeze_norm
:
false
return_idx
:
[
0
]
KeyPointMSELoss
:
use_target_weight
:
true
#####optimizer
LearningRate
:
base_lr
:
0.0005
schedulers
:
-
!PiecewiseDecay
milestones
:
[
170
,
200
]
gamma
:
0.1
-
!LinearWarmup
start_factor
:
0.001
steps
:
1000
OptimizerBuilder
:
optimizer
:
type
:
Adam
regularizer
:
factor
:
0.0
type
:
L2
#####data
TrainDataset
:
!KeypointTopDownCocoDataset
image_dir
:
train2017
anno_path
:
annotations/person_keypoints_train2017.json
dataset_dir
:
dataset/coco
num_joints
:
*num_joints
trainsize
:
*trainsize
pixel_std
:
*pixel_std
use_gt_bbox
:
True
EvalDataset
:
!KeypointTopDownCocoDataset
image_dir
:
val2017
anno_path
:
annotations/person_keypoints_val2017.json
dataset_dir
:
dataset/coco
bbox_file
:
person_detection_results/COCO_val2017_detections_AP_H_56_person.json
num_joints
:
*num_joints
trainsize
:
*trainsize
pixel_std
:
*pixel_std
use_gt_bbox
:
True
image_thre
:
0.0
TestDataset
:
!ImageFolder
anno_path
:
dataset/coco/keypoint_imagelist.txt
worker_num
:
2
global_mean
:
&global_mean
[
0.485
,
0.456
,
0.406
]
global_std
:
&global_std
[
0.229
,
0.224
,
0.225
]
TrainReader
:
sample_transforms
:
-
RandomFlipHalfBodyTransform
:
scale
:
0.5
rot
:
40
num_joints_half_body
:
8
prob_half_body
:
0.3
pixel_std
:
*pixel_std
trainsize
:
*trainsize
upper_body_ids
:
[
0
,
1
,
2
,
3
,
4
,
5
,
6
,
7
,
8
,
9
,
10
]
flip_pairs
:
*flip_perm
-
TopDownAffine
:
trainsize
:
*trainsize
-
ToHeatmapsTopDown
:
hmsize
:
*hmsize
sigma
:
2
batch_transforms
:
-
NormalizeImage
:
mean
:
*global_mean
std
:
*global_std
is_scale
:
true
-
Permute
:
{}
batch_size
:
64
shuffle
:
true
drop_last
:
false
EvalReader
:
sample_transforms
:
-
TopDownAffine
:
trainsize
:
*trainsize
-
ToHeatmapsTopDown
:
hmsize
:
*hmsize
sigma
:
2
batch_transforms
:
-
NormalizeImage
:
mean
:
*global_mean
std
:
*global_std
is_scale
:
true
-
Permute
:
{}
batch_size
:
16
drop_empty
:
false
TestReader
:
sample_transforms
:
-
Decode
:
{}
-
TopDownEvalAffine
:
trainsize
:
*trainsize
-
NormalizeImage
:
mean
:
*global_mean
std
:
*global_std
is_scale
:
true
-
Permute
:
{}
batch_size
:
1
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