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ModelZoo
SOLOv2-pytorch
Commits
b320d0ab
Commit
b320d0ab
authored
Dec 12, 2018
by
yhcao6
Browse files
fix
parent
450cfb73
Changes
4
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4 changed files
with
31 additions
and
24 deletions
+31
-24
configs/pascal_voc/ssd300_voc.py
configs/pascal_voc/ssd300_voc.py
+5
-4
configs/pascal_voc/ssd512_voc.py
configs/pascal_voc/ssd512_voc.py
+16
-12
configs/ssd300_coco.py
configs/ssd300_coco.py
+5
-4
configs/ssd512_coco.py
configs/ssd512_coco.py
+5
-4
No files found.
configs/ssd300_voc.py
→
configs/
pascal_voc/
ssd300_voc.py
View file @
b320d0ab
# model settings
input_size
=
300
model
=
dict
(
type
=
'SingleStageDetector'
,
pretrained
=
'data/vgg_backbone.pth'
,
backbone
=
dict
(
type
=
'SSDVGG'
,
input_size
=
300
,
input_size
=
input_size
,
depth
=
16
,
with_last_pool
=
False
,
ceil_mode
=
True
,
...
...
@@ -14,7 +15,7 @@ model = dict(
neck
=
None
,
bbox_head
=
dict
(
type
=
'SSDHead'
,
input_size
=
300
,
input_size
=
input_size
,
in_channels
=
(
512
,
1024
,
512
,
256
,
256
,
256
),
num_classes
=
21
,
anchor_strides
=
(
8
,
16
,
32
,
64
,
100
,
300
),
...
...
@@ -50,6 +51,7 @@ data = dict(
workers_per_gpu
=
3
,
train
=
dict
(
type
=
'RepeatDataset'
,
times
=
20
,
dataset
=
dict
(
type
=
dataset_type
,
ann_file
=
[
...
...
@@ -77,8 +79,7 @@ data = dict(
ratio_range
=
(
1
,
4
)),
random_crop
=
dict
(
min_ious
=
(
0.1
,
0.3
,
0.5
,
0.7
,
0.9
),
min_crop_size
=
0.3
)),
resize_keep_ratio
=
False
),
times
=
20
),
resize_keep_ratio
=
False
)),
val
=
dict
(
type
=
dataset_type
,
ann_file
=
data_root
+
'VOC2007/ImageSets/Main/test.txt'
,
...
...
configs/ssd512_voc.py
→
configs/
pascal_voc/
ssd512_voc.py
View file @
b320d0ab
# model settings
input_size
=
512
model
=
dict
(
type
=
'SingleStageDetector'
,
pretrained
=
'data/vgg_backbone.pth'
,
backbone
=
dict
(
type
=
'SSDVGG'
,
input_size
=
512
,
input_size
=
input_size
,
depth
=
16
,
with_last_pool
=
False
,
ceil_mode
=
True
,
...
...
@@ -14,7 +15,7 @@ model = dict(
neck
=
None
,
bbox_head
=
dict
(
type
=
'SSDHead'
,
input_size
=
512
,
input_size
=
input_size
,
in_channels
=
(
512
,
1024
,
512
,
256
,
256
,
256
,
256
),
num_classes
=
81
,
anchor_strides
=
(
8
,
16
,
32
,
64
,
128
,
256
,
512
),
...
...
@@ -42,18 +43,22 @@ test_cfg = dict(
max_per_img
=
200
)
# model training and testing settings
# dataset settings
dataset_type
=
'
Coco
Dataset'
data_root
=
'data/
coco
/'
dataset_type
=
'
VOC
Dataset'
data_root
=
'data/
VOCdevkit
/'
img_norm_cfg
=
dict
(
mean
=
[
123.675
,
116.28
,
103.53
],
std
=
[
1
,
1
,
1
],
to_rgb
=
True
)
data
=
dict
(
imgs_per_gpu
=
8
,
workers_per_gpu
=
3
,
train
=
dict
(
type
=
'RepeatDataset'
,
times
=
20
,
dataset
=
dict
(
type
=
dataset_type
,
ann_file
=
data_root
+
'annotations/instances_train2017.json'
,
img_prefix
=
data_root
+
'train2017/'
,
ann_file
=
[
data_root
+
'VOC2007/ImageSets/Main/trainval.txt'
,
data_root
+
'VOC2012/ImageSets/Main/trainval.txt'
],
img_prefix
=
[
data_root
+
'VOC2007/'
,
data_root
+
'VOC2012/'
],
img_scale
=
(
512
,
512
),
img_norm_cfg
=
img_norm_cfg
,
size_divisor
=
None
,
...
...
@@ -74,12 +79,11 @@ data = dict(
ratio_range
=
(
1
,
4
)),
random_crop
=
dict
(
min_ious
=
(
0.1
,
0.3
,
0.5
,
0.7
,
0.9
),
min_crop_size
=
0.3
)),
resize_keep_ratio
=
False
),
times
=
10
),
resize_keep_ratio
=
False
)),
val
=
dict
(
type
=
dataset_type
,
ann_file
=
data_root
+
'
annotations/instances_val2017.json
'
,
img_prefix
=
data_root
+
'
val
20
1
7/'
,
ann_file
=
data_root
+
'
VOC2007/ImageSets/Main/test.txt
'
,
img_prefix
=
data_root
+
'
VOC
20
0
7/'
,
img_scale
=
(
512
,
512
),
img_norm_cfg
=
img_norm_cfg
,
size_divisor
=
None
,
...
...
@@ -90,8 +94,8 @@ data = dict(
resize_keep_ratio
=
False
),
test
=
dict
(
type
=
dataset_type
,
ann_file
=
data_root
+
'
annotations/instances_val2017.json
'
,
img_prefix
=
data_root
+
'
val
20
1
7/'
,
ann_file
=
data_root
+
'
VOC2007/ImageSets/Main/test.txt
'
,
img_prefix
=
data_root
+
'
VOC
20
0
7/'
,
img_scale
=
(
512
,
512
),
img_norm_cfg
=
img_norm_cfg
,
size_divisor
=
None
,
...
...
configs/ssd300_coco.py
View file @
b320d0ab
# model settings
input_size
=
300
model
=
dict
(
type
=
'SingleStageDetector'
,
pretrained
=
'data/vgg_backbone.pth'
,
backbone
=
dict
(
type
=
'SSDVGG'
,
input_size
=
300
,
input_size
=
input_size
,
depth
=
16
,
with_last_pool
=
False
,
ceil_mode
=
True
,
...
...
@@ -14,7 +15,7 @@ model = dict(
neck
=
None
,
bbox_head
=
dict
(
type
=
'SSDHead'
,
input_size
=
300
,
input_size
=
input_size
,
in_channels
=
(
512
,
1024
,
512
,
256
,
256
,
256
),
num_classes
=
81
,
anchor_strides
=
(
8
,
16
,
32
,
64
,
100
,
300
),
...
...
@@ -50,6 +51,7 @@ data = dict(
workers_per_gpu
=
3
,
train
=
dict
(
type
=
'RepeatDataset'
,
times
=
10
,
dataset
=
dict
(
type
=
dataset_type
,
ann_file
=
data_root
+
'annotations/instances_train2017.json'
,
...
...
@@ -74,8 +76,7 @@ data = dict(
ratio_range
=
(
1
,
4
)),
random_crop
=
dict
(
min_ious
=
(
0.1
,
0.3
,
0.5
,
0.7
,
0.9
),
min_crop_size
=
0.3
)),
resize_keep_ratio
=
False
),
times
=
10
),
resize_keep_ratio
=
False
)),
val
=
dict
(
type
=
dataset_type
,
ann_file
=
data_root
+
'annotations/instances_val2017.json'
,
...
...
configs/ssd512_coco.py
View file @
b320d0ab
# model settings
input_size
=
512
model
=
dict
(
type
=
'SingleStageDetector'
,
pretrained
=
'data/vgg_backbone.pth'
,
backbone
=
dict
(
type
=
'SSDVGG'
,
input_size
=
512
,
input_size
=
input_size
,
depth
=
16
,
with_last_pool
=
False
,
ceil_mode
=
True
,
...
...
@@ -14,7 +15,7 @@ model = dict(
neck
=
None
,
bbox_head
=
dict
(
type
=
'SSDHead'
,
input_size
=
512
,
input_size
=
input_size
,
in_channels
=
(
512
,
1024
,
512
,
256
,
256
,
256
,
256
),
num_classes
=
81
,
anchor_strides
=
(
8
,
16
,
32
,
64
,
128
,
256
,
512
),
...
...
@@ -50,6 +51,7 @@ data = dict(
workers_per_gpu
=
3
,
train
=
dict
(
type
=
'RepeatDataset'
,
times
=
10
,
dataset
=
dict
(
type
=
dataset_type
,
ann_file
=
data_root
+
'annotations/instances_train2017.json'
,
...
...
@@ -74,8 +76,7 @@ data = dict(
ratio_range
=
(
1
,
4
)),
random_crop
=
dict
(
min_ious
=
(
0.1
,
0.3
,
0.5
,
0.7
,
0.9
),
min_crop_size
=
0.3
)),
resize_keep_ratio
=
False
),
times
=
10
),
resize_keep_ratio
=
False
)),
val
=
dict
(
type
=
dataset_type
,
ann_file
=
data_root
+
'annotations/instances_val2017.json'
,
...
...
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