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Administrator
yolov5
Commits
61047a2b
Unverified
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61047a2b
authored
7月 07, 2021
作者:
johnohagan
提交者:
GitHub
7月 07, 2021
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电子邮件补丁
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Save PyTorch Hub models to `/root/hub/cache/dir` (#3904)
* Create hubconf.py * Add save_dir variable Co-authored-by:
Glenn Jocher
<
glenn.jocher@ultralytics.com
>
上级
33202b7f
隐藏空白字符变更
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1 个修改的文件
包含
8 行增加
和
7 行删除
+8
-7
hubconf.py
hubconf.py
+8
-7
没有找到文件。
hubconf.py
浏览文件 @
61047a2b
...
@@ -4,9 +4,12 @@ Usage:
...
@@ -4,9 +4,12 @@ Usage:
import torch
import torch
model = torch.hub.load('ultralytics/yolov5', 'yolov5s')
model = torch.hub.load('ultralytics/yolov5', 'yolov5s')
"""
"""
from
pathlib
import
Path
import
torch
import
torch
FILE
=
Path
(
__file__
)
.
absolute
()
def
_create
(
name
,
pretrained
=
True
,
channels
=
3
,
classes
=
80
,
autoshape
=
True
,
verbose
=
True
,
device
=
None
):
def
_create
(
name
,
pretrained
=
True
,
channels
=
3
,
classes
=
80
,
autoshape
=
True
,
verbose
=
True
,
device
=
None
):
"""Creates a specified YOLOv5 model
"""Creates a specified YOLOv5 model
...
@@ -23,28 +26,26 @@ def _create(name, pretrained=True, channels=3, classes=80, autoshape=True, verbo
...
@@ -23,28 +26,26 @@ def _create(name, pretrained=True, channels=3, classes=80, autoshape=True, verbo
Returns:
Returns:
YOLOv5 pytorch model
YOLOv5 pytorch model
"""
"""
from
pathlib
import
Path
from
models.yolo
import
Model
,
attempt_load
from
models.yolo
import
Model
,
attempt_load
from
utils.general
import
check_requirements
,
set_logging
from
utils.general
import
check_requirements
,
set_logging
from
utils.google_utils
import
attempt_download
from
utils.google_utils
import
attempt_download
from
utils.torch_utils
import
select_device
from
utils.torch_utils
import
select_device
check_requirements
(
requirements
=
Path
(
__file__
)
.
parent
/
'requirements.txt'
,
check_requirements
(
requirements
=
FILE
.
parent
/
'requirements.txt'
,
exclude
=
(
'tensorboard'
,
'thop'
,
'opencv-python'
))
exclude
=
(
'tensorboard'
,
'thop'
,
'opencv-python'
))
set_logging
(
verbose
=
verbose
)
set_logging
(
verbose
=
verbose
)
fname
=
Path
(
name
)
.
with_suffix
(
'.pt'
)
# checkpoint filename
save_dir
=
Path
(
''
)
if
str
(
name
)
.
endswith
(
'.pt'
)
else
FILE
.
parent
path
=
(
save_dir
/
name
)
.
with_suffix
(
'.pt'
)
# checkpoint path
try
:
try
:
device
=
select_device
((
'0'
if
torch
.
cuda
.
is_available
()
else
'cpu'
)
if
device
is
None
else
device
)
device
=
select_device
((
'0'
if
torch
.
cuda
.
is_available
()
else
'cpu'
)
if
device
is
None
else
device
)
if
pretrained
and
channels
==
3
and
classes
==
80
:
if
pretrained
and
channels
==
3
and
classes
==
80
:
model
=
attempt_load
(
fname
,
map_location
=
device
)
# download/load FP32 model
model
=
attempt_load
(
path
,
map_location
=
device
)
# download/load FP32 model
else
:
else
:
cfg
=
list
((
Path
(
__file__
)
.
parent
/
'models'
)
.
rglob
(
f
'{name}.yaml'
))[
0
]
# model.yaml path
cfg
=
list
((
Path
(
__file__
)
.
parent
/
'models'
)
.
rglob
(
f
'{name}.yaml'
))[
0
]
# model.yaml path
model
=
Model
(
cfg
,
channels
,
classes
)
# create model
model
=
Model
(
cfg
,
channels
,
classes
)
# create model
if
pretrained
:
if
pretrained
:
ckpt
=
torch
.
load
(
attempt_download
(
fname
),
map_location
=
device
)
# load
ckpt
=
torch
.
load
(
attempt_download
(
path
),
map_location
=
device
)
# load
msd
=
model
.
state_dict
()
# model state_dict
msd
=
model
.
state_dict
()
# model state_dict
csd
=
ckpt
[
'model'
]
.
float
()
.
state_dict
()
# checkpoint state_dict as FP32
csd
=
ckpt
[
'model'
]
.
float
()
.
state_dict
()
# checkpoint state_dict as FP32
csd
=
{
k
:
v
for
k
,
v
in
csd
.
items
()
if
msd
[
k
]
.
shape
==
v
.
shape
}
# filter
csd
=
{
k
:
v
for
k
,
v
in
csd
.
items
()
if
msd
[
k
]
.
shape
==
v
.
shape
}
# filter
...
...
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