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yolov5
Commits
f7bc685c
Unverified
提交
f7bc685c
authored
4月 21, 2021
作者:
Glenn Jocher
提交者:
GitHub
4月 21, 2021
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Implement yaml.safe_load() (#2876)
* Implement yaml.safe_load() * yaml.safe_dump()
上级
c949fc86
隐藏空白字符变更
内嵌
并排
正在显示
10 个修改的文件
包含
23 行增加
和
22 行删除
+23
-22
coco.yaml
data/coco.yaml
+1
-1
yolo.py
models/yolo.py
+1
-1
test.py
test.py
+1
-1
train.py
train.py
+10
-9
autoanchor.py
utils/autoanchor.py
+1
-1
resume.py
utils/aws/resume.py
+1
-1
general.py
utils/general.py
+1
-1
plots.py
utils/plots.py
+1
-1
log_dataset.py
utils/wandb_logging/log_dataset.py
+1
-1
wandb_utils.py
utils/wandb_logging/wandb_utils.py
+5
-5
没有找到文件。
data/coco.yaml
浏览文件 @
f7bc685c
...
@@ -30,6 +30,6 @@ names: [ 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', '
...
@@ -30,6 +30,6 @@ names: [ 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', '
# Print classes
# Print classes
# with open('data/coco.yaml') as f:
# with open('data/coco.yaml') as f:
# d = yaml.
load(f, Loader=yaml.FullLoader
) # dict
# d = yaml.
safe_load(f
) # dict
# for i, x in enumerate(d['names']):
# for i, x in enumerate(d['names']):
# print(i, x)
# print(i, x)
models/yolo.py
浏览文件 @
f7bc685c
...
@@ -72,7 +72,7 @@ class Model(nn.Module):
...
@@ -72,7 +72,7 @@ class Model(nn.Module):
import
yaml
# for torch hub
import
yaml
# for torch hub
self
.
yaml_file
=
Path
(
cfg
)
.
name
self
.
yaml_file
=
Path
(
cfg
)
.
name
with
open
(
cfg
)
as
f
:
with
open
(
cfg
)
as
f
:
self
.
yaml
=
yaml
.
load
(
f
,
Loader
=
yaml
.
SafeLoader
)
# model dict
self
.
yaml
=
yaml
.
safe_load
(
f
)
# model dict
# Define model
# Define model
ch
=
self
.
yaml
[
'ch'
]
=
self
.
yaml
.
get
(
'ch'
,
ch
)
# input channels
ch
=
self
.
yaml
[
'ch'
]
=
self
.
yaml
.
get
(
'ch'
,
ch
)
# input channels
...
...
test.py
浏览文件 @
f7bc685c
...
@@ -71,7 +71,7 @@ def test(data,
...
@@ -71,7 +71,7 @@ def test(data,
if
isinstance
(
data
,
str
):
if
isinstance
(
data
,
str
):
is_coco
=
data
.
endswith
(
'coco.yaml'
)
is_coco
=
data
.
endswith
(
'coco.yaml'
)
with
open
(
data
)
as
f
:
with
open
(
data
)
as
f
:
data
=
yaml
.
load
(
f
,
Loader
=
yaml
.
SafeLoader
)
data
=
yaml
.
safe_load
(
f
)
check_dataset
(
data
)
# check
check_dataset
(
data
)
# check
nc
=
1
if
single_cls
else
int
(
data
[
'nc'
])
# number of classes
nc
=
1
if
single_cls
else
int
(
data
[
'nc'
])
# number of classes
iouv
=
torch
.
linspace
(
0.5
,
0.95
,
10
)
.
to
(
device
)
# iou vector for mAP@0.5:0.95
iouv
=
torch
.
linspace
(
0.5
,
0.95
,
10
)
.
to
(
device
)
# iou vector for mAP@0.5:0.95
...
...
train.py
浏览文件 @
f7bc685c
...
@@ -41,7 +41,7 @@ logger = logging.getLogger(__name__)
...
@@ -41,7 +41,7 @@ logger = logging.getLogger(__name__)
def
train
(
hyp
,
opt
,
device
,
tb_writer
=
None
):
def
train
(
hyp
,
opt
,
device
,
tb_writer
=
None
):
logger
.
info
(
colorstr
(
'hyperparameters: '
)
+
', '
.
join
(
f
'{k}={v}'
for
k
,
v
in
hyp
.
items
()))
logger
.
info
(
colorstr
(
'hyperparameters: '
)
+
', '
.
join
(
f
'{k}={v}'
for
k
,
v
in
hyp
.
items
()))
save_dir
,
epochs
,
batch_size
,
total_batch_size
,
weights
,
rank
=
\
save_dir
,
epochs
,
batch_size
,
total_batch_size
,
weights
,
rank
=
\
opt
.
save_dir
,
opt
.
epochs
,
opt
.
batch_size
,
opt
.
total_batch_size
,
opt
.
weights
,
opt
.
global_rank
Path
(
opt
.
save_dir
)
,
opt
.
epochs
,
opt
.
batch_size
,
opt
.
total_batch_size
,
opt
.
weights
,
opt
.
global_rank
# Directories
# Directories
wdir
=
save_dir
/
'weights'
wdir
=
save_dir
/
'weights'
...
@@ -52,16 +52,16 @@ def train(hyp, opt, device, tb_writer=None):
...
@@ -52,16 +52,16 @@ def train(hyp, opt, device, tb_writer=None):
# Save run settings
# Save run settings
with
open
(
save_dir
/
'hyp.yaml'
,
'w'
)
as
f
:
with
open
(
save_dir
/
'hyp.yaml'
,
'w'
)
as
f
:
yaml
.
dump
(
hyp
,
f
,
sort_keys
=
False
)
yaml
.
safe_
dump
(
hyp
,
f
,
sort_keys
=
False
)
with
open
(
save_dir
/
'opt.yaml'
,
'w'
)
as
f
:
with
open
(
save_dir
/
'opt.yaml'
,
'w'
)
as
f
:
yaml
.
dump
(
vars
(
opt
),
f
,
sort_keys
=
False
)
yaml
.
safe_
dump
(
vars
(
opt
),
f
,
sort_keys
=
False
)
# Configure
# Configure
plots
=
not
opt
.
evolve
# create plots
plots
=
not
opt
.
evolve
# create plots
cuda
=
device
.
type
!=
'cpu'
cuda
=
device
.
type
!=
'cpu'
init_seeds
(
2
+
rank
)
init_seeds
(
2
+
rank
)
with
open
(
opt
.
data
)
as
f
:
with
open
(
opt
.
data
)
as
f
:
data_dict
=
yaml
.
load
(
f
,
Loader
=
yaml
.
SafeLoader
)
# data dict
data_dict
=
yaml
.
safe_load
(
f
)
# data dict
is_coco
=
opt
.
data
.
endswith
(
'coco.yaml'
)
is_coco
=
opt
.
data
.
endswith
(
'coco.yaml'
)
# Logging- Doing this before checking the dataset. Might update data_dict
# Logging- Doing this before checking the dataset. Might update data_dict
...
@@ -506,8 +506,9 @@ if __name__ == '__main__':
...
@@ -506,8 +506,9 @@ if __name__ == '__main__':
assert
os
.
path
.
isfile
(
ckpt
),
'ERROR: --resume checkpoint does not exist'
assert
os
.
path
.
isfile
(
ckpt
),
'ERROR: --resume checkpoint does not exist'
apriori
=
opt
.
global_rank
,
opt
.
local_rank
apriori
=
opt
.
global_rank
,
opt
.
local_rank
with
open
(
Path
(
ckpt
)
.
parent
.
parent
/
'opt.yaml'
)
as
f
:
with
open
(
Path
(
ckpt
)
.
parent
.
parent
/
'opt.yaml'
)
as
f
:
opt
=
argparse
.
Namespace
(
**
yaml
.
load
(
f
,
Loader
=
yaml
.
SafeLoader
))
# replace
opt
=
argparse
.
Namespace
(
**
yaml
.
safe_load
(
f
))
# replace
opt
.
cfg
,
opt
.
weights
,
opt
.
resume
,
opt
.
batch_size
,
opt
.
global_rank
,
opt
.
local_rank
=
''
,
ckpt
,
True
,
opt
.
total_batch_size
,
*
apriori
# reinstate
opt
.
cfg
,
opt
.
weights
,
opt
.
resume
,
opt
.
batch_size
,
opt
.
global_rank
,
opt
.
local_rank
=
\
''
,
ckpt
,
True
,
opt
.
total_batch_size
,
*
apriori
# reinstate
logger
.
info
(
'Resuming training from
%
s'
%
ckpt
)
logger
.
info
(
'Resuming training from
%
s'
%
ckpt
)
else
:
else
:
# opt.hyp = opt.hyp or ('hyp.finetune.yaml' if opt.weights else 'hyp.scratch.yaml')
# opt.hyp = opt.hyp or ('hyp.finetune.yaml' if opt.weights else 'hyp.scratch.yaml')
...
@@ -515,7 +516,7 @@ if __name__ == '__main__':
...
@@ -515,7 +516,7 @@ if __name__ == '__main__':
assert
len
(
opt
.
cfg
)
or
len
(
opt
.
weights
),
'either --cfg or --weights must be specified'
assert
len
(
opt
.
cfg
)
or
len
(
opt
.
weights
),
'either --cfg or --weights must be specified'
opt
.
img_size
.
extend
([
opt
.
img_size
[
-
1
]]
*
(
2
-
len
(
opt
.
img_size
)))
# extend to 2 sizes (train, test)
opt
.
img_size
.
extend
([
opt
.
img_size
[
-
1
]]
*
(
2
-
len
(
opt
.
img_size
)))
# extend to 2 sizes (train, test)
opt
.
name
=
'evolve'
if
opt
.
evolve
else
opt
.
name
opt
.
name
=
'evolve'
if
opt
.
evolve
else
opt
.
name
opt
.
save_dir
=
increment_path
(
Path
(
opt
.
project
)
/
opt
.
name
,
exist_ok
=
opt
.
exist_ok
|
opt
.
evolve
)
# increment run
opt
.
save_dir
=
str
(
increment_path
(
Path
(
opt
.
project
)
/
opt
.
name
,
exist_ok
=
opt
.
exist_ok
|
opt
.
evolve
))
# DDP mode
# DDP mode
opt
.
total_batch_size
=
opt
.
batch_size
opt
.
total_batch_size
=
opt
.
batch_size
...
@@ -530,7 +531,7 @@ if __name__ == '__main__':
...
@@ -530,7 +531,7 @@ if __name__ == '__main__':
# Hyperparameters
# Hyperparameters
with
open
(
opt
.
hyp
)
as
f
:
with
open
(
opt
.
hyp
)
as
f
:
hyp
=
yaml
.
load
(
f
,
Loader
=
yaml
.
SafeLoader
)
# load hyps
hyp
=
yaml
.
safe_load
(
f
)
# load hyps
# Train
# Train
logger
.
info
(
opt
)
logger
.
info
(
opt
)
...
@@ -577,7 +578,7 @@ if __name__ == '__main__':
...
@@ -577,7 +578,7 @@ if __name__ == '__main__':
assert
opt
.
local_rank
==
-
1
,
'DDP mode not implemented for --evolve'
assert
opt
.
local_rank
==
-
1
,
'DDP mode not implemented for --evolve'
opt
.
notest
,
opt
.
nosave
=
True
,
True
# only test/save final epoch
opt
.
notest
,
opt
.
nosave
=
True
,
True
# only test/save final epoch
# ei = [isinstance(x, (int, float)) for x in hyp.values()] # evolvable indices
# ei = [isinstance(x, (int, float)) for x in hyp.values()] # evolvable indices
yaml_file
=
opt
.
save_dir
/
'hyp_evolved.yaml'
# save best result here
yaml_file
=
Path
(
opt
.
save_dir
)
/
'hyp_evolved.yaml'
# save best result here
if
opt
.
bucket
:
if
opt
.
bucket
:
os
.
system
(
'gsutil cp gs://
%
s/evolve.txt .'
%
opt
.
bucket
)
# download evolve.txt if exists
os
.
system
(
'gsutil cp gs://
%
s/evolve.txt .'
%
opt
.
bucket
)
# download evolve.txt if exists
...
...
utils/autoanchor.py
浏览文件 @
f7bc685c
...
@@ -102,7 +102,7 @@ def kmean_anchors(path='./data/coco128.yaml', n=9, img_size=640, thr=4.0, gen=10
...
@@ -102,7 +102,7 @@ def kmean_anchors(path='./data/coco128.yaml', n=9, img_size=640, thr=4.0, gen=10
if
isinstance
(
path
,
str
):
# *.yaml file
if
isinstance
(
path
,
str
):
# *.yaml file
with
open
(
path
)
as
f
:
with
open
(
path
)
as
f
:
data_dict
=
yaml
.
load
(
f
,
Loader
=
yaml
.
SafeLoader
)
# model dict
data_dict
=
yaml
.
safe_load
(
f
)
# model dict
from
utils.datasets
import
LoadImagesAndLabels
from
utils.datasets
import
LoadImagesAndLabels
dataset
=
LoadImagesAndLabels
(
data_dict
[
'train'
],
augment
=
True
,
rect
=
True
)
dataset
=
LoadImagesAndLabels
(
data_dict
[
'train'
],
augment
=
True
,
rect
=
True
)
else
:
else
:
...
...
utils/aws/resume.py
浏览文件 @
f7bc685c
...
@@ -19,7 +19,7 @@ for last in path.rglob('*/**/last.pt'):
...
@@ -19,7 +19,7 @@ for last in path.rglob('*/**/last.pt'):
# Load opt.yaml
# Load opt.yaml
with
open
(
last
.
parent
.
parent
/
'opt.yaml'
)
as
f
:
with
open
(
last
.
parent
.
parent
/
'opt.yaml'
)
as
f
:
opt
=
yaml
.
load
(
f
,
Loader
=
yaml
.
SafeLoader
)
opt
=
yaml
.
safe_load
(
f
)
# Get device count
# Get device count
d
=
opt
[
'device'
]
.
split
(
','
)
# devices
d
=
opt
[
'device'
]
.
split
(
','
)
# devices
...
...
utils/general.py
浏览文件 @
f7bc685c
...
@@ -550,7 +550,7 @@ def print_mutation(hyp, results, yaml_file='hyp_evolved.yaml', bucket=''):
...
@@ -550,7 +550,7 @@ def print_mutation(hyp, results, yaml_file='hyp_evolved.yaml', bucket=''):
results
=
tuple
(
x
[
0
,
:
7
])
results
=
tuple
(
x
[
0
,
:
7
])
c
=
'
%10.4
g'
*
len
(
results
)
%
results
# results (P, R, mAP@0.5, mAP@0.5:0.95, val_losses x 3)
c
=
'
%10.4
g'
*
len
(
results
)
%
results
# results (P, R, mAP@0.5, mAP@0.5:0.95, val_losses x 3)
f
.
write
(
'# Hyperparameter Evolution Results
\n
# Generations:
%
g
\n
# Metrics: '
%
len
(
x
)
+
c
+
'
\n\n
'
)
f
.
write
(
'# Hyperparameter Evolution Results
\n
# Generations:
%
g
\n
# Metrics: '
%
len
(
x
)
+
c
+
'
\n\n
'
)
yaml
.
dump
(
hyp
,
f
,
sort_keys
=
False
)
yaml
.
safe_
dump
(
hyp
,
f
,
sort_keys
=
False
)
if
bucket
:
if
bucket
:
os
.
system
(
'gsutil cp evolve.txt
%
s gs://
%
s'
%
(
yaml_file
,
bucket
))
# upload
os
.
system
(
'gsutil cp evolve.txt
%
s gs://
%
s'
%
(
yaml_file
,
bucket
))
# upload
...
...
utils/plots.py
浏览文件 @
f7bc685c
...
@@ -323,7 +323,7 @@ def plot_labels(labels, names=(), save_dir=Path(''), loggers=None):
...
@@ -323,7 +323,7 @@ def plot_labels(labels, names=(), save_dir=Path(''), loggers=None):
def
plot_evolution
(
yaml_file
=
'data/hyp.finetune.yaml'
):
# from utils.plots import *; plot_evolution()
def
plot_evolution
(
yaml_file
=
'data/hyp.finetune.yaml'
):
# from utils.plots import *; plot_evolution()
# Plot hyperparameter evolution results in evolve.txt
# Plot hyperparameter evolution results in evolve.txt
with
open
(
yaml_file
)
as
f
:
with
open
(
yaml_file
)
as
f
:
hyp
=
yaml
.
load
(
f
,
Loader
=
yaml
.
SafeLoader
)
hyp
=
yaml
.
safe_load
(
f
)
x
=
np
.
loadtxt
(
'evolve.txt'
,
ndmin
=
2
)
x
=
np
.
loadtxt
(
'evolve.txt'
,
ndmin
=
2
)
f
=
fitness
(
x
)
f
=
fitness
(
x
)
# weights = (f - f.min()) ** 2 # for weighted results
# weights = (f - f.min()) ** 2 # for weighted results
...
...
utils/wandb_logging/log_dataset.py
浏览文件 @
f7bc685c
...
@@ -9,7 +9,7 @@ WANDB_ARTIFACT_PREFIX = 'wandb-artifact://'
...
@@ -9,7 +9,7 @@ WANDB_ARTIFACT_PREFIX = 'wandb-artifact://'
def
create_dataset_artifact
(
opt
):
def
create_dataset_artifact
(
opt
):
with
open
(
opt
.
data
)
as
f
:
with
open
(
opt
.
data
)
as
f
:
data
=
yaml
.
load
(
f
,
Loader
=
yaml
.
SafeLoader
)
# data dict
data
=
yaml
.
safe_load
(
f
)
# data dict
logger
=
WandbLogger
(
opt
,
''
,
None
,
data
,
job_type
=
'Dataset Creation'
)
logger
=
WandbLogger
(
opt
,
''
,
None
,
data
,
job_type
=
'Dataset Creation'
)
...
...
utils/wandb_logging/wandb_utils.py
浏览文件 @
f7bc685c
...
@@ -55,7 +55,7 @@ def check_wandb_resume(opt):
...
@@ -55,7 +55,7 @@ def check_wandb_resume(opt):
def
process_wandb_config_ddp_mode
(
opt
):
def
process_wandb_config_ddp_mode
(
opt
):
with
open
(
opt
.
data
)
as
f
:
with
open
(
opt
.
data
)
as
f
:
data_dict
=
yaml
.
load
(
f
,
Loader
=
yaml
.
SafeLoader
)
# data dict
data_dict
=
yaml
.
safe_load
(
f
)
# data dict
train_dir
,
val_dir
=
None
,
None
train_dir
,
val_dir
=
None
,
None
if
isinstance
(
data_dict
[
'train'
],
str
)
and
data_dict
[
'train'
]
.
startswith
(
WANDB_ARTIFACT_PREFIX
):
if
isinstance
(
data_dict
[
'train'
],
str
)
and
data_dict
[
'train'
]
.
startswith
(
WANDB_ARTIFACT_PREFIX
):
api
=
wandb
.
Api
()
api
=
wandb
.
Api
()
...
@@ -73,7 +73,7 @@ def process_wandb_config_ddp_mode(opt):
...
@@ -73,7 +73,7 @@ def process_wandb_config_ddp_mode(opt):
if
train_dir
or
val_dir
:
if
train_dir
or
val_dir
:
ddp_data_path
=
str
(
Path
(
val_dir
)
/
'wandb_local_data.yaml'
)
ddp_data_path
=
str
(
Path
(
val_dir
)
/
'wandb_local_data.yaml'
)
with
open
(
ddp_data_path
,
'w'
)
as
f
:
with
open
(
ddp_data_path
,
'w'
)
as
f
:
yaml
.
dump
(
data_dict
,
f
)
yaml
.
safe_
dump
(
data_dict
,
f
)
opt
.
data
=
ddp_data_path
opt
.
data
=
ddp_data_path
...
@@ -120,7 +120,7 @@ class WandbLogger():
...
@@ -120,7 +120,7 @@ class WandbLogger():
'YOLOv5'
if
opt
.
project
==
'runs/train'
else
Path
(
opt
.
project
)
.
stem
)
'YOLOv5'
if
opt
.
project
==
'runs/train'
else
Path
(
opt
.
project
)
.
stem
)
print
(
"Created dataset config file "
,
config_path
)
print
(
"Created dataset config file "
,
config_path
)
with
open
(
config_path
)
as
f
:
with
open
(
config_path
)
as
f
:
wandb_data_dict
=
yaml
.
load
(
f
,
Loader
=
yaml
.
SafeLoader
)
wandb_data_dict
=
yaml
.
safe_load
(
f
)
return
wandb_data_dict
return
wandb_data_dict
def
setup_training
(
self
,
opt
,
data_dict
):
def
setup_training
(
self
,
opt
,
data_dict
):
...
@@ -192,7 +192,7 @@ class WandbLogger():
...
@@ -192,7 +192,7 @@ class WandbLogger():
def
log_dataset_artifact
(
self
,
data_file
,
single_cls
,
project
,
overwrite_config
=
False
):
def
log_dataset_artifact
(
self
,
data_file
,
single_cls
,
project
,
overwrite_config
=
False
):
with
open
(
data_file
)
as
f
:
with
open
(
data_file
)
as
f
:
data
=
yaml
.
load
(
f
,
Loader
=
yaml
.
SafeLoader
)
# data dict
data
=
yaml
.
safe_load
(
f
)
# data dict
nc
,
names
=
(
1
,
[
'item'
])
if
single_cls
else
(
int
(
data
[
'nc'
]),
data
[
'names'
])
nc
,
names
=
(
1
,
[
'item'
])
if
single_cls
else
(
int
(
data
[
'nc'
]),
data
[
'names'
])
names
=
{
k
:
v
for
k
,
v
in
enumerate
(
names
)}
# to index dictionary
names
=
{
k
:
v
for
k
,
v
in
enumerate
(
names
)}
# to index dictionary
self
.
train_artifact
=
self
.
create_dataset_table
(
LoadImagesAndLabels
(
self
.
train_artifact
=
self
.
create_dataset_table
(
LoadImagesAndLabels
(
...
@@ -206,7 +206,7 @@ class WandbLogger():
...
@@ -206,7 +206,7 @@ class WandbLogger():
path
=
data_file
if
overwrite_config
else
'_wandb.'
.
join
(
data_file
.
rsplit
(
'.'
,
1
))
# updated data.yaml path
path
=
data_file
if
overwrite_config
else
'_wandb.'
.
join
(
data_file
.
rsplit
(
'.'
,
1
))
# updated data.yaml path
data
.
pop
(
'download'
,
None
)
data
.
pop
(
'download'
,
None
)
with
open
(
path
,
'w'
)
as
f
:
with
open
(
path
,
'w'
)
as
f
:
yaml
.
dump
(
data
,
f
)
yaml
.
safe_
dump
(
data
,
f
)
if
self
.
job_type
==
'Training'
:
# builds correct artifact pipeline graph
if
self
.
job_type
==
'Training'
:
# builds correct artifact pipeline graph
self
.
wandb_run
.
use_artifact
(
self
.
val_artifact
)
self
.
wandb_run
.
use_artifact
(
self
.
val_artifact
)
...
...
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