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前往新版Gitcode,体验更适合开发者的 AI 搜索 >>
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a4a0a30f
编写于
11月 11, 2020
作者:
B
Bubbliiiing
提交者:
GitHub
11月 11, 2020
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Update train_with_tensorboard.py
上级
25d9604e
变更
1
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并排
Showing
1 changed file
with
4 addition
and
4 deletion
+4
-4
train_with_tensorboard.py
train_with_tensorboard.py
+4
-4
未找到文件。
train_with_tensorboard.py
浏览文件 @
a4a0a30f
...
@@ -207,9 +207,9 @@ if __name__ == "__main__":
...
@@ -207,9 +207,9 @@ if __name__ == "__main__":
if
Use_Data_Loader
:
if
Use_Data_Loader
:
train_dataset
=
YoloDataset
(
lines
[:
num_train
],
(
input_shape
[
0
],
input_shape
[
1
]),
mosaic
=
mosaic
)
train_dataset
=
YoloDataset
(
lines
[:
num_train
],
(
input_shape
[
0
],
input_shape
[
1
]),
mosaic
=
mosaic
)
val_dataset
=
YoloDataset
(
lines
[
num_train
:],
(
input_shape
[
0
],
input_shape
[
1
]),
mosaic
=
False
)
val_dataset
=
YoloDataset
(
lines
[
num_train
:],
(
input_shape
[
0
],
input_shape
[
1
]),
mosaic
=
False
)
gen
=
DataLoader
(
train_dataset
,
batch_size
=
Batch_size
,
num_workers
=
4
,
pin_memory
=
True
,
gen
=
DataLoader
(
train_dataset
,
shuffle
=
True
,
batch_size
=
Batch_size
,
num_workers
=
4
,
pin_memory
=
True
,
drop_last
=
True
,
collate_fn
=
yolo_dataset_collate
)
drop_last
=
True
,
collate_fn
=
yolo_dataset_collate
)
gen_val
=
DataLoader
(
val_dataset
,
batch_size
=
Batch_size
,
num_workers
=
4
,
pin_memory
=
True
,
gen_val
=
DataLoader
(
val_dataset
,
shuffle
=
True
,
batch_size
=
Batch_size
,
num_workers
=
4
,
pin_memory
=
True
,
drop_last
=
True
,
collate_fn
=
yolo_dataset_collate
)
drop_last
=
True
,
collate_fn
=
yolo_dataset_collate
)
else
:
else
:
gen
=
Generator
(
Batch_size
,
lines
[:
num_train
],
gen
=
Generator
(
Batch_size
,
lines
[:
num_train
],
...
@@ -244,9 +244,9 @@ if __name__ == "__main__":
...
@@ -244,9 +244,9 @@ if __name__ == "__main__":
if
Use_Data_Loader
:
if
Use_Data_Loader
:
train_dataset
=
YoloDataset
(
lines
[:
num_train
],
(
input_shape
[
0
],
input_shape
[
1
]),
mosaic
=
mosaic
)
train_dataset
=
YoloDataset
(
lines
[:
num_train
],
(
input_shape
[
0
],
input_shape
[
1
]),
mosaic
=
mosaic
)
val_dataset
=
YoloDataset
(
lines
[
num_train
:],
(
input_shape
[
0
],
input_shape
[
1
]),
mosaic
=
False
)
val_dataset
=
YoloDataset
(
lines
[
num_train
:],
(
input_shape
[
0
],
input_shape
[
1
]),
mosaic
=
False
)
gen
=
DataLoader
(
train_dataset
,
batch_size
=
Batch_size
,
num_workers
=
4
,
pin_memory
=
True
,
gen
=
DataLoader
(
train_dataset
,
shuffle
=
True
,
batch_size
=
Batch_size
,
num_workers
=
4
,
pin_memory
=
True
,
drop_last
=
True
,
collate_fn
=
yolo_dataset_collate
)
drop_last
=
True
,
collate_fn
=
yolo_dataset_collate
)
gen_val
=
DataLoader
(
val_dataset
,
batch_size
=
Batch_size
,
num_workers
=
4
,
pin_memory
=
True
,
gen_val
=
DataLoader
(
val_dataset
,
shuffle
=
True
,
batch_size
=
Batch_size
,
num_workers
=
4
,
pin_memory
=
True
,
drop_last
=
True
,
collate_fn
=
yolo_dataset_collate
)
drop_last
=
True
,
collate_fn
=
yolo_dataset_collate
)
else
:
else
:
gen
=
Generator
(
Batch_size
,
lines
[:
num_train
],
gen
=
Generator
(
Batch_size
,
lines
[:
num_train
],
...
...
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