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b20f8b9e
编写于
6月 01, 2020
作者:
C
chenguowei01
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# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from
datasets
import
Dataset
import
transforms
import
paddle.fluid
as
fluid
from
models
import
UNet
data_dir
=
'/ssd1/chenguowei01/dataset/optic_disc_seg'
train_list
=
'/ssd1/chenguowei01/dataset/optic_disc_seg/train_list.txt'
val_list
=
'/ssd1/chenguowei01/dataset/optic_disc_seg/val_list.txt'
img_file
=
data_dir
+
'/JPEGImages/H0005.jpg'
train_transforms
=
transforms
.
Compose
([
transforms
.
Resize
((
192
,
192
)),
transforms
.
RandomHorizontalFlip
(),
transforms
.
Normalize
()
])
train_dataset
=
Dataset
(
data_dir
=
data_dir
,
file_list
=
train_list
,
transforms
=
train_transforms
,
num_workers
=
'auto'
,
buffer_size
=
100
,
parallel_method
=
'thread'
,
shuffle
=
True
)
eval_transforms
=
transforms
.
Compose
(
[
transforms
.
Resize
((
192
,
192
)),
transforms
.
Normalize
()])
eval_dataset
=
Dataset
(
data_dir
=
data_dir
,
file_list
=
val_list
,
transforms
=
eval_transforms
,
num_workers
=
'auto'
,
buffer_size
=
100
,
parallel_method
=
'thread'
,
shuffle
=
True
)
model
=
UNet
(
num_classes
=
2
)
with
fluid
.
dygraph
.
guard
(
model
.
places
):
model
.
build_model
()
#model.load_model('output/epoch_10/')
model
.
train
(
num_epochs
=
10
,
train_dataset
=
train_dataset
,
eval_dataset
=
eval_dataset
)
model
.
evaluate
(
eval_dataset
)
model
.
predict
(
img_file
,
eval_transforms
)
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