You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
60 lines
2.3 KiB
60 lines
2.3 KiB
3 years ago
|
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
|
||
|
|
#
|
||
|
|
# 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.
|
||
|
|
|
||
|
|
import numpy as np
|
||
|
|
|
||
|
|
|
||
|
|
def config_check(cfg, train_dataset=None, val_dataset=None):
|
||
|
|
"""
|
||
|
|
To check config。
|
||
|
|
|
||
|
|
Args:
|
||
|
|
cfg (paddleseg.cvlibs.Config): An object of paddleseg.cvlibs.Config.
|
||
|
|
train_dataset (paddle.io.Dataset): Used to read and process training datasets.
|
||
|
|
val_dataset (paddle.io.Dataset, optional): Used to read and process validation datasets.
|
||
|
|
"""
|
||
|
|
|
||
|
|
num_classes_check(cfg, train_dataset, val_dataset)
|
||
|
|
|
||
|
|
|
||
|
|
def num_classes_check(cfg, train_dataset, val_dataset):
|
||
|
|
""""
|
||
|
|
Check that the num_classes in model, train_dataset and val_dataset is consistent.
|
||
|
|
"""
|
||
|
|
num_classes_set = set()
|
||
|
|
if train_dataset and hasattr(train_dataset, 'num_classes'):
|
||
|
|
num_classes_set.add(train_dataset.num_classes)
|
||
|
|
if val_dataset and hasattr(val_dataset, 'num_classes'):
|
||
|
|
num_classes_set.add(val_dataset.num_classes)
|
||
|
|
if cfg.dic.get('model', None) and cfg.dic['model'].get('num_classes', None):
|
||
|
|
num_classes_set.add(cfg.dic['model'].get('num_classes'))
|
||
|
|
if (not cfg.train_dataset) and (not cfg.val_dataset):
|
||
|
|
raise ValueError(
|
||
|
|
'One of `train_dataset` or `val_dataset should be given, but there are none.'
|
||
|
|
)
|
||
|
|
if len(num_classes_set) == 0:
|
||
|
|
raise ValueError(
|
||
|
|
'`num_classes` is not found. Please set it in model, train_dataset or val_dataset'
|
||
|
|
)
|
||
|
|
elif len(num_classes_set) > 1:
|
||
|
|
raise ValueError(
|
||
|
|
'`num_classes` is not consistent: {}. Please set it consistently in model or train_dataset or val_dataset'
|
||
|
|
.format(num_classes_set))
|
||
|
|
else:
|
||
|
|
num_classes = num_classes_set.pop()
|
||
|
|
if train_dataset:
|
||
|
|
train_dataset.num_classes = num_classes
|
||
|
|
if val_dataset:
|
||
|
|
val_dataset.num_classes = num_classes
|