89 lines
3.2 KiB
Python
Executable File
89 lines
3.2 KiB
Python
Executable File
# 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.
|
|
|
|
from __future__ import absolute_import
|
|
from __future__ import division
|
|
from __future__ import print_function
|
|
|
|
import os
|
|
import sys
|
|
__dir__ = os.path.dirname(__file__)
|
|
sys.path.append(__dir__)
|
|
sys.path.append(os.path.join(__dir__, '..'))
|
|
|
|
|
|
def set_paddle_flags(**kwargs):
|
|
for key, value in kwargs.items():
|
|
if os.environ.get(key, None) is None:
|
|
os.environ[key] = str(value)
|
|
|
|
|
|
# NOTE(paddle-dev): All of these flags should be
|
|
# set before `import paddle`. Otherwise, it would
|
|
# not take any effect.
|
|
set_paddle_flags(
|
|
FLAGS_eager_delete_tensor_gb=0, # enable GC to save memory
|
|
)
|
|
|
|
import program
|
|
from paddle import fluid
|
|
from ppocr.utils.utility import initial_logger
|
|
logger = initial_logger()
|
|
from ppocr.data.reader_main import reader_main
|
|
from ppocr.utils.save_load import init_model
|
|
from eval_utils.eval_det_utils import eval_det_run
|
|
from eval_utils.eval_rec_utils import test_rec_benchmark
|
|
from eval_utils.eval_rec_utils import eval_rec_run
|
|
|
|
|
|
def main():
|
|
startup_prog, eval_program, place, config, train_alg_type = program.preprocess()
|
|
eval_build_outputs = program.build(
|
|
config, eval_program, startup_prog, mode='test')
|
|
eval_fetch_name_list = eval_build_outputs[1]
|
|
eval_fetch_varname_list = eval_build_outputs[2]
|
|
eval_program = eval_program.clone(for_test=True)
|
|
exe = fluid.Executor(place)
|
|
exe.run(startup_prog)
|
|
|
|
init_model(config, eval_program, exe)
|
|
|
|
if train_alg_type == 'det':
|
|
eval_reader = reader_main(config=config, mode="eval")
|
|
eval_info_dict = {'program':eval_program,\
|
|
'reader':eval_reader,\
|
|
'fetch_name_list':eval_fetch_name_list,\
|
|
'fetch_varname_list':eval_fetch_varname_list}
|
|
metrics = eval_det_run(exe, config, eval_info_dict, "eval")
|
|
logger.info("Eval result: {}".format(metrics))
|
|
else:
|
|
reader_type = config['Global']['reader_yml']
|
|
if "benchmark" not in reader_type:
|
|
eval_reader = reader_main(config=config, mode="eval")
|
|
eval_info_dict = {'program': eval_program, \
|
|
'reader': eval_reader, \
|
|
'fetch_name_list': eval_fetch_name_list, \
|
|
'fetch_varname_list': eval_fetch_varname_list}
|
|
metrics = eval_rec_run(exe, config, eval_info_dict, "eval")
|
|
logger.info("Eval result: {}".format(metrics))
|
|
else:
|
|
eval_info_dict = {'program':eval_program,\
|
|
'fetch_name_list':eval_fetch_name_list,\
|
|
'fetch_varname_list':eval_fetch_varname_list}
|
|
test_rec_benchmark(exe, config, eval_info_dict)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
main()
|