114 lines
3.8 KiB
Python
Executable File
114 lines
3.8 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 ppocr.utils.character import CharacterOps
|
|
|
|
|
|
def main():
|
|
config = program.load_config(FLAGS.config)
|
|
program.merge_config(FLAGS.opt)
|
|
logger.info(config)
|
|
|
|
# check if set use_gpu=True in paddlepaddle cpu version
|
|
use_gpu = config['Global']['use_gpu']
|
|
program.check_gpu(use_gpu)
|
|
|
|
alg = config['Global']['algorithm']
|
|
assert alg in ['EAST', 'DB', 'Rosetta', 'CRNN', 'STARNet', 'RARE']
|
|
if alg in ['Rosetta', 'CRNN', 'STARNet', 'RARE']:
|
|
config['Global']['char_ops'] = CharacterOps(config['Global'])
|
|
|
|
place = fluid.CUDAPlace(0) if use_gpu else fluid.CPUPlace()
|
|
startup_program = fluid.Program()
|
|
train_program = fluid.Program()
|
|
train_build_outputs = program.build(
|
|
config, train_program, startup_program, mode='train')
|
|
train_loader = train_build_outputs[0]
|
|
train_fetch_name_list = train_build_outputs[1]
|
|
train_fetch_varname_list = train_build_outputs[2]
|
|
train_opt_loss_name = train_build_outputs[3]
|
|
|
|
eval_program = fluid.Program()
|
|
eval_build_outputs = program.build(
|
|
config, eval_program, startup_program, mode='eval')
|
|
eval_fetch_name_list = eval_build_outputs[1]
|
|
eval_fetch_varname_list = eval_build_outputs[2]
|
|
eval_program = eval_program.clone(for_test=True)
|
|
|
|
train_reader = reader_main(config=config, mode="train")
|
|
train_loader.set_sample_list_generator(train_reader, places=place)
|
|
|
|
eval_reader = reader_main(config=config, mode="eval")
|
|
|
|
exe = fluid.Executor(place)
|
|
exe.run(startup_program)
|
|
|
|
# compile program for multi-devices
|
|
train_compile_program = program.create_multi_devices_program(
|
|
train_program, train_opt_loss_name)
|
|
init_model(config, train_program, exe)
|
|
|
|
train_info_dict = {'compile_program':train_compile_program,\
|
|
'train_program':train_program,\
|
|
'reader':train_loader,\
|
|
'fetch_name_list':train_fetch_name_list,\
|
|
'fetch_varname_list':train_fetch_varname_list}
|
|
|
|
eval_info_dict = {'program':eval_program,\
|
|
'reader':eval_reader,\
|
|
'fetch_name_list':eval_fetch_name_list,\
|
|
'fetch_varname_list':eval_fetch_varname_list}
|
|
|
|
if alg in ['EAST', 'DB']:
|
|
program.train_eval_det_run(config, exe, train_info_dict, eval_info_dict)
|
|
else:
|
|
program.train_eval_rec_run(config, exe, train_info_dict, eval_info_dict)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
parser = program.ArgsParser()
|
|
FLAGS = parser.parse_args()
|
|
main()
|
|
# test_reader()
|