109 lines
4.4 KiB
Python
109 lines
4.4 KiB
Python
# 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(os.path.abspath(__file__))
|
|
sys.path.insert(0, __dir__)
|
|
sys.path.insert(0, os.path.abspath(os.path.join(__dir__, '..')))
|
|
|
|
from ppocr.data import build_dataloader
|
|
from ppocr.modeling.architectures import build_model
|
|
from ppocr.postprocess import build_post_process
|
|
from ppocr.metrics import build_metric
|
|
from ppocr.utils.save_load import load_model
|
|
import tools.program as program
|
|
|
|
|
|
def main():
|
|
global_config = config['Global']
|
|
# build dataloader
|
|
valid_dataloader = build_dataloader(config, 'Eval', device, logger)
|
|
|
|
# build post process
|
|
post_process_class = build_post_process(config['PostProcess'],
|
|
global_config)
|
|
|
|
# build model
|
|
# for rec algorithm
|
|
if hasattr(post_process_class, 'character'):
|
|
char_num = len(getattr(post_process_class, 'character'))
|
|
if config['Architecture']["algorithm"] in ["Distillation",
|
|
]: # distillation model
|
|
for key in config['Architecture']["Models"]:
|
|
if config['Architecture']['Models'][key]['Head'][
|
|
'name'] == 'MultiHead': # for multi head
|
|
out_channels_list = {}
|
|
if config['PostProcess'][
|
|
'name'] == 'DistillationSARLabelDecode':
|
|
char_num = char_num - 2
|
|
out_channels_list['CTCLabelDecode'] = char_num
|
|
out_channels_list['SARLabelDecode'] = char_num + 2
|
|
config['Architecture']['Models'][key]['Head'][
|
|
'out_channels_list'] = out_channels_list
|
|
else:
|
|
config['Architecture']["Models"][key]["Head"][
|
|
'out_channels'] = char_num
|
|
elif config['Architecture']['Head'][
|
|
'name'] == 'MultiHead': # for multi head
|
|
out_channels_list = {}
|
|
if config['PostProcess']['name'] == 'SARLabelDecode':
|
|
char_num = char_num - 2
|
|
out_channels_list['CTCLabelDecode'] = char_num
|
|
out_channels_list['SARLabelDecode'] = char_num + 2
|
|
config['Architecture']['Head'][
|
|
'out_channels_list'] = out_channels_list
|
|
else: # base rec model
|
|
config['Architecture']["Head"]['out_channels'] = char_num
|
|
|
|
model = build_model(config['Architecture'])
|
|
extra_input_models = ["SRN", "NRTR", "SAR", "SEED", "SVTR", "VisionLAN"]
|
|
extra_input = False
|
|
if config['Architecture']['algorithm'] == 'Distillation':
|
|
for key in config['Architecture']["Models"]:
|
|
extra_input = extra_input or config['Architecture']['Models'][key][
|
|
'algorithm'] in extra_input_models
|
|
else:
|
|
extra_input = config['Architecture']['algorithm'] in extra_input_models
|
|
if "model_type" in config['Architecture'].keys():
|
|
model_type = config['Architecture']['model_type']
|
|
else:
|
|
model_type = None
|
|
|
|
best_model_dict = load_model(
|
|
config, model, model_type=config['Architecture']["model_type"])
|
|
if len(best_model_dict):
|
|
logger.info('metric in ckpt ***************')
|
|
for k, v in best_model_dict.items():
|
|
logger.info('{}:{}'.format(k, v))
|
|
|
|
# build metric
|
|
eval_class = build_metric(config['Metric'])
|
|
# start eval
|
|
metric = program.eval(model, valid_dataloader, post_process_class,
|
|
eval_class, model_type, extra_input)
|
|
logger.info('metric eval ***************')
|
|
for k, v in metric.items():
|
|
logger.info('{}:{}'.format(k, v))
|
|
|
|
|
|
if __name__ == '__main__':
|
|
config, device, logger, vdl_writer = program.preprocess()
|
|
main()
|