forked from PulseFocusPlatform/PulseFocusPlatform
103 lines
3.4 KiB
Python
103 lines
3.4 KiB
Python
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# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import os
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import sys
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# add python path of PadleDetection to sys.path
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parent_path = os.path.abspath(os.path.join(__file__, *(['..'] * 2)))
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if parent_path not in sys.path:
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sys.path.append(parent_path)
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from paddle import fluid
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import logging
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FORMAT = '%(asctime)s-%(levelname)s: %(message)s'
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logging.basicConfig(level=logging.INFO, format=FORMAT)
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logger = logging.getLogger(__name__)
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try:
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from ppdet.core.workspace import load_config, merge_config, create
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from ppdet.utils.cli import ArgsParser
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import ppdet.utils.checkpoint as checkpoint
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from ppdet.utils.export_utils import save_infer_model, dump_infer_config
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from ppdet.utils.check import check_config, check_version, check_py_func, enable_static_mode
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except ImportError as e:
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if sys.argv[0].find('static') >= 0:
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logger.error("Importing ppdet failed when running static model "
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"with error: {}\n"
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"please try:\n"
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"\t1. run static model under PaddleDetection/static "
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"directory\n"
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"\t2. run 'pip uninstall ppdet' to uninstall ppdet "
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"dynamic version firstly.".format(e))
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sys.exit(-1)
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else:
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raise e
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def main():
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cfg = load_config(FLAGS.config)
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merge_config(FLAGS.opt)
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check_config(cfg)
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check_version()
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main_arch = cfg.architecture
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# Use CPU for exporting inference model instead of GPU
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place = fluid.CPUPlace()
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exe = fluid.Executor(place)
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model = create(main_arch)
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startup_prog = fluid.Program()
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infer_prog = fluid.Program()
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with fluid.program_guard(infer_prog, startup_prog):
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with fluid.unique_name.guard():
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inputs_def = cfg['TestReader']['inputs_def']
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inputs_def['use_dataloader'] = False
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feed_vars, _ = model.build_inputs(**inputs_def)
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# postprocess not need in exclude_nms, exclude NMS in exclude_nms mode
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test_fetches = model.test(feed_vars, exclude_nms=FLAGS.exclude_nms)
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infer_prog = infer_prog.clone(True)
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check_py_func(infer_prog)
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exe.run(startup_prog)
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checkpoint.load_params(exe, infer_prog, cfg.weights)
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dump_infer_config(FLAGS, cfg)
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save_infer_model(FLAGS, exe, feed_vars, test_fetches, infer_prog)
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if __name__ == '__main__':
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enable_static_mode()
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parser = ArgsParser()
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parser.add_argument(
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"--output_dir",
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type=str,
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default="output",
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help="Directory for storing the output model files.")
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parser.add_argument(
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"--exclude_nms",
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action='store_true',
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default=False,
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help="Whether prune NMS for benchmark")
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FLAGS = parser.parse_args()
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main()
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