更换文档检测模型

paddle_detection/tools/post_quant.py

@@ -0,0 +1,98 @@
+# Copyright (c) 2021 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
+
+# add python path of PaddleDetection to sys.path
+parent_path = os.path.abspath(os.path.join(__file__, *(['..'] * 2)))
+sys.path.insert(0, parent_path)
+
+# ignore warning log
+import warnings
+warnings.filterwarnings('ignore')
+
+import paddle
+
+from ppdet.core.workspace import load_config, merge_config
+from ppdet.utils.check import check_gpu, check_version, check_config
+from ppdet.utils.cli import ArgsParser
+from ppdet.engine import Trainer
+from ppdet.slim import build_slim_model
+
+from ppdet.utils.logger import setup_logger
+logger = setup_logger('post_quant')
+
+
+def parse_args():
+    parser = ArgsParser()
+    parser.add_argument(
+        "--output_dir",
+        type=str,
+        default="output_inference",
+        help="Directory for storing the output model files.")
+    parser.add_argument(
+        "--slim_config",
+        default=None,
+        type=str,
+        help="Configuration file of slim method.")
+    args = parser.parse_args()
+    return args
+
+
+def run(FLAGS, cfg):
+    # build detector
+    trainer = Trainer(cfg, mode='eval')
+
+    # load weights
+    if cfg.architecture in ['DeepSORT']:
+        if cfg.det_weights != 'None':
+            trainer.load_weights_sde(cfg.det_weights, cfg.reid_weights)
+        else:
+            trainer.load_weights_sde(None, cfg.reid_weights)
+    else:
+        trainer.load_weights(cfg.weights)
+
+    # post quant model
+    trainer.post_quant(FLAGS.output_dir)
+
+
+def main():
+    FLAGS = parse_args()
+    cfg = load_config(FLAGS.config)
+    # TODO: to be refined in the future
+    if 'norm_type' in cfg and cfg['norm_type'] == 'sync_bn':
+        FLAGS.opt['norm_type'] = 'bn'
+    merge_config(FLAGS.opt)
+
+    if FLAGS.slim_config:
+        cfg = build_slim_model(cfg, FLAGS.slim_config, mode='test')
+
+    # FIXME: Temporarily solve the priority problem of FLAGS.opt
+    merge_config(FLAGS.opt)
+    check_config(cfg)
+    if 'use_gpu' not in cfg:
+        cfg.use_gpu = False
+    check_gpu(cfg.use_gpu)
+    check_version()
+
+    run(FLAGS, cfg)
+
+
+if __name__ == '__main__':
+    main()