mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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de7c06a309
* update .gitignore * Added checking for cmake include dir * fixed missing trt_backend option bug when init from trt * remove un-need data layout and add pre-check for dtype * changed RGB2BRG to BGR2RGB in ppcls model * add model_zoo yolov6 c++/python demo * fixed CMakeLists.txt typos * update yolov6 cpp/README.md
56 lines
1.8 KiB
Python
56 lines
1.8 KiB
Python
# Copyright (c) 2022 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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import logging
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from . import fastdeploy_main as C
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class FastDeployModel:
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def __init__(self, option):
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self._model = None
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self._runtime_option = option
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if self._runtime_option is None:
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self._runtime_option = C.RuntimeOption()
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def model_name(self):
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return self._model.model_name()
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def num_inputs(self):
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return self._model.num_inputs()
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def num_outputs(self):
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return self._model.num_outputs()
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def get_input_info(self, index):
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assert index < self.num_inputs(
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), "The index:{} must be less than number of inputs:{}.".format(
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index, self.num_inputs())
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return self._model.get_input_info(index)
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def get_output_info(self, index):
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assert index < self.num_outputs(
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), "The index:{} must be less than number of outputs:{}.".format(
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index, self.num_outputs())
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return self._model.get_output_info(index)
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@property
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def runtime_option(self):
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return self._model.runtime_option if self._model is not None else None
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@property
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def initialized(self):
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if self._model is None:
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return False
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return self._model.initialized()
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