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ade27d29cb
* [Sync][Internal] sync some internal codes * [Sync][Internal] sync some internal features of paddle3d inference * [Sync][Internal] sync some internal features of paddle3d inference
88 lines
3.7 KiB
C++
Executable File
88 lines
3.7 KiB
C++
Executable File
// 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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#pragma once
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#include "fastdeploy/vision/common/processors/manager.h"
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#include "fastdeploy/vision/common/processors/transform.h"
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#include "fastdeploy/vision/common/result.h"
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namespace fastdeploy {
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namespace vision {
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namespace perception {
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/*! @brief Preprocessor object for Petr serials model.
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*/
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class FASTDEPLOY_DECL PetrPreprocessor : public ProcessorManager {
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public:
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PetrPreprocessor() = default;
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/** \brief Create a preprocessor instance for Petr model
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*
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* \param[in] config_file Path of configuration file for deployment, e.g smoke/infer_cfg.yml
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*/
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explicit PetrPreprocessor(const std::string& config_file);
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/** \brief Process the input image and prepare input tensors for runtime
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*
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* \param[in] images The input image data list, all the elements are returned by cv::imread()
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* \param[in] outputs The output tensors which will feed in runtime
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* \param[in] ims_info The shape info list, record input_shape and output_shape
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* \return true if the preprocess successed, otherwise false
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*/
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bool Apply(FDMatBatch* image_batch, std::vector<FDTensor>* outputs);
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protected:
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bool BuildPreprocessPipelineFromConfig();
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std::vector<std::shared_ptr<Processor>> processors_;
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bool disable_permute_ = false;
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bool initialized_ = false;
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std::string config_file_;
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float scale_ = 1.0f;
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std::vector<float> mean_;
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std::vector<float> std_;
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std::vector<float> input_k_data_{
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-1.40307297e-03, 9.07780395e-06, 4.84838307e-01, -5.43047376e-02,
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-1.40780103e-04, 1.25770375e-05, 1.04126692e+00, 7.67668605e-01,
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-1.02884378e-05, -1.41007011e-03, 1.02823459e-01, -3.07415128e-01,
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0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 1.00000000e+00,
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-9.39000631e-04, -7.65239349e-07, 1.14073277e+00, 4.46270645e-01,
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1.04998052e-03, 1.91798881e-05, 2.06218868e-01, 7.42717385e-01,
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1.48074005e-05, -1.40855671e-03, 7.45946690e-02, -3.16081315e-01,
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0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 1.00000000e+00,
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-7.0699735e-04, 4.2389297e-07, -5.5183989e-01, -5.3276348e-01,
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-1.2281288e-03, 2.5626015e-05, 1.0212017e+00, 6.1102939e-01,
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-2.2421273e-05, -1.4170362e-03, 9.3639769e-02, -3.0863306e-01,
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0.0000000e+00, 0.0000000e+00, 0.0000000e+00, 1.0000000e+00,
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2.2227580e-03, 2.5312484e-06, -9.7261822e-01, 9.0684637e-02,
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1.9360810e-04, 2.1347081e-05, -1.0779887e+00, -7.9227984e-01,
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4.3742721e-06, -2.2310747e-03, 1.0842450e-01, -2.9406491e-01,
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0.0000000e+00, 0.0000000e+00, 0.0000000e+00, 1.0000000e+00,
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5.97175560e-04, -5.88774265e-06, -1.15893924e+00, -4.49921310e-01,
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-1.28312141e-03, 3.58297058e-07, 1.48300052e-01, 1.14334166e-01,
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-2.80917516e-06, -1.41527120e-03, 8.37693438e-02, -2.36765608e-01,
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0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 1.00000000e+00,
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3.6048229e-04, 3.8333174e-06, 7.9871160e-01, 4.3321830e-01,
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1.3671946e-03, 6.7484652e-06, -8.4722507e-01, 1.9411178e-01,
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7.5027779e-06, -1.4139183e-03, 8.2083985e-02, -2.4505949e-01,
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0.0000000e+00, 0.0000000e+00, 0.0000000e+00, 1.0000000e+00};
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};
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} // namespace perception
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} // namespace vision
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} // namespace fastdeploy
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