mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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aa21272eaa
* add paddle_trt in benchmark * update benchmark in device * update benchmark * update result doc * fixed for CI * update python api_docs * update index.rst * add runtime cpp examples * deal with comments * Update infer_paddle_tensorrt.py * Add runtime quick start * deal with comments * fixed reused_input_tensors&&reused_output_tensors * fixed docs * fixed headpose typo * fixed typo * refactor yolov5 * update model infer * refactor pybind for yolov5 * rm origin yolov5 * fixed bugs * rm cuda preprocess * fixed bugs * fixed bugs * fixed bug * fixed bug * fix pybind * rm useless code * add convert_and_permute * fixed bugs * fixed im_info for bs_predict * fixed bug * add bs_predict for yolov5 * Add runtime test and batch eval * deal with comments * fixed bug * update testcase * fixed batch eval bug * fixed preprocess bug Co-authored-by: Jason <928090362@qq.com> Co-authored-by: Jason <jiangjiajun@baidu.com>
88 lines
3.0 KiB
C++
Executable File
88 lines
3.0 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/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 detection {
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/*! @brief Preprocessor object for YOLOv5 serials model.
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*/
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class FASTDEPLOY_DECL YOLOv5Preprocessor {
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public:
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/** \brief Create a preprocessor instance for YOLOv5 serials model
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*/
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YOLOv5Preprocessor();
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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 Run(std::vector<FDMat>* images, std::vector<FDTensor>* outputs,
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std::vector<std::map<std::string, std::array<float, 2>>>* ims_info);
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/// Set target size, tuple of (width, height), default size = {640, 640}
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void SetSize(const std::vector<int>& size) { size_ = size; }
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/// Get target size, tuple of (width, height), default size = {640, 640}
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std::vector<int> GetSize() const { return size_; }
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/// Set padding value, size should be the same as channels
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void SetPaddingValue(const std::vector<float>& padding_value) {
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padding_value_ = padding_value;
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}
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/// Get padding value, size should be the same as channels
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std::vector<float> GetPaddingValue() const { return padding_value_; }
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protected:
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bool Preprocess(FDMat* mat, FDTensor* output,
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std::map<std::string, std::array<float, 2>>* im_info);
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void LetterBox(FDMat* mat);
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// target size, tuple of (width, height), default size = {640, 640}
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std::vector<int> size_;
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// padding value, size should be the same as channels
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std::vector<float> padding_value_;
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// only pad to the minimum rectange which height and width is times of stride
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bool is_mini_pad_;
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// while is_mini_pad = false and is_no_pad = true,
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// will resize the image to the set size
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bool is_no_pad_;
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// if is_scale_up is false, the input image only can be zoom out,
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// the maximum resize scale cannot exceed 1.0
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bool is_scale_up_;
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// padding stride, for is_mini_pad
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int stride_;
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// for offseting the boxes by classes when using NMS
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float max_wh_;
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};
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} // namespace detection
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} // namespace vision
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} // namespace fastdeploy
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