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[Model] Refactor YOLOv5 module (PaddlePaddle#562)
* 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 <[email protected]> Co-authored-by: Jason <[email protected]>
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fastdeploy/vision/common/processors/convert_and_permute.cc
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// Copyright (c) 2022 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. | ||
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#include "fastdeploy/vision/common/processors/convert_and_permute.h" | ||
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namespace fastdeploy { | ||
namespace vision { | ||
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ConvertAndPermute::ConvertAndPermute(const std::vector<float>& alpha, | ||
const std::vector<float>& beta, | ||
bool swap_rb) { | ||
FDASSERT(alpha.size() == beta.size(), | ||
"ConvertAndPermute: requires the size of alpha equal to the size of beta."); | ||
FDASSERT(alpha.size() > 0 && beta.size() > 0, | ||
"ConvertAndPermute: requires the size of alpha and beta > 0."); | ||
alpha_.assign(alpha.begin(), alpha.end()); | ||
beta_.assign(beta.begin(), beta.end()); | ||
swap_rb_ = swap_rb; | ||
} | ||
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bool ConvertAndPermute::ImplByOpenCV(FDMat* mat) { | ||
cv::Mat* im = mat->GetOpenCVMat(); | ||
int origin_w = im->cols; | ||
int origin_h = im->rows; | ||
std::vector<cv::Mat> split_im; | ||
cv::split(*im, split_im); | ||
if (swap_rb_) std::swap(split_im[0], split_im[2]); | ||
for (int c = 0; c < im->channels(); c++) { | ||
split_im[c].convertTo(split_im[c], CV_32FC1, alpha_[c], beta_[c]); | ||
} | ||
cv::Mat res(origin_h, origin_w, CV_32FC(im->channels())); | ||
for (int i = 0; i < im->channels(); ++i) { | ||
cv::extractChannel(split_im[i], | ||
cv::Mat(origin_h, origin_w, CV_32FC1, | ||
res.ptr() + i * origin_h * origin_w * 4), | ||
0); | ||
} | ||
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mat->SetMat(res); | ||
mat->layout = Layout::CHW; | ||
return true; | ||
} | ||
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#ifdef ENABLE_FLYCV | ||
bool ConvertAndPermute::ImplByFlyCV(FDMat* mat) { | ||
if (mat->layout != Layout::HWC) { | ||
FDERROR << "Only supports input with HWC layout." << std::endl; | ||
return false; | ||
} | ||
fcv::Mat* im = mat->GetFlyCVMat(); | ||
if (im->channels() != 3) { | ||
FDERROR << "Only supports 3-channels image in FlyCV, but now it's " | ||
<< im->channels() << "." << std::endl; | ||
return false; | ||
} | ||
std::vector<float> mean(3, 0); | ||
std::vector<float> std(3, 0); | ||
for (size_t i = 0; i < 3; ++i) { | ||
std[i] = 1.0 / alpha_[i]; | ||
mean[i] = -1 * beta_[i] * std[i]; | ||
} | ||
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std::vector<uint32_t> channel_reorder_index = {0, 1, 2}; | ||
if (swap_rb_) std::swap(channel_reorder_index[0], channel_reorder_index[2]); | ||
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fcv::Mat new_im; | ||
fcv::normalize_to_submean_to_reorder(*im, mean, std, channel_reorder_index, | ||
new_im, false); | ||
mat->SetMat(new_im); | ||
mat->layout = Layout::CHW; | ||
return true; | ||
} | ||
#endif | ||
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bool ConvertAndPermute::Run(FDMat* mat, const std::vector<float>& alpha, | ||
const std::vector<float>& beta, bool swap_rb, | ||
ProcLib lib) { | ||
auto n = ConvertAndPermute(alpha, beta, swap_rb); | ||
return n(mat, lib); | ||
} | ||
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} // namespace vision | ||
} // namespace fastdeploy |
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// Copyright (c) 2022 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. | ||
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#pragma once | ||
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#include "fastdeploy/vision/common/processors/base.h" | ||
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namespace fastdeploy { | ||
namespace vision { | ||
class FASTDEPLOY_DECL ConvertAndPermute : public Processor { | ||
public: | ||
ConvertAndPermute(const std::vector<float>& alpha = std::vector<float>(), | ||
const std::vector<float>& beta = std::vector<float>(), | ||
bool swap_rb = false); | ||
bool ImplByOpenCV(FDMat* mat); | ||
#ifdef ENABLE_FLYCV | ||
bool ImplByFlyCV(FDMat* mat); | ||
#endif | ||
std::string Name() { return "ConvertAndPermute"; } | ||
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static bool Run(FDMat* mat, const std::vector<float>& alpha, | ||
const std::vector<float>& beta, bool swap_rb = false, | ||
ProcLib lib = ProcLib::DEFAULT); | ||
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std::vector<float> GetAlpha() const { return alpha_; } | ||
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void SetAlpha(const std::vector<float>& alpha) { | ||
alpha_.clear(); | ||
std::vector<float>().swap(alpha_); | ||
alpha_.assign(alpha.begin(), alpha.end()); | ||
} | ||
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std::vector<float> GetBeta() const { return beta_; } | ||
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void SetBeta(const std::vector<float>& beta) { | ||
beta_.clear(); | ||
std::vector<float>().swap(beta_); | ||
beta_.assign(beta.begin(), beta.end()); | ||
} | ||
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bool GetSwapRB() { | ||
return swap_rb_; | ||
} | ||
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void SetSwapRB(bool swap_rb) { | ||
swap_rb_ = swap_rb; | ||
} | ||
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private: | ||
std::vector<float> alpha_; | ||
std::vector<float> beta_; | ||
bool swap_rb_; | ||
}; | ||
} // namespace vision | ||
} // namespace fastdeploy |
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