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* * 更新picodet cpp代码 * * 更新文档 * 更新picodet cpp example * * 删除无用的debug代码 * 新增python example * * 修改c++代码 * * 修改python代码 * * 修改postprocess代码 * 修复没有scale_factor导致的bug * 修复错误 * 更正代码格式 * 更正代码格式
62 lines
2.2 KiB
C++
62 lines
2.2 KiB
C++
// 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 Postprocessor object for PaddleDet serials model.
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*/
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class FASTDEPLOY_DECL PaddleDetPostprocessor {
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public:
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PaddleDetPostprocessor() = default;
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/** \brief Process the result of runtime and fill to ClassifyResult structure
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*
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* \param[in] tensors The inference result from runtime
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* \param[in] result The output result of detection
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* \return true if the postprocess successed, otherwise false
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*/
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bool Run(const std::vector<FDTensor>& tensors,
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std::vector<DetectionResult>* result);
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/// Apply box decoding and nms step for the outputs for the model.This is
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/// only available for those model exported without box decoding and nms.
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void ApplyDecodeAndNMS();
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bool DecodeAndNMSApplied();
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/// Set scale_factor_ value.This is only available for those model exported
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/// without box decoding and nms.
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void SetScaleFactor(float* scale_factor_value);
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private:
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// Process mask tensor for MaskRCNN
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bool ProcessMask(const FDTensor& tensor,
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std::vector<DetectionResult>* results);
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bool apply_decode_and_nms_ = false;
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std::vector<float> scale_factor_{1.0, 1.0};
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std::vector<float> GetScaleFactor();
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bool ProcessUnDecodeResults(const std::vector<FDTensor>& tensors,
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std::vector<DetectionResult>* results);
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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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