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6343b0db47
* Add notes for tensors * Optimize some apis * move some warnings * Support build with Paddle2ONNX * Add protobuf support * Fix compile on mac * add clearn package script * Add paddle2onnx code * remove submodule * Add onnx ocde * remove softlink * add onnx code * fix error * Add cmake file * fix patchelf * update paddle2onnx * Delete .gitmodules --------- Co-authored-by: PaddleCI <paddle_ci@example.com> Co-authored-by: pangyoki <pangyoki@126.com> Co-authored-by: jiangjiajun <jiangjiajun@baidu.lcom>
63 lines
2.1 KiB
C++
63 lines
2.1 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 <string>
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#include <vector>
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#include "paddle2onnx/mapper/mapper.h"
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namespace paddle2onnx {
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class NMSMapper : public Mapper {
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public:
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NMSMapper(const PaddleParser& p, OnnxHelper* helper, int64_t block_id,
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int64_t op_id)
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: Mapper(p, helper, block_id, op_id) {
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// NMS is a post process operators for object detection
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// We have found there're difference between `multi_class_nms3` in
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// PaddlePaddle and `NonMaxSuppresion` in ONNX
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MarkAsExperimentalOp();
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GetAttr("normalized", &normalized_);
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GetAttr("nms_threshold", &nms_threshold_);
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GetAttr("score_threshold", &score_threshold_);
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GetAttr("nms_eta", &nms_eta_);
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// The `nms_top_k` in Paddle and `max_output_boxes_per_class` in ONNX share
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// the same meaning But the filter process may not be same Since NMS is just
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// a post process for Detection, we are not going to export it with exactly
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// same result. We will make a precision performance in COCO or Pascal VOC
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// data later.
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GetAttr("nms_top_k", &nms_top_k_);
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GetAttr("background_label", &background_label_);
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GetAttr("keep_top_k", &keep_top_k_);
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}
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int32_t GetMinOpset(bool verbose = false);
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void KeepTopK(const std::string& selected_indices);
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void Opset10();
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void ExportForTensorRT();
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void ExportAsCustomOp();
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private:
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bool normalized_;
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float nms_threshold_;
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float score_threshold_;
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float nms_eta_;
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int64_t nms_top_k_;
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int64_t background_label_;
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int64_t keep_top_k_;
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};
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} // namespace paddle2onnx
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