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a9b5c6ed85
* Support compile on windows x86 * fix cmake Co-authored-by: root <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com>
81 lines
2.3 KiB
C++
81 lines
2.3 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 <map>
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#ifndef NON_64_PLATFORM
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#include "onnxruntime_cxx_api.h" // NOLINT
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namespace fastdeploy {
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struct MultiClassNmsKernel {
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protected:
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int64_t background_label = -1;
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int64_t keep_top_k = -1;
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float nms_eta;
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float nms_threshold = 0.7;
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int64_t nms_top_k;
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bool normalized;
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float score_threshold;
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Ort::CustomOpApi ort_;
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public:
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MultiClassNmsKernel(Ort::CustomOpApi ort, const OrtKernelInfo* info)
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: ort_(ort) {
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GetAttribute(info);
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}
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void GetAttribute(const OrtKernelInfo* info);
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void Compute(OrtKernelContext* context);
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void FastNMS(const float* boxes, const float* scores, const int& num_boxes,
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std::vector<int>* keep_indices);
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int NMSForEachSample(const float* boxes, const float* scores, int num_boxes,
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int num_classes,
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std::map<int, std::vector<int>>* keep_indices);
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};
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struct MultiClassNmsOp
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: Ort::CustomOpBase<MultiClassNmsOp, MultiClassNmsKernel> {
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void* CreateKernel(Ort::CustomOpApi api, const OrtKernelInfo* info) const {
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return new MultiClassNmsKernel(api, info);
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}
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const char* GetName() const { return "MultiClassNMS"; }
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size_t GetInputTypeCount() const { return 2; }
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ONNXTensorElementDataType GetInputType(size_t index) const {
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return ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT;
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}
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size_t GetOutputTypeCount() const { return 3; }
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ONNXTensorElementDataType GetOutputType(size_t index) const {
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if (index == 0) {
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return ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT;
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}
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return ONNX_TENSOR_ELEMENT_DATA_TYPE_INT32;
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}
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const char* GetExecutionProviderType() const {
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return "CPUExecutionProvider";
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}
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};
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} // namespace fastdeploy
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#endif |