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https://github.com/PaddlePaddle/FastDeploy.git
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625845c7d6
* Update ppseg backend support type * Update ppseg preprocess if condition * Update README.md * Update README.md * Update README.md * Update ppseg with eigen functions * Delete old argmax function * Update README.md * Delete apply_softmax in ppseg example demo * Update ppseg code with createFromTensor function * Delete FDTensor2CVMat function * Update README.md * Update README.md * Update README.md * Update README.md * Update ppseg model.cc with transpose&&softmax in place convert * Update segmentation_result.md * Update model.cc * Update README.md * Update README.md Co-authored-by: Jason <jiangjiajun@baidu.com>
79 lines
2.5 KiB
C++
79 lines
2.5 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 <set>
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#include <vector>
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#include "fastdeploy/core/fd_tensor.h"
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#include "fastdeploy/utils/utils.h"
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#include "fastdeploy/vision/common/result.h"
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// #include "unsupported/Eigen/CXX11/Tensor"
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#include "fastdeploy/function/reduce.h"
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#include "fastdeploy/function/softmax.h"
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#include "fastdeploy/function/transpose.h"
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namespace fastdeploy {
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namespace vision {
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namespace utils {
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// topk sometimes is a very small value
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// so this implementation is simple but I don't think it will
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// cost too much time
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// Also there may be cause problem since we suppose the minimum value is
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// -99999999
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// Do not use this function on array which topk contains value less than
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// -99999999
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template <typename T>
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std::vector<int32_t> TopKIndices(const T* array, int array_size, int topk) {
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topk = std::min(array_size, topk);
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std::vector<int32_t> res(topk);
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std::set<int32_t> searched;
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for (int32_t i = 0; i < topk; ++i) {
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T min = -99999999;
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for (int32_t j = 0; j < array_size; ++j) {
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if (searched.find(j) != searched.end()) {
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continue;
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}
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if (*(array + j) > min) {
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res[i] = j;
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min = *(array + j);
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}
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}
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searched.insert(res[i]);
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}
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return res;
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}
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void NMS(DetectionResult* output, float iou_threshold = 0.5);
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void NMS(FaceDetectionResult* result, float iou_threshold = 0.5);
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// MergeSort
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void SortDetectionResult(DetectionResult* output);
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void SortDetectionResult(FaceDetectionResult* result);
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// L2 Norm / cosine similarity (for face recognition, ...)
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FASTDEPLOY_DECL std::vector<float> L2Normalize(
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const std::vector<float>& values);
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FASTDEPLOY_DECL float CosineSimilarity(const std::vector<float>& a,
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const std::vector<float>& b,
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bool normalized = true);
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} // namespace utils
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} // namespace vision
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} // namespace fastdeploy
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