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https://github.com/PaddlePaddle/FastDeploy.git
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39aca6787a
* Add multi-label function for yolov5 * Update README.md Update doc * Update fastdeploy_runtime.cc fix variable option.trt_max_shape wrong name * Update runtime_option.md Update resnet model dynamic shape setting name from images to x * Fix bug when inference result boxes are empty * Delete detection.py
82 lines
2.3 KiB
C++
82 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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#include "fastdeploy/vision/utils/utils.h"
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namespace fastdeploy {
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namespace vision {
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namespace utils {
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void Merge(DetectionResult* result, size_t low, size_t mid, size_t high) {
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std::vector<std::array<float, 4>>& boxes = result->boxes;
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std::vector<float>& scores = result->scores;
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std::vector<int32_t>& label_ids = result->label_ids;
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std::vector<std::array<float, 4>> temp_boxes(boxes);
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std::vector<float> temp_scores(scores);
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std::vector<int32_t> temp_label_ids(label_ids);
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size_t i = low;
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size_t j = mid + 1;
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size_t k = i;
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for (; i <= mid && j <= high; k++) {
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if (temp_scores[i] >= temp_scores[j]) {
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scores[k] = temp_scores[i];
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label_ids[k] = temp_label_ids[i];
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boxes[k] = temp_boxes[i];
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i++;
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} else {
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scores[k] = temp_scores[j];
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label_ids[k] = temp_label_ids[j];
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boxes[k] = temp_boxes[j];
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j++;
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}
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}
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while (i <= mid) {
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scores[k] = temp_scores[i];
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label_ids[k] = temp_label_ids[i];
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boxes[k] = temp_boxes[i];
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k++;
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i++;
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}
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while (j <= high) {
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scores[k] = temp_scores[j];
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label_ids[k] = temp_label_ids[j];
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boxes[k] = temp_boxes[j];
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k++;
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j++;
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}
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}
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void MergeSort(DetectionResult* result, size_t low, size_t high) {
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if (low < high) {
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size_t mid = (high - low) / 2 + low;
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MergeSort(result, low, mid);
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MergeSort(result, mid + 1, high);
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Merge(result, low, mid, high);
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}
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}
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void SortDetectionResult(DetectionResult* result) {
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size_t low = 0;
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size_t high = result->scores.size();
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if (high == 0) {
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return;
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}
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high = high - 1;
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MergeSort(result, low, high);
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}
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} // namespace utils
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} // namespace vision
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} // namespace fastdeploy
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