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Move cpp code to directory csrcs (#42)

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* move cpp code to csrcs

* move cpp code to csrcs
This commit is contained in:
Jason
2022-07-26 17:59:02 +08:00
committed by GitHub
parent 7fa3afa9de
commit ffbc5cc42d
128 changed files with 1 additions and 1 deletions
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127
fastdeploy/vision/utils/nms.cc
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// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "fastdeploy/utils/perf.h"
#include "fastdeploy/vision/utils/utils.h"
namespace fastdeploy {
namespace vision {
namespace utils {
// The implementation refers to
// https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.4/deploy/cpp/src/utils.cc
void NMS(DetectionResult* result, float iou_threshold) {
utils::SortDetectionResult(result);
std::vector<float> area_of_boxes(result->boxes.size());
std::vector<int> suppressed(result->boxes.size(), 0);
for (size_t i = 0; i < result->boxes.size(); ++i) {
area_of_boxes[i] = (result->boxes[i][2] - result->boxes[i][0]) *
(result->boxes[i][3] - result->boxes[i][1]);
}
for (size_t i = 0; i < result->boxes.size(); ++i) {
if (suppressed[i] == 1) {
continue;
}
for (size_t j = i + 1; j < result->boxes.size(); ++j) {
if (suppressed[j] == 1) {
continue;
}
float xmin = std::max(result->boxes[i][0], result->boxes[j][0]);
float ymin = std::max(result->boxes[i][1], result->boxes[j][1]);
float xmax = std::min(result->boxes[i][2], result->boxes[j][2]);
float ymax = std::min(result->boxes[i][3], result->boxes[j][3]);
float overlap_w = std::max(0.0f, xmax - xmin);
float overlap_h = std::max(0.0f, ymax - ymin);
float overlap_area = overlap_w * overlap_h;
float overlap_ratio =
overlap_area / (area_of_boxes[i] + area_of_boxes[j] - overlap_area);
if (overlap_ratio > iou_threshold) {
suppressed[j] = 1;
}
}
}
DetectionResult backup(*result);
result->Clear();
result->Reserve(suppressed.size());
for (size_t i = 0; i < suppressed.size(); ++i) {
if (suppressed[i] == 1) {
continue;
}
result->boxes.emplace_back(backup.boxes[i]);
result->scores.push_back(backup.scores[i]);
result->label_ids.push_back(backup.label_ids[i]);
}
}
void NMS(FaceDetectionResult* result, float iou_threshold) {
utils::SortDetectionResult(result);
std::vector<float> area_of_boxes(result->boxes.size());
std::vector<int> suppressed(result->boxes.size(), 0);
for (size_t i = 0; i < result->boxes.size(); ++i) {
area_of_boxes[i] = (result->boxes[i][2] - result->boxes[i][0]) *
(result->boxes[i][3] - result->boxes[i][1]);
}
for (size_t i = 0; i < result->boxes.size(); ++i) {
if (suppressed[i] == 1) {
continue;
}
for (size_t j = i + 1; j < result->boxes.size(); ++j) {
if (suppressed[j] == 1) {
continue;
}
float xmin = std::max(result->boxes[i][0], result->boxes[j][0]);
float ymin = std::max(result->boxes[i][1], result->boxes[j][1]);
float xmax = std::min(result->boxes[i][2], result->boxes[j][2]);
float ymax = std::min(result->boxes[i][3], result->boxes[j][3]);
float overlap_w = std::max(0.0f, xmax - xmin);
float overlap_h = std::max(0.0f, ymax - ymin);
float overlap_area = overlap_w * overlap_h;
float overlap_ratio =
overlap_area / (area_of_boxes[i] + area_of_boxes[j] - overlap_area);
if (overlap_ratio > iou_threshold) {
suppressed[j] = 1;
}
}
}
FaceDetectionResult backup(*result);
int landmarks_per_face = result->landmarks_per_face;
result->Clear();
// don't forget to reset the landmarks_per_face
// before apply Reserve method.
result->landmarks_per_face = landmarks_per_face;
result->Reserve(suppressed.size());
for (size_t i = 0; i < suppressed.size(); ++i) {
if (suppressed[i] == 1) {
continue;
}
result->boxes.emplace_back(backup.boxes[i]);
result->scores.push_back(backup.scores[i]);
// landmarks (if have)
if (result->landmarks_per_face > 0) {
for (size_t j = 0; j < result->landmarks_per_face; ++j) {
result->landmarks.emplace_back(
backup.landmarks[i * result->landmarks_per_face + j]);
}
}
}
}
} // namespace utils
} // namespace vision
} // namespace fastdeploy