PaddleClas/deploy/lite_shitu/src/picodet_postprocess.cc

130 lines
4.2 KiB
C++

// Copyright (c) 2021 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.
//
// The code is based on:
// https://github.com/RangiLyu/nanodet/blob/main/demo_mnn/nanodet_mnn.cpp
#include "include/picodet_postprocess.h"
#include <cmath>
namespace PPShiTu {
float fast_exp(float x) {
union {
uint32_t i;
float f;
} v{};
v.i = (1 << 23) * (1.4426950409 * x + 126.93490512f);
return v.f;
}
template <typename _Tp>
int activation_function_softmax(const _Tp *src, _Tp *dst, int length) {
const _Tp alpha = *std::max_element(src, src + length);
_Tp denominator{0};
for (int i = 0; i < length; ++i) {
dst[i] = fast_exp(src[i] - alpha);
denominator += dst[i];
}
for (int i = 0; i < length; ++i) {
dst[i] /= denominator;
}
return 0;
}
// PicoDet decode
PPShiTu::ObjectResult disPred2Bbox(const float *&dfl_det, int label,
float score, int x, int y, int stride,
std::vector<float> im_shape, int reg_max) {
float ct_x = (x + 0.5) * stride;
float ct_y = (y + 0.5) * stride;
std::vector<float> dis_pred;
dis_pred.resize(4);
for (int i = 0; i < 4; i++) {
float dis = 0;
float *dis_after_sm = new float[reg_max + 1];
activation_function_softmax(dfl_det + i * (reg_max + 1), dis_after_sm,
reg_max + 1);
for (int j = 0; j < reg_max + 1; j++) {
dis += j * dis_after_sm[j];
}
dis *= stride;
dis_pred[i] = dis;
delete[] dis_after_sm;
}
int xmin = (int)(std::max)(ct_x - dis_pred[0], .0f);
int ymin = (int)(std::max)(ct_y - dis_pred[1], .0f);
int xmax = (int)(std::min)(ct_x + dis_pred[2], (float)im_shape[0]);
int ymax = (int)(std::min)(ct_y + dis_pred[3], (float)im_shape[1]);
PPShiTu::ObjectResult result_item;
result_item.rect = {xmin, ymin, xmax, ymax};
result_item.class_id = label;
result_item.confidence = score;
return result_item;
}
void PicoDetPostProcess(std::vector<PPShiTu::ObjectResult> *results,
std::vector<const float *> outs,
std::vector<int> fpn_stride,
std::vector<float> im_shape,
std::vector<float> scale_factor, float score_threshold,
float nms_threshold, int num_class, int reg_max) {
std::vector<std::vector<PPShiTu::ObjectResult>> bbox_results;
bbox_results.resize(num_class);
int in_h = im_shape[0], in_w = im_shape[1];
for (int i = 0; i < fpn_stride.size(); ++i) {
int feature_h = ceil((float)in_h / fpn_stride[i]);
int feature_w = ceil((float)in_w / fpn_stride[i]);
for (int idx = 0; idx < feature_h * feature_w; idx++) {
const float *scores = outs[i] + (idx * num_class);
int row = idx / feature_w;
int col = idx % feature_w;
float score = 0;
int cur_label = 0;
for (int label = 0; label < num_class; label++) {
if (scores[label] > score) {
score = scores[label];
cur_label = label;
}
}
if (score > score_threshold) {
const float *bbox_pred =
outs[i + fpn_stride.size()] + (idx * 4 * (reg_max + 1));
bbox_results[cur_label].push_back(
disPred2Bbox(bbox_pred, cur_label, score, col, row, fpn_stride[i],
im_shape, reg_max));
}
}
}
for (int i = 0; i < (int)bbox_results.size(); i++) {
PPShiTu::nms(bbox_results[i], nms_threshold);
for (auto box : bbox_results[i]) {
box.rect[0] = box.rect[0] / scale_factor[1];
box.rect[2] = box.rect[2] / scale_factor[1];
box.rect[1] = box.rect[1] / scale_factor[0];
box.rect[3] = box.rect[3] / scale_factor[0];
results->push_back(box);
}
}
}
} // namespace PPShiTu