Files
xtensa_dsp/test/npu_test/detect.cpp
2022-09-13 10:33:44 +08:00

246 lines
6.7 KiB
C++

#include <math.h>
#include <stdio.h>
#include <string>
#include <vector>
#include <algorithm>
#include "detect.h"
int num_class = 21;
float nms_threshold = 0.45f;
int nms_top_k = 100;
int keep_top_k = 100;
float confidence_threshold = 0.51f;
static inline float intersection_area(const BBoxRect& a, const BBoxRect& b)
{
if (a.xmin > b.xmax || a.xmax < b.xmin || a.ymin > b.ymax || a.ymax < b.ymin)
{
// no intersection
return 0.f;
}
float inter_width = std::min(a.xmax, b.xmax) - std::max(a.xmin, b.xmin);
float inter_height = std::min(a.ymax, b.ymax) - std::max(a.ymin, b.ymin);
return inter_width * inter_height;
}
template <typename T>
static void qsort_descent_inplace(std::vector<T>& datas, std::vector<float>& scores, int left, int right)
{
int i = left;
int j = right;
//must be instanced ... so this function must include vector
float p = scores[(left + right) / 2];
while (i <= j)
{
while (scores[i] > p)
i++;
while (scores[j] < p)
j--;
if (i <= j)
{
// swap
std::swap(datas[i], datas[j]);
std::swap(scores[i], scores[j]);
i++;
j--;
}
}
if (left < j)
qsort_descent_inplace(datas, scores, left, j);
if (i < right)
qsort_descent_inplace(datas, scores, i, right);
}
template <typename T>
static void qsort_descent_inplace(std::vector<T>& datas, std::vector<float>& scores)
{
if (datas.empty() || scores.empty())
return;
qsort_descent_inplace(datas, scores, 0, scores.size() - 1);
}
static void nms_sorted_bboxes(const std::vector<BBoxRect>& bboxes, std::vector<int>& picked, float nms_threshold)
{
picked.clear();
const int n = bboxes.size();
std::vector<float> areas(n);
for (int i = 0; i < n; i++)
{
const BBoxRect& r = bboxes[i];
float width = r.xmax - r.xmin;
float height = r.ymax - r.ymin;
areas[i] = width * height;
}
for (int i = 0; i < n; i++)
{
const BBoxRect& a = bboxes[i];
int keep = 1;
for (int j = 0; j < (int)picked.size(); j++)
{
const BBoxRect& b = bboxes[picked[j]];
float interarea = intersection_area(a, b);
float unionarea = areas[i] + areas[picked[j]] - interarea;
if (interarea / unionarea > nms_threshold)
keep = 0;
}
if (keep)
picked.push_back(i);
}
}
int ssdforward(float *location,float * confidence,float * priorbox,BBox *bboxes,BBoxOut *out)
{
const float* location_ptr = location;
const float* priorbox_ptr = priorbox;
const float* variance_ptr = priorbox + num_prior*4;
for (int i = 0; i < num_prior; i++)
{
const float* loc = location_ptr + i * 4;
const float* pb = priorbox_ptr + i * 4;
const float* var = variance_ptr;// + i * 4;
float* bbox = (float*)&bboxes[i];// bboxes.row(i);
// CENTER_SIZE
float pb_w = pb[2] - pb[0];
float pb_h = pb[3] - pb[1];
float pb_cx = (pb[0] + pb[2]) * 0.5f;
float pb_cy = (pb[1] + pb[3]) * 0.5f;
float bbox_cx = var[0] * loc[0] * pb_w + pb_cx;
float bbox_cy = var[1] * loc[1] * pb_h + pb_cy;
float bbox_w = exp(var[2] * loc[2]) * pb_w;
float bbox_h = exp(var[3] * loc[3]) * pb_h;
bbox[0] = bbox_cx - bbox_w * 0.5f;
bbox[1] = bbox_cy - bbox_h * 0.5f;
bbox[2] = bbox_cx + bbox_w * 0.5f;
bbox[3] = bbox_cy + bbox_h * 0.5f;
}
// sort and nms for each class
std::vector< std::vector<BBoxRect> > all_class_bbox_rects;
std::vector< std::vector<float> > all_class_bbox_scores;
all_class_bbox_rects.resize(num_class);
all_class_bbox_scores.resize(num_class);
// start from 1 to ignore background class
for (int i = 1; i < num_class; i++)
{
// filter by confidence_threshold
std::vector<BBoxRect> class_bbox_rects;
std::vector<float> class_bbox_scores;
for (int j = 0; j < num_prior; j++)
{
float score = confidence[j * num_class + i];
if (score > confidence_threshold)
{
const float* bbox = (float*)&bboxes[j];
BBoxRect c = { bbox[0], bbox[1], bbox[2], bbox[3], i };
class_bbox_rects.push_back(c);
class_bbox_scores.push_back(score);
}
}
// sort inplace
qsort_descent_inplace(class_bbox_rects, class_bbox_scores);
// keep nms_top_k
if (nms_top_k < (int)class_bbox_rects.size())
{
class_bbox_rects.resize(nms_top_k);
class_bbox_scores.resize(nms_top_k);
}
// apply nms
std::vector<int> picked;
nms_sorted_bboxes(class_bbox_rects, picked, nms_threshold);
// select
for (int j = 0; j < (int)picked.size(); j++)
{
int z = picked[j];
all_class_bbox_rects[i].push_back(class_bbox_rects[z]);
all_class_bbox_scores[i].push_back(class_bbox_scores[z]);
}
}
// gather all class
std::vector<BBoxRect> bbox_rects;
std::vector<float> bbox_scores;
for (int i = 1; i < num_class; i++)
{
const std::vector<BBoxRect>& class_bbox_rects = all_class_bbox_rects[i];
const std::vector<float>& class_bbox_scores = all_class_bbox_scores[i];
bbox_rects.insert(bbox_rects.end(), class_bbox_rects.begin(), class_bbox_rects.end());
bbox_scores.insert(bbox_scores.end(), class_bbox_scores.begin(), class_bbox_scores.end());
}
// global sort inplace
qsort_descent_inplace(bbox_rects, bbox_scores);
// keep_top_k
if (keep_top_k < (int)bbox_rects.size())
{
bbox_rects.resize(keep_top_k);
bbox_scores.resize(keep_top_k);
}
int num_detected = bbox_rects.size();
if(num_detected >100) num_detected =100;
for (int i = 0; i < num_detected; i++)
{
const BBoxRect& r = bbox_rects[i];
float score = bbox_scores[i];
float* outptr = (float*)&out[i];
int *labelptr = (int *)outptr;
labelptr[0] = r.label;
outptr[1] = score;
outptr[2] = r.xmin;
outptr[3] = r.ymin;
outptr[4] = r.xmax;
outptr[5] = r.ymax;
}
return num_detected;
}
int readbintomem(float *dst,char *path)
{
FILE *pFile = fopen (path, "rb" );
if (pFile==NULL)
{
fputs ("File error",stderr);
exit (1);
}
fseek (pFile , 0 , SEEK_END);
int fsize = ftell(pFile);
rewind (pFile);
//buffer = (char*) malloc (sizeof(char)*lSize);
int result = fread (dst,1,fsize,pFile);
fclose(pFile);
return result;
}