From eef9f8e5bb9fdbe22c6301a56f12e315f9ac64d9 Mon Sep 17 00:00:00 2001
From: AlexeyAB <alexeyab84@gmail.com>
Date: Wed, 23 May 2018 15:35:08 +0000
Subject: [PATCH] Minor fixes
---
src/yolo_v2_class.cpp | 79 ++++++++++++++++++++++-----------------
1 files changed, 44 insertions(+), 35 deletions(-)
diff --git a/src/yolo_v2_class.cpp b/src/yolo_v2_class.cpp
index 518ea65..03d581a 100644
--- a/src/yolo_v2_class.cpp
+++ b/src/yolo_v2_class.cpp
@@ -22,9 +22,16 @@
#define FRAMES 3
-struct detector_gpu_t{
- float **probs;
- box *boxes;
+#ifdef GPU
+void check_cuda(cudaError_t status) {
+ if (status != cudaSuccess) {
+ const char *s = cudaGetErrorString(status);
+ printf("CUDA Error Prev: %s\n", s);
+ }
+}
+#endif
+
+struct detector_gpu_t {
network net;
image images[FRAMES];
float *avg;
@@ -33,23 +40,24 @@
unsigned int *track_id;
};
-
YOLODLL_API Detector::Detector(std::string cfg_filename, std::string weight_filename, int gpu_id) : cur_gpu_id(gpu_id)
{
wait_stream = 0;
int old_gpu_index;
#ifdef GPU
- cudaGetDevice(&old_gpu_index);
+ check_cuda( cudaGetDevice(&old_gpu_index) );
#endif
detector_gpu_ptr = std::make_shared<detector_gpu_t>();
- detector_gpu_t &detector_gpu = *reinterpret_cast<detector_gpu_t *>(detector_gpu_ptr.get());
+ detector_gpu_t &detector_gpu = *static_cast<detector_gpu_t *>(detector_gpu_ptr.get());
#ifdef GPU
- cudaSetDevice(gpu_id);
+ //check_cuda( cudaSetDevice(cur_gpu_id) );
+ cuda_set_device(cur_gpu_id);
+ printf(" Used GPU %d \n", cur_gpu_id);
#endif
network &net = detector_gpu.net;
- net.gpu_index = gpu_id;
+ net.gpu_index = cur_gpu_id;
//gpu_index = i;
char *cfgfile = const_cast<char *>(cfg_filename.data());
@@ -60,7 +68,8 @@
load_weights(&net, weightfile);
}
set_batch_network(&net, 1);
- net.gpu_index = gpu_id;
+ net.gpu_index = cur_gpu_id;
+ fuse_conv_batchnorm(net);
layer l = net.layers[net.n - 1];
int j;
@@ -69,22 +78,18 @@
for (j = 0; j < FRAMES; ++j) detector_gpu.predictions[j] = (float *)calloc(l.outputs, sizeof(float));
for (j = 0; j < FRAMES; ++j) detector_gpu.images[j] = make_image(1, 1, 3);
- detector_gpu.boxes = (box *)calloc(l.w*l.h*l.n, sizeof(box));
- detector_gpu.probs = (float **)calloc(l.w*l.h*l.n, sizeof(float *));
- for (j = 0; j < l.w*l.h*l.n; ++j) detector_gpu.probs[j] = (float *)calloc(l.classes, sizeof(float));
-
detector_gpu.track_id = (unsigned int *)calloc(l.classes, sizeof(unsigned int));
for (j = 0; j < l.classes; ++j) detector_gpu.track_id[j] = 1;
#ifdef GPU
- cudaSetDevice(old_gpu_index);
+ check_cuda( cudaSetDevice(old_gpu_index) );
#endif
}
YOLODLL_API Detector::~Detector()
{
- detector_gpu_t &detector_gpu = *reinterpret_cast<detector_gpu_t *>(detector_gpu_ptr.get());
+ detector_gpu_t &detector_gpu = *static_cast<detector_gpu_t *>(detector_gpu_ptr.get());
layer l = detector_gpu.net.layers[detector_gpu.net.n - 1];
free(detector_gpu.track_id);
@@ -93,14 +98,10 @@
for (int j = 0; j < FRAMES; ++j) free(detector_gpu.predictions[j]);
for (int j = 0; j < FRAMES; ++j) if(detector_gpu.images[j].data) free(detector_gpu.images[j].data);
- for (int j = 0; j < l.w*l.h*l.n; ++j) free(detector_gpu.probs[j]);
- free(detector_gpu.boxes);
- free(detector_gpu.probs);
-
int old_gpu_index;
#ifdef GPU
cudaGetDevice(&old_gpu_index);
- cudaSetDevice(detector_gpu.net.gpu_index);
+ cuda_set_device(detector_gpu.net.gpu_index);
#endif
free_network(detector_gpu.net);
@@ -111,11 +112,11 @@
}
YOLODLL_API int Detector::get_net_width() const {
- detector_gpu_t &detector_gpu = *reinterpret_cast<detector_gpu_t *>(detector_gpu_ptr.get());
+ detector_gpu_t &detector_gpu = *static_cast<detector_gpu_t *>(detector_gpu_ptr.get());
return detector_gpu.net.w;
}
YOLODLL_API int Detector::get_net_height() const {
- detector_gpu_t &detector_gpu = *reinterpret_cast<detector_gpu_t *>(detector_gpu_ptr.get());
+ detector_gpu_t &detector_gpu = *static_cast<detector_gpu_t *>(detector_gpu_ptr.get());
return detector_gpu.net.h;
}
@@ -173,7 +174,7 @@
YOLODLL_API std::vector<bbox_t> Detector::detect(image_t img, float thresh, bool use_mean)
{
- detector_gpu_t &detector_gpu = *reinterpret_cast<detector_gpu_t *>(detector_gpu_ptr.get());
+ detector_gpu_t &detector_gpu = *static_cast<detector_gpu_t *>(detector_gpu_ptr.get());
network &net = detector_gpu.net;
int old_gpu_index;
#ifdef GPU
@@ -214,17 +215,21 @@
l.output = detector_gpu.avg;
detector_gpu.demo_index = (detector_gpu.demo_index + 1) % FRAMES;
}
+ //get_region_boxes(l, 1, 1, thresh, detector_gpu.probs, detector_gpu.boxes, 0, 0);
+ //if (nms) do_nms_sort(detector_gpu.boxes, detector_gpu.probs, l.w*l.h*l.n, l.classes, nms);
- get_region_boxes(l, 1, 1, thresh, detector_gpu.probs, detector_gpu.boxes, 0, 0);
- if (nms) do_nms_sort(detector_gpu.boxes, detector_gpu.probs, l.w*l.h*l.n, l.classes, nms);
- //draw_detections(im, l.w*l.h*l.n, thresh, boxes, probs, names, alphabet, l.classes);
+ int nboxes = 0;
+ int letterbox = 0;
+ float hier_thresh = 0.5;
+ detection *dets = get_network_boxes(&net, im.w, im.h, thresh, hier_thresh, 0, 1, &nboxes, letterbox);
+ if (nms) do_nms_sort(dets, nboxes, l.classes, nms);
std::vector<bbox_t> bbox_vec;
- for (size_t i = 0; i < (l.w*l.h*l.n); ++i) {
- box b = detector_gpu.boxes[i];
- int const obj_id = max_index(detector_gpu.probs[i], l.classes);
- float const prob = detector_gpu.probs[i][obj_id];
+ for (size_t i = 0; i < nboxes; ++i) {
+ box b = dets[i].bbox;
+ int const obj_id = max_index(dets[i].prob, l.classes);
+ float const prob = dets[i].prob[obj_id];
if (prob > thresh)
{
@@ -241,6 +246,7 @@
}
}
+ free_detections(dets, nboxes);
if(sized.data)
free(sized.data);
@@ -252,9 +258,10 @@
return bbox_vec;
}
-YOLODLL_API std::vector<bbox_t> Detector::tracking(std::vector<bbox_t> cur_bbox_vec, int const frames_story)
+YOLODLL_API std::vector<bbox_t> Detector::tracking_id(std::vector<bbox_t> cur_bbox_vec, bool const change_history,
+ int const frames_story, int const max_dist)
{
- detector_gpu_t &det_gpu = *reinterpret_cast<detector_gpu_t *>(detector_gpu_ptr.get());
+ detector_gpu_t &det_gpu = *static_cast<detector_gpu_t *>(detector_gpu_ptr.get());
bool prev_track_id_present = false;
for (auto &i : prev_bbox_vec_deque)
@@ -279,7 +286,7 @@
float center_x_diff = (float)(i.x + i.w/2) - (float)(k.x + k.w/2);
float center_y_diff = (float)(i.y + i.h/2) - (float)(k.y + k.h/2);
unsigned int cur_dist = sqrt(center_x_diff*center_x_diff + center_y_diff*center_y_diff);
- if (cur_dist < 100 && (k.track_id == 0 || dist_vec[m] > cur_dist)) {
+ if (cur_dist < max_dist && (k.track_id == 0 || dist_vec[m] > cur_dist)) {
dist_vec[m] = cur_dist;
cur_index = m;
}
@@ -301,8 +308,10 @@
if (cur_bbox_vec[i].track_id == 0)
cur_bbox_vec[i].track_id = det_gpu.track_id[cur_bbox_vec[i].obj_id]++;
- prev_bbox_vec_deque.push_front(cur_bbox_vec);
- if (prev_bbox_vec_deque.size() > frames_story) prev_bbox_vec_deque.pop_back();
+ if (change_history) {
+ prev_bbox_vec_deque.push_front(cur_bbox_vec);
+ if (prev_bbox_vec_deque.size() > frames_story) prev_bbox_vec_deque.pop_back();
+ }
return cur_bbox_vec;
}
\ No newline at end of file
--
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