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Yolo v3 using SO/DLL library

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This commit is contained in:
AlexeyAB
2018-03-29 20:47:17 +03:00
parent d0039f6dfd
commit 0039fd2678
2 changed files with 13 additions and 18 deletions
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1
src/network.h
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@ -133,6 +133,7 @@ void set_batch_network(network *net, int b);
int get_network_input_size(network net);
float get_network_cost(network net);
detection *get_network_boxes(network *net, int w, int h, float thresh, float hier, int *map, int relative, int *num, int letter);
void free_detections(detection *dets, int n);
int get_network_nuisance(network net);
int get_network_background(network net);

30
src/yolo_v2_class.cpp
View File

@ -32,8 +32,6 @@ void check_cuda(cudaError_t status) {
#endif
struct detector_gpu_t {
float **probs;
box *boxes;
network net;
image images[FRAMES];
float *avg;
@ -79,10 +77,6 @@ YOLODLL_API Detector::Detector(std::string cfg_filename, std::string weight_file
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;
@ -103,14 +97,9 @@ YOLODLL_API Detector::~Detector()
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
@ -225,17 +214,21 @@ YOLODLL_API std::vector<bbox_t> Detector::detect(image_t img, float thresh, bool
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_v3(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)
{
@ -252,6 +245,7 @@ YOLODLL_API std::vector<bbox_t> Detector::detect(image_t img, float thresh, bool
}
}
free_detections(dets, nboxes);
if(sized.data)
free(sized.data);