From 0039fd26786ab5f71d5af725fc18b3f521e7acfd Mon Sep 17 00:00:00 2001 From: AlexeyAB Date: Thu, 29 Mar 2018 20:47:17 +0300 Subject: [PATCH] Yolo v3 using SO/DLL library --- src/network.h | 1 + src/yolo_v2_class.cpp | 30 ++++++++++++------------------ 2 files changed, 13 insertions(+), 18 deletions(-) diff --git a/src/network.h b/src/network.h index d7f86c10d08..f3bb5425327 100644 --- a/src/network.h +++ b/src/network.h @@ -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); diff --git a/src/yolo_v2_class.cpp b/src/yolo_v2_class.cpp index 076bab8f3ab..be1b4ee9c73 100644 --- a/src/yolo_v2_class.cpp +++ b/src/yolo_v2_class.cpp @@ -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 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_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 Detector::detect(image_t img, float thresh, bool } } + free_detections(dets, nboxes); if(sized.data) free(sized.data);