From 3459c47bfa02d23d300df9a44ba3ec9c958850fe Mon Sep 17 00:00:00 2001
From: Philip Kahn <tigerhawkvok@gmail.com>
Date: Fri, 04 May 2018 21:00:11 +0000
Subject: [PATCH] Also replace root version to Python3
---
src/yolo_v2_class.cpp | 31 +++++++++++++------------------
1 files changed, 13 insertions(+), 18 deletions(-)
diff --git a/src/yolo_v2_class.cpp b/src/yolo_v2_class.cpp
index 076bab8..03d581a 100644
--- a/src/yolo_v2_class.cpp
+++ b/src/yolo_v2_class.cpp
@@ -32,8 +32,6 @@
#endif
struct detector_gpu_t {
- float **probs;
- box *boxes;
network net;
image images[FRAMES];
float *avg;
@@ -71,6 +69,7 @@
}
set_batch_network(&net, 1);
net.gpu_index = cur_gpu_id;
+ fuse_conv_batchnorm(net);
layer l = net.layers[net.n - 1];
int j;
@@ -79,10 +78,6 @@
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 +98,9 @@
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 +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)
{
@@ -252,6 +246,7 @@
}
}
+ free_detections(dets, nboxes);
if(sized.data)
free(sized.data);
--
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