From e34f0416f507499e9dbbc2557430850ba3a022ab Mon Sep 17 00:00:00 2001
From: AlexeyAB <alexeyab84@gmail.com>
Date: Fri, 04 Aug 2017 22:47:58 +0000
Subject: [PATCH] Added detection on images from the txt list file by using SO/DLL.
---
src/yolo_v2_class.cpp | 112 +++++++++++++++++++++++++++++++++++++++++++++++++++----
1 files changed, 103 insertions(+), 9 deletions(-)
diff --git a/src/yolo_v2_class.cpp b/src/yolo_v2_class.cpp
index c58ebda..a2fabcd 100644
--- a/src/yolo_v2_class.cpp
+++ b/src/yolo_v2_class.cpp
@@ -18,6 +18,7 @@
#include <vector>
#include <iostream>
+#include <algorithm>
#define FRAMES 3
@@ -28,18 +29,23 @@
image images[FRAMES];
float *avg;
float *predictions[FRAMES];
+ int demo_index;
};
YOLODLL_API Detector::Detector(std::string cfg_filename, std::string weight_filename, int gpu_id)
{
int old_gpu_index;
+#ifdef GPU
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());
+#ifdef GPU
cudaSetDevice(gpu_id);
+#endif
network &net = detector_gpu.net;
net.gpu_index = gpu_id;
//gpu_index = i;
@@ -65,7 +71,9 @@
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));
+#ifdef GPU
cudaSetDevice(old_gpu_index);
+#endif
}
@@ -78,25 +86,38 @@
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);
- for (int j = 0; j < l.w*l.h*l.n; ++j) free(detector_gpu.probs[j]);
int old_gpu_index;
+#ifdef GPU
cudaGetDevice(&old_gpu_index);
cudaSetDevice(detector_gpu.net.gpu_index);
+#endif
free_network(detector_gpu.net);
+#ifdef GPU
cudaSetDevice(old_gpu_index);
+#endif
+}
+
+YOLODLL_API int Detector::get_net_width() {
+ detector_gpu_t &detector_gpu = *reinterpret_cast<detector_gpu_t *>(detector_gpu_ptr.get());
+ return detector_gpu.net.w;
+}
+YOLODLL_API int Detector::get_net_height() {
+ detector_gpu_t &detector_gpu = *reinterpret_cast<detector_gpu_t *>(detector_gpu_ptr.get());
+ return detector_gpu.net.h;
}
-YOLODLL_API std::vector<bbox_t> Detector::detect(std::string image_filename, float thresh)
+YOLODLL_API std::vector<bbox_t> Detector::detect(std::string image_filename, float thresh, bool use_mean)
{
std::shared_ptr<image_t> image_ptr(new image_t, [](image_t *img) { if (img->data) free(img->data); delete img; });
*image_ptr = load_image(image_filename);
- return detect(*image_ptr, thresh);
+ return detect(*image_ptr, thresh, use_mean);
}
static image load_image_stb(char *filename, int channels)
@@ -143,17 +164,19 @@
}
}
-YOLODLL_API std::vector<bbox_t> Detector::detect(image_t img, float thresh)
+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());
network &net = detector_gpu.net;
int old_gpu_index;
+#ifdef GPU
cudaGetDevice(&old_gpu_index);
cudaSetDevice(net.gpu_index);
+#endif
//std::cout << "net.gpu_index = " << net.gpu_index << std::endl;
- float nms = .4;
+ //float nms = .4;
image im;
im.c = img.c;
@@ -161,12 +184,27 @@
im.h = img.h;
im.w = img.w;
- image sized = resize_image(im, net.w, net.h);
+ image sized;
+
+ if (net.w == im.w && net.h == im.h) {
+ sized = make_image(im.w, im.h, im.c);
+ memcpy(sized.data, im.data, im.w*im.h*im.c * sizeof(float));
+ }
+ else
+ sized = resize_image(im, net.w, net.h);
+
layer l = net.layers[net.n - 1];
float *X = sized.data;
- network_predict(net, X);
+ float *prediction = network_predict(net, X);
+
+ if (use_mean) {
+ memcpy(detector_gpu.predictions[detector_gpu.demo_index], prediction, l.outputs * sizeof(float));
+ mean_arrays(detector_gpu.predictions, FRAMES, l.outputs, detector_gpu.avg);
+ 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);
@@ -182,12 +220,13 @@
if (prob > thresh)
{
bbox_t bbox;
- bbox.x = (b.x - b.w / 2.)*im.w;
- bbox.y = (b.y - b.h / 2.)*im.h;
+ bbox.x = std::max((double)0, (b.x - b.w / 2.)*im.w);
+ bbox.y = std::max((double)0, (b.y - b.h / 2.)*im.h);
bbox.w = b.w*im.w;
bbox.h = b.h*im.h;
bbox.obj_id = obj_id;
bbox.prob = prob;
+ bbox.track_id = 0;
bbox_vec.push_back(bbox);
}
@@ -196,7 +235,62 @@
if(sized.data)
free(sized.data);
+#ifdef GPU
cudaSetDevice(old_gpu_index);
+#endif
return bbox_vec;
+}
+
+YOLODLL_API std::vector<bbox_t> Detector::tracking(std::vector<bbox_t> cur_bbox_vec, int const frames_story)
+{
+ bool prev_track_id_present = false;
+ for (auto &i : prev_bbox_vec_deque)
+ if (i.size() > 0) prev_track_id_present = true;
+
+ static unsigned int track_id = 1;
+
+ if (!prev_track_id_present) {
+ //track_id = 1;
+ for (size_t i = 0; i < cur_bbox_vec.size(); ++i)
+ cur_bbox_vec[i].track_id = track_id++;
+ 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;
+ }
+
+ std::vector<unsigned int> dist_vec(cur_bbox_vec.size(), std::numeric_limits<unsigned int>::max());
+
+ for (auto &prev_bbox_vec : prev_bbox_vec_deque) {
+ for (auto &i : prev_bbox_vec) {
+ int cur_index = -1;
+ for (size_t m = 0; m < cur_bbox_vec.size(); ++m) {
+ bbox_t const& k = cur_bbox_vec[m];
+ if (i.obj_id == k.obj_id) {
+ unsigned int cur_dist = sqrt(((float)i.x - k.x)*((float)i.x - k.x) + ((float)i.y - k.y)*((float)i.y - k.y));
+ if (cur_dist < 100 && (k.track_id == 0 || dist_vec[m] > cur_dist)) {
+ dist_vec[m] = cur_dist;
+ cur_index = m;
+ }
+ }
+ }
+
+ bool track_id_absent = !std::any_of(cur_bbox_vec.begin(), cur_bbox_vec.end(), [&](bbox_t const& b) { return b.track_id == i.track_id; });
+
+ if (cur_index >= 0 && track_id_absent) {
+ cur_bbox_vec[cur_index].track_id = i.track_id;
+ cur_bbox_vec[cur_index].w = (cur_bbox_vec[cur_index].w + i.w) / 2;
+ cur_bbox_vec[cur_index].h = (cur_bbox_vec[cur_index].h + i.h) / 2;
+ }
+ }
+ }
+
+ for (size_t i = 0; i < cur_bbox_vec.size(); ++i)
+ if (cur_bbox_vec[i].track_id == 0)
+ cur_bbox_vec[i].track_id = track_id++;
+
+ 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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