From 04c0c4fdf84bb7b9e89604e8b9a6079016d5968c Mon Sep 17 00:00:00 2001
From: Alexey <AlexeyAB@users.noreply.github.com>
Date: Wed, 04 Jul 2018 16:06:41 +0000
Subject: [PATCH] Merge pull request #1132 from tinohager/master

---
 src/yolo_v2_class.cpp |   76 +++++++++++++++++++-------------------
 1 files changed, 38 insertions(+), 38 deletions(-)

diff --git a/src/yolo_v2_class.cpp b/src/yolo_v2_class.cpp
index a93f3b9..4df9be5 100644
--- a/src/yolo_v2_class.cpp
+++ b/src/yolo_v2_class.cpp
@@ -25,39 +25,39 @@
 //static Detector* detector = NULL;
 static std::unique_ptr<Detector> detector;
 
-int init(const char *configurationFilename, const char *weightsFilename, int gpu)
+int init(const char *configurationFilename, const char *weightsFilename, int gpu) 
 {
-	detector.reset(new Detector(configurationFilename, weightsFilename, gpu));
-	return 1;
+    detector.reset(new Detector(configurationFilename, weightsFilename, gpu));
+    return 1;
 }
 
-int detect_image(const char *filename, bbox_t_container &container)
+int detect_image(const char *filename, bbox_t_container &container) 
 {
-	std::vector<bbox_t> detection = detector->detect(filename);
-	for (size_t i = 0; i < detection.size() && i < C_SHARP_MAX_OBJECTS; ++i)
-		container.candidates[i] = detection[i];
-	return detection.size();
+    std::vector<bbox_t> detection = detector->detect(filename);
+    for (size_t i = 0; i < detection.size() && i < C_SHARP_MAX_OBJECTS; ++i)
+        container.candidates[i] = detection[i];
+    return detection.size();
 }
 
 int detect_mat(const uint8_t* data, const size_t data_length, bbox_t_container &container) {
 #ifdef OPENCV
-	std::vector<char> vdata(data, data + data_length);
-	cv::Mat image = imdecode(cv::Mat(vdata), 1);
+    std::vector<char> vdata(data, data + data_length);
+    cv::Mat image = imdecode(cv::Mat(vdata), 1);
 
-	std::vector<bbox_t> detection = detector->detect(image);
-	for (size_t i = 0; i < detection.size() && i < C_SHARP_MAX_OBJECTS; ++i)
-		container.candidates[i] = detection[i];
-	return detection.size();
+    std::vector<bbox_t> detection = detector->detect(image);
+    for (size_t i = 0; i < detection.size() && i < C_SHARP_MAX_OBJECTS; ++i)
+        container.candidates[i] = detection[i];
+    return detection.size();
 #else
-	return -1;
+    return -1;
 #endif	// OPENCV
 }
 
 int dispose() {
 	//if (detector != NULL) delete detector;
 	//detector = NULL;
-	detector.reset();
-	return 1;
+    detector.reset();
+    return 1;
 }
 
 #ifdef GPU
@@ -83,7 +83,7 @@
 	wait_stream = 0;
 	int old_gpu_index;
 #ifdef GPU
-	check_cuda(cudaGetDevice(&old_gpu_index));
+	check_cuda( cudaGetDevice(&old_gpu_index) );
 #endif
 
 	detector_gpu_ptr = std::make_shared<detector_gpu_t>();
@@ -97,7 +97,7 @@
 	network &net = detector_gpu.net;
 	net.gpu_index = cur_gpu_id;
 	//gpu_index = i;
-
+	
 	char *cfgfile = const_cast<char *>(cfg_filename.data());
 	char *weightfile = const_cast<char *>(weight_filename.data());
 
@@ -120,12 +120,12 @@
 	for (j = 0; j < l.classes; ++j) detector_gpu.track_id[j] = 1;
 
 #ifdef GPU
-	check_cuda(cudaSetDevice(old_gpu_index));
+	check_cuda( cudaSetDevice(old_gpu_index) );
 #endif
 }
 
 
-YOLODLL_API Detector::~Detector()
+YOLODLL_API Detector::~Detector() 
 {
 	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];
@@ -134,7 +134,7 @@
 
 	free(detector_gpu.avg);
 	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 < FRAMES; ++j) if(detector_gpu.images[j].data) free(detector_gpu.images[j].data);
 
 	int old_gpu_index;
 #ifdef GPU
@@ -174,7 +174,7 @@
 {
 	int w, h, c;
 	unsigned char *data = stbi_load(filename, &w, &h, &c, channels);
-	if (!data)
+	if (!data) 
 		throw std::runtime_error("file not found");
 	if (channels) c = channels;
 	int i, j, k;
@@ -182,8 +182,8 @@
 	for (k = 0; k < c; ++k) {
 		for (j = 0; j < h; ++j) {
 			for (i = 0; i < w; ++i) {
-				int dst_index = i + w * j + w * h*k;
-				int src_index = k + c * i + c * w*j;
+				int dst_index = i + w*j + w*h*k;
+				int src_index = k + c*i + c*w*j;
 				im.data[dst_index] = (float)data[src_index] / 255.;
 			}
 		}
@@ -221,14 +221,14 @@
 	int old_gpu_index;
 #ifdef GPU
 	cudaGetDevice(&old_gpu_index);
-	if (cur_gpu_id != old_gpu_index)
+	if(cur_gpu_id != old_gpu_index)
 		cudaSetDevice(net.gpu_index);
 
 	net.wait_stream = wait_stream;	// 1 - wait CUDA-stream, 0 - not to wait
 #endif
-									//std::cout << "net.gpu_index = " << net.gpu_index << std::endl;
+	//std::cout << "net.gpu_index = " << net.gpu_index << std::endl;
 
-									//float nms = .4;
+	//float nms = .4;
 
 	image im;
 	im.c = img.c;
@@ -237,7 +237,7 @@
 	im.w = img.w;
 
 	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));
@@ -272,8 +272,8 @@
 		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)
+		
+		if (prob > thresh) 
 		{
 			bbox_t bbox;
 			bbox.x = std::max((double)0, (b.x - b.w / 2.)*im.w);
@@ -289,7 +289,7 @@
 	}
 
 	free_detections(dets, nboxes);
-	if (sized.data)
+	if(sized.data)
 		free(sized.data);
 
 #ifdef GPU
@@ -300,7 +300,7 @@
 	return bbox_vec;
 }
 
-YOLODLL_API std::vector<bbox_t> Detector::tracking_id(std::vector<bbox_t> cur_bbox_vec, bool const change_history,
+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 = *static_cast<detector_gpu_t *>(detector_gpu_ptr.get());
@@ -325,9 +325,9 @@
 			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) {
-					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);
+					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 < max_dist && (k.track_id == 0 || dist_vec[m] > cur_dist)) {
 						dist_vec[m] = cur_dist;
 						cur_index = m;
@@ -335,10 +335,10 @@
 				}
 			}
 
-			bool track_id_absent = !std::any_of(cur_bbox_vec.begin(), cur_bbox_vec.end(),
+			bool track_id_absent = !std::any_of(cur_bbox_vec.begin(), cur_bbox_vec.end(), 
 				[&i](bbox_t const& b) { return b.track_id == i.track_id && b.obj_id == i.obj_id; });
 
-			if (cur_index >= 0 && track_id_absent) {
+			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;

--
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