yolo_v2_class.h

#pragma once
#ifdef YOLODLL_EXPORTS
#if defined(_MSC_VER)
#define YOLODLL_API __declspec(dllexport) 
#else
#define YOLODLL_API __attribute__((visibility("default")))
#endif
#else
#if defined(_MSC_VER)
#define YOLODLL_API __declspec(dllimport) 
#else
#define YOLODLL_API
#endif
#endif

struct bbox_t {
	unsigned int x, y, w, h;	// (x,y) - top-left corner, (w, h) - width & height of bounded box
	float prob;					// confidence - probability that the object was found correctly
	unsigned int obj_id;		// class of object - from range [0, classes-1]
	unsigned int track_id;		// tracking id for video (0 - untracked, 1 - inf - tracked object)
	unsigned int frames_counter;// counter of frames on which the object was detected
};

struct image_t {
	int h;						// height
	int w;						// width
	int c;						// number of chanels (3 - for RGB)
	float *data;				// pointer to the image data
};

#ifdef __cplusplus
#include <memory>
#include <vector>
#include <deque>
#include <algorithm>


#include <opencv2/opencv.hpp>			// C++
#include "opencv2/highgui/highgui_c.h"	// C
#include "opencv2/imgproc/imgproc_c.h"	// C


class Detector {
	std::shared_ptr<void> detector_gpu_ptr;
	std::deque<std::vector<bbox_t>> prev_bbox_vec_deque;
	const int cur_gpu_id;
public:
	float nms = .4;
	bool wait_stream;

	YOLODLL_API Detector(std::string cfg_filename, std::string weight_filename, int gpu_id = 0);
	YOLODLL_API ~Detector();

	YOLODLL_API std::vector<bbox_t> detect(std::string image_filename, float thresh = 0.2, bool use_mean = false);
	YOLODLL_API std::vector<bbox_t> detect(image_t img, float thresh = 0.2, bool use_mean = false);
	static YOLODLL_API image_t load_image(std::string image_filename);
	static YOLODLL_API void free_image(image_t m);
	YOLODLL_API int get_net_width() const;
	YOLODLL_API int get_net_height() const;
	YOLODLL_API int get_net_color_depth() const;

	YOLODLL_API std::vector<bbox_t> tracking_id(std::vector<bbox_t> cur_bbox_vec, bool const change_history = true, 
												int const frames_story = 10, int const max_dist = 150);

	std::vector<bbox_t> detect_resized(image_t img, int init_w, int init_h, float thresh = 0.2, bool use_mean = false)
	{
		if (img.data == NULL)
			throw std::runtime_error("Image is empty");
		auto detection_boxes = detect(img, thresh, use_mean);
		float wk = (float)init_w / img.w, hk = (float)init_h / img.h;
		for (auto &i : detection_boxes) i.x *= wk, i.w *= wk, i.y *= hk, i.h *= hk;
		return detection_boxes;
	}


	std::vector<bbox_t> detect(cv::Mat mat, float thresh = 0.2, bool use_mean = false)
	{
		if(mat.data == NULL)
			throw std::runtime_error("Image is empty");
		auto image_ptr = mat_to_image_resize(mat);
		return detect_resized(*image_ptr, mat.cols, mat.rows, thresh, use_mean);
	}

	std::shared_ptr<image_t> mat_to_image_resize(cv::Mat mat) const
	{
		if (mat.data == NULL) return std::shared_ptr<image_t>(NULL);
		cv::Mat det_mat;
		cv::resize(mat, det_mat, cv::Size(get_net_width(), get_net_height()));
		return mat_to_image(det_mat);
	}

	static std::shared_ptr<image_t> mat_to_image(cv::Mat img_src)
	{
		cv::Mat img;
		cv::cvtColor(img_src, img, cv::COLOR_RGB2BGR);
		std::shared_ptr<image_t> image_ptr(new image_t, [](image_t *img) { free_image(*img); delete img; });
		std::shared_ptr<IplImage> ipl_small = std::make_shared<IplImage>(img);
		*image_ptr = ipl_to_image(ipl_small.get());
		return image_ptr;
	}

private:

	static image_t ipl_to_image(IplImage* src)
	{
		unsigned char *data = (unsigned char *)src->imageData;
		int h = src->height;
		int w = src->width;
		int c = src->nChannels;
		int step = src->widthStep;
		image_t out = make_image_custom(w, h, c);
		int count = 0;

		for (int k = 0; k < c; ++k) {
			for (int i = 0; i < h; ++i) {
				int i_step = i*step;
				for (int j = 0; j < w; ++j) {
					out.data[count++] = data[i_step + j*c + k] / 255.;
				}
			}
		}

		return out;
	}

	static image_t make_empty_image(int w, int h, int c)
	{
		image_t out;
		out.data = 0;
		out.h = h;
		out.w = w;
		out.c = c;
		return out;
	}

	static image_t make_image_custom(int w, int h, int c)
	{
		image_t out = make_empty_image(w, h, c);
		out.data = (float *)calloc(h*w*c, sizeof(float));
		return out;
	}



};



#if defined(TRACK_OPTFLOW) && defined(OPENCV) && defined(GPU)

#include <opencv2/cudaoptflow.hpp>
#include <opencv2/cudaimgproc.hpp>
#include <opencv2/cudaarithm.hpp>
#include <opencv2/core/cuda.hpp>

class Tracker_optflow {
public:
	const int gpu_count;
	const int gpu_id;
	const int flow_error;


	Tracker_optflow(int _gpu_id = 0, int win_size = 9, int max_level = 3, int iterations = 8000, int _flow_error = -1) :
		gpu_count(cv::cuda::getCudaEnabledDeviceCount()), gpu_id(std::min(_gpu_id, gpu_count-1)),
		flow_error((_flow_error > 0)? _flow_error:(win_size*4))
	{
		int const old_gpu_id = cv::cuda::getDevice();
		cv::cuda::setDevice(gpu_id);

		stream = cv::cuda::Stream();

		sync_PyrLKOpticalFlow_gpu = cv::cuda::SparsePyrLKOpticalFlow::create();
		sync_PyrLKOpticalFlow_gpu->setWinSize(cv::Size(win_size, win_size));	// 9, 15, 21, 31
		sync_PyrLKOpticalFlow_gpu->setMaxLevel(max_level);		// +- 3 pt
		sync_PyrLKOpticalFlow_gpu->setNumIters(iterations);	// 2000, def: 30

		cv::cuda::setDevice(old_gpu_id);
	}

	// just to avoid extra allocations
	cv::cuda::GpuMat src_mat_gpu;
	cv::cuda::GpuMat dst_mat_gpu, dst_grey_gpu;
	cv::cuda::GpuMat prev_pts_flow_gpu, cur_pts_flow_gpu;
	cv::cuda::GpuMat status_gpu, err_gpu;

	cv::cuda::GpuMat src_grey_gpu;	// used in both functions
	cv::Ptr<cv::cuda::SparsePyrLKOpticalFlow> sync_PyrLKOpticalFlow_gpu;
	cv::cuda::Stream stream;

	std::vector<bbox_t> cur_bbox_vec;
	std::vector<bool> good_bbox_vec_flags;
	cv::Mat prev_pts_flow_cpu;

	void update_cur_bbox_vec(std::vector<bbox_t> _cur_bbox_vec)
	{
		cur_bbox_vec = _cur_bbox_vec;
		good_bbox_vec_flags = std::vector<bool>(cur_bbox_vec.size(), true);
		cv::Mat prev_pts, cur_pts_flow_cpu;

		for (auto &i : cur_bbox_vec) {
			float x_center = (i.x + i.w / 2.0F);
			float y_center = (i.y + i.h / 2.0F);
			prev_pts.push_back(cv::Point2f(x_center, y_center));
		}

		if (prev_pts.rows == 0)
			prev_pts_flow_cpu = cv::Mat();
		else
			cv::transpose(prev_pts, prev_pts_flow_cpu);

		if (prev_pts_flow_gpu.cols < prev_pts_flow_cpu.cols) {
			prev_pts_flow_gpu = cv::cuda::GpuMat(prev_pts_flow_cpu.size(), prev_pts_flow_cpu.type());
			cur_pts_flow_gpu = cv::cuda::GpuMat(prev_pts_flow_cpu.size(), prev_pts_flow_cpu.type());

			status_gpu = cv::cuda::GpuMat(prev_pts_flow_cpu.size(), CV_8UC1);
			err_gpu = cv::cuda::GpuMat(prev_pts_flow_cpu.size(), CV_32FC1);
		}

		prev_pts_flow_gpu.upload(cv::Mat(prev_pts_flow_cpu), stream);
	}


	void update_tracking_flow(cv::Mat src_mat, std::vector<bbox_t> _cur_bbox_vec)
	{
		int const old_gpu_id = cv::cuda::getDevice();
		if (old_gpu_id != gpu_id)
			cv::cuda::setDevice(gpu_id);

		if (src_mat.channels() == 3) {
			if (src_mat_gpu.cols == 0) {
				src_mat_gpu = cv::cuda::GpuMat(src_mat.size(), src_mat.type());
				src_grey_gpu = cv::cuda::GpuMat(src_mat.size(), CV_8UC1);
			}

			update_cur_bbox_vec(_cur_bbox_vec);

			//src_grey_gpu.upload(src_mat, stream);	// use BGR
			src_mat_gpu.upload(src_mat, stream);
			cv::cuda::cvtColor(src_mat_gpu, src_grey_gpu, CV_BGR2GRAY, 1, stream);
		}
		if (old_gpu_id != gpu_id)
			cv::cuda::setDevice(old_gpu_id);
	}


	std::vector<bbox_t> tracking_flow(cv::Mat dst_mat, bool check_error = true)
	{
		if (sync_PyrLKOpticalFlow_gpu.empty()) {
			std::cout << "sync_PyrLKOpticalFlow_gpu isn't initialized \n";
			return cur_bbox_vec;
		}

		int const old_gpu_id = cv::cuda::getDevice();
		if(old_gpu_id != gpu_id)
			cv::cuda::setDevice(gpu_id);

		if (dst_mat_gpu.cols == 0) {
			dst_mat_gpu = cv::cuda::GpuMat(dst_mat.size(), dst_mat.type());
			dst_grey_gpu = cv::cuda::GpuMat(dst_mat.size(), CV_8UC1);
		}

		//dst_grey_gpu.upload(dst_mat, stream);	// use BGR
		dst_mat_gpu.upload(dst_mat, stream);
		cv::cuda::cvtColor(dst_mat_gpu, dst_grey_gpu, CV_BGR2GRAY, 1, stream);

		if (src_grey_gpu.rows != dst_grey_gpu.rows || src_grey_gpu.cols != dst_grey_gpu.cols) {
			stream.waitForCompletion();
			src_grey_gpu = dst_grey_gpu.clone();
			cv::cuda::setDevice(old_gpu_id);
			return cur_bbox_vec;
		}

		////sync_PyrLKOpticalFlow_gpu.sparse(src_grey_gpu, dst_grey_gpu, prev_pts_flow_gpu, cur_pts_flow_gpu, status_gpu, &err_gpu);	// OpenCV 2.4.x
		sync_PyrLKOpticalFlow_gpu->calc(src_grey_gpu, dst_grey_gpu, prev_pts_flow_gpu, cur_pts_flow_gpu, status_gpu, err_gpu, stream);	// OpenCV 3.x

		cv::Mat cur_pts_flow_cpu;
		cur_pts_flow_gpu.download(cur_pts_flow_cpu, stream);

		dst_grey_gpu.copyTo(src_grey_gpu, stream);

		cv::Mat err_cpu, status_cpu;
		err_gpu.download(err_cpu, stream);
		status_gpu.download(status_cpu, stream);

		stream.waitForCompletion();

		std::vector<bbox_t> result_bbox_vec;

		if (err_cpu.cols == cur_bbox_vec.size() && status_cpu.cols == cur_bbox_vec.size()) 
		{
			for (size_t i = 0; i < cur_bbox_vec.size(); ++i)
			{
				cv::Point2f cur_key_pt = cur_pts_flow_cpu.at<cv::Point2f>(0, i);
				cv::Point2f prev_key_pt = prev_pts_flow_cpu.at<cv::Point2f>(0, i);

				float moved_x = cur_key_pt.x - prev_key_pt.x;
				float moved_y = cur_key_pt.y - prev_key_pt.y;

				if (abs(moved_x) < 100 && abs(moved_y) < 100 && good_bbox_vec_flags[i])
					if (err_cpu.at<float>(0, i) < flow_error && status_cpu.at<unsigned char>(0, i) != 0 &&
						((float)cur_bbox_vec[i].x + moved_x) > 0 && ((float)cur_bbox_vec[i].y + moved_y) > 0)
					{
						cur_bbox_vec[i].x += moved_x + 0.5;
						cur_bbox_vec[i].y += moved_y + 0.5;
						result_bbox_vec.push_back(cur_bbox_vec[i]);
					}
					else good_bbox_vec_flags[i] = false;
				else good_bbox_vec_flags[i] = false;

				//if(!check_error && !good_bbox_vec_flags[i]) result_bbox_vec.push_back(cur_bbox_vec[i]);
			}
		}

		cur_pts_flow_gpu.swap(prev_pts_flow_gpu);
		cur_pts_flow_cpu.copyTo(prev_pts_flow_cpu);

		if (old_gpu_id != gpu_id)
			cv::cuda::setDevice(old_gpu_id);

		return result_bbox_vec;
	}

};

#elif defined(TRACK_OPTFLOW) && defined(OPENCV)

//#include <opencv2/optflow.hpp>
#include <opencv2/video/tracking.hpp>

class Tracker_optflow {
public:
	const int flow_error;


	Tracker_optflow(int win_size = 9, int max_level = 3, int iterations = 8000, int _flow_error = -1) :
		flow_error((_flow_error > 0)? _flow_error:(win_size*4))
	{
		sync_PyrLKOpticalFlow = cv::SparsePyrLKOpticalFlow::create();
		sync_PyrLKOpticalFlow->setWinSize(cv::Size(win_size, win_size));	// 9, 15, 21, 31
		sync_PyrLKOpticalFlow->setMaxLevel(max_level);		// +- 3 pt

	}

	// just to avoid extra allocations
	cv::Mat dst_grey;
	cv::Mat prev_pts_flow, cur_pts_flow;
	cv::Mat status, err;

	cv::Mat src_grey;	// used in both functions
	cv::Ptr<cv::SparsePyrLKOpticalFlow> sync_PyrLKOpticalFlow;

	std::vector<bbox_t> cur_bbox_vec;
	std::vector<bool> good_bbox_vec_flags;

	void update_cur_bbox_vec(std::vector<bbox_t> _cur_bbox_vec)
	{
		cur_bbox_vec = _cur_bbox_vec;
		good_bbox_vec_flags = std::vector<bool>(cur_bbox_vec.size(), true);
		cv::Mat prev_pts, cur_pts_flow;

		for (auto &i : cur_bbox_vec) {
			float x_center = (i.x + i.w / 2.0F);
			float y_center = (i.y + i.h / 2.0F);
			prev_pts.push_back(cv::Point2f(x_center, y_center));
		}

		if (prev_pts.rows == 0)
			prev_pts_flow = cv::Mat();
		else
			cv::transpose(prev_pts, prev_pts_flow);
	}


	void update_tracking_flow(cv::Mat new_src_mat, std::vector<bbox_t> _cur_bbox_vec)
	{
		if (new_src_mat.channels() == 3) {

			update_cur_bbox_vec(_cur_bbox_vec);

			cv::cvtColor(new_src_mat, src_grey, CV_BGR2GRAY, 1);
		}
	}


	std::vector<bbox_t> tracking_flow(cv::Mat new_dst_mat, bool check_error = true)
	{
		if (sync_PyrLKOpticalFlow.empty()) {
			std::cout << "sync_PyrLKOpticalFlow isn't initialized \n";
			return cur_bbox_vec;
		}

		cv::cvtColor(new_dst_mat, dst_grey, CV_BGR2GRAY, 1);

		if (src_grey.rows != dst_grey.rows || src_grey.cols != dst_grey.cols) {
			src_grey = dst_grey.clone();
			return cur_bbox_vec;
		}

		if (prev_pts_flow.cols < 1) {
			return cur_bbox_vec;
		}

		////sync_PyrLKOpticalFlow_gpu.sparse(src_grey_gpu, dst_grey_gpu, prev_pts_flow_gpu, cur_pts_flow_gpu, status_gpu, &err_gpu);	// OpenCV 2.4.x
		sync_PyrLKOpticalFlow->calc(src_grey, dst_grey, prev_pts_flow, cur_pts_flow, status, err);	// OpenCV 3.x

		dst_grey.copyTo(src_grey);

		std::vector<bbox_t> result_bbox_vec;

		if (err.rows == cur_bbox_vec.size() && status.rows == cur_bbox_vec.size())
		{
			for (size_t i = 0; i < cur_bbox_vec.size(); ++i)
			{
				cv::Point2f cur_key_pt = cur_pts_flow.at<cv::Point2f>(0, i);
				cv::Point2f prev_key_pt = prev_pts_flow.at<cv::Point2f>(0, i);

				float moved_x = cur_key_pt.x - prev_key_pt.x;
				float moved_y = cur_key_pt.y - prev_key_pt.y;

				if (abs(moved_x) < 100 && abs(moved_y) < 100 && good_bbox_vec_flags[i])
					if (err.at<float>(0, i) < flow_error && status.at<unsigned char>(0, i) != 0 &&
						((float)cur_bbox_vec[i].x + moved_x) > 0 && ((float)cur_bbox_vec[i].y + moved_y) > 0)
					{
						cur_bbox_vec[i].x += moved_x + 0.5;
						cur_bbox_vec[i].y += moved_y + 0.5;
						result_bbox_vec.push_back(cur_bbox_vec[i]);
					}
					else good_bbox_vec_flags[i] = false;
				else good_bbox_vec_flags[i] = false;

				//if(!check_error && !good_bbox_vec_flags[i]) result_bbox_vec.push_back(cur_bbox_vec[i]);
			}
		}

		prev_pts_flow = cur_pts_flow.clone();

		return result_bbox_vec;
	}

};
#else

class Tracker_optflow {};

#endif	// defined(TRACK_OPTFLOW) && defined(OPENCV)


#ifdef OPENCV

static cv::Scalar obj_id_to_color(int obj_id) {
	int const colors[6][3] = { { 1,0,1 },{ 0,0,1 },{ 0,1,1 },{ 0,1,0 },{ 1,1,0 },{ 1,0,0 } };
	int const offset = obj_id * 123457 % 6;
	int const color_scale = 150 + (obj_id * 123457) % 100;
	cv::Scalar color(colors[offset][0], colors[offset][1], colors[offset][2]);
	color *= color_scale;
	return color;
}

class preview_boxes_t {
	enum { frames_history = 30 };	// how long to keep the history saved

	struct preview_box_track_t {
		unsigned int track_id, obj_id, last_showed_frames_ago;
		bool current_detection;
		bbox_t bbox;
		cv::Mat mat_obj, mat_resized_obj;
		preview_box_track_t() : track_id(0), obj_id(0), last_showed_frames_ago(frames_history), current_detection(false) {}
	};
	std::vector<preview_box_track_t> preview_box_track_id;
	size_t const preview_box_size, bottom_offset;
	bool const one_off_detections;
public:
	preview_boxes_t(size_t _preview_box_size = 100, size_t _bottom_offset = 100, bool _one_off_detections = false) :
		preview_box_size(_preview_box_size), bottom_offset(_bottom_offset), one_off_detections(_one_off_detections)
	{}

	void set(cv::Mat src_mat, std::vector<bbox_t> result_vec)
	{
		size_t const count_preview_boxes = src_mat.cols / preview_box_size;
		if (preview_box_track_id.size() != count_preview_boxes) preview_box_track_id.resize(count_preview_boxes);

		// increment frames history
		for (auto &i : preview_box_track_id)
			i.last_showed_frames_ago = std::min((unsigned)frames_history, i.last_showed_frames_ago + 1);

		// occupy empty boxes
		for (auto &k : result_vec) {
			bool found = false;
			// find the same (track_id)
			for (auto &i : preview_box_track_id) {
				if (i.track_id == k.track_id) {
					if (!one_off_detections) i.last_showed_frames_ago = 0; // for tracked objects
					found = true;
					break;
				}
			}
			if (!found) {
				// find empty box
				for (auto &i : preview_box_track_id) {
					if (i.last_showed_frames_ago == frames_history) {
						if (!one_off_detections && k.frames_counter == 0) break; // don't show if obj isn't tracked yet
						i.track_id = k.track_id;
						i.obj_id = k.obj_id;
						i.bbox = k;
						i.last_showed_frames_ago = 0;
						break;
					}
				}
			}
		}

		// draw preview box (from old or current frame)
		for (size_t i = 0; i < preview_box_track_id.size(); ++i)
		{
			// get object image
			cv::Mat dst = preview_box_track_id[i].mat_resized_obj;
			preview_box_track_id[i].current_detection = false;

			for (auto &k : result_vec) {
				if (preview_box_track_id[i].track_id == k.track_id) {
					if (one_off_detections && preview_box_track_id[i].last_showed_frames_ago > 0) {
						preview_box_track_id[i].last_showed_frames_ago = frames_history; break;
					}
					bbox_t b = k;
					cv::Rect r(b.x, b.y, b.w, b.h);
					cv::Rect img_rect(cv::Point2i(0, 0), src_mat.size());
					cv::Rect rect_roi = r & img_rect;
					if (rect_roi.width > 1 || rect_roi.height > 1) {
						cv::Mat roi = src_mat(rect_roi);
						cv::resize(roi, dst, cv::Size(preview_box_size, preview_box_size), cv::INTER_NEAREST);
						preview_box_track_id[i].mat_obj = roi.clone();
						preview_box_track_id[i].mat_resized_obj = dst.clone();
						preview_box_track_id[i].current_detection = true;
						preview_box_track_id[i].bbox = k;
					}
					break;
				}
			}
		}
	}


	void draw(cv::Mat draw_mat, bool show_small_boxes = false)
	{
		// draw preview box (from old or current frame)
		for (size_t i = 0; i < preview_box_track_id.size(); ++i)
		{
			auto &prev_box = preview_box_track_id[i];

			// draw object image
			cv::Mat dst = prev_box.mat_resized_obj;
			if (prev_box.last_showed_frames_ago < frames_history &&
				dst.size() == cv::Size(preview_box_size, preview_box_size))
			{
				cv::Rect dst_rect_roi(cv::Point2i(i * preview_box_size, draw_mat.rows - bottom_offset), dst.size());
				cv::Mat dst_roi = draw_mat(dst_rect_roi);
				dst.copyTo(dst_roi);

				cv::Scalar color = obj_id_to_color(prev_box.obj_id);
				int thickness = (prev_box.current_detection) ? 5 : 1;
				cv::rectangle(draw_mat, dst_rect_roi, color, thickness);

				unsigned int const track_id = prev_box.track_id;
				std::string track_id_str = (track_id > 0) ? std::to_string(track_id) : "";
				putText(draw_mat, track_id_str, dst_rect_roi.tl() - cv::Point2i(-4, 5), cv::FONT_HERSHEY_COMPLEX_SMALL, 0.9, cv::Scalar(0, 0, 0), 2);

				std::string size_str = std::to_string(prev_box.bbox.w) + "x" + std::to_string(prev_box.bbox.h);
				putText(draw_mat, size_str, dst_rect_roi.tl() + cv::Point2i(0, 12), cv::FONT_HERSHEY_COMPLEX_SMALL, 0.8, cv::Scalar(0, 0, 0), 1);

				if (!one_off_detections && prev_box.current_detection) {
					cv::line(draw_mat, dst_rect_roi.tl() + cv::Point2i(preview_box_size, 0),
						cv::Point2i(prev_box.bbox.x, prev_box.bbox.y + prev_box.bbox.h),
						color);
				}

				if (one_off_detections && show_small_boxes) {
					cv::Rect src_rect_roi(cv::Point2i(prev_box.bbox.x, prev_box.bbox.y),
						cv::Size(prev_box.bbox.w, prev_box.bbox.h));
					unsigned int const color_history = (255 * prev_box.last_showed_frames_ago) / frames_history;
					color = cv::Scalar(255 - 3 * color_history, 255 - 2 * color_history, 255 - 1 * color_history);
					if (prev_box.mat_obj.size() == src_rect_roi.size()) {
						prev_box.mat_obj.copyTo(draw_mat(src_rect_roi));
					}
					cv::rectangle(draw_mat, src_rect_roi, color, thickness);
					putText(draw_mat, track_id_str, src_rect_roi.tl() - cv::Point2i(0, 10), cv::FONT_HERSHEY_COMPLEX_SMALL, 0.8, cv::Scalar(0, 0, 0), 1);
				}
			}
		}
	}
};
#endif	// OPENCV

//extern "C" {
#endif	// __cplusplus

/*
	// C - wrappers
	YOLODLL_API void create_detector(char const* cfg_filename, char const* weight_filename, int gpu_id);
	YOLODLL_API void delete_detector();
	YOLODLL_API bbox_t* detect_custom(image_t img, float thresh, bool use_mean, int *result_size);
	YOLODLL_API bbox_t* detect_resized(image_t img, int init_w, int init_h, float thresh, bool use_mean, int *result_size);
	YOLODLL_API bbox_t* detect(image_t img, int *result_size);
	YOLODLL_API image_t load_img(char *image_filename);
	YOLODLL_API void free_img(image_t m);

#ifdef __cplusplus
}	// extern "C"

static std::shared_ptr<void> c_detector_ptr;
static std::vector<bbox_t> c_result_vec;

void create_detector(char const* cfg_filename, char const* weight_filename, int gpu_id) {
	c_detector_ptr = std::make_shared<YOLODLL_API Detector>(cfg_filename, weight_filename, gpu_id);
}

void delete_detector() { c_detector_ptr.reset(); }

bbox_t* detect_custom(image_t img, float thresh, bool use_mean, int *result_size) {
	c_result_vec = static_cast<Detector*>(c_detector_ptr.get())->detect(img, thresh, use_mean);
	*result_size = c_result_vec.size();
	return c_result_vec.data();
}

bbox_t* detect_resized(image_t img, int init_w, int init_h, float thresh, bool use_mean, int *result_size) {
	c_result_vec = static_cast<Detector*>(c_detector_ptr.get())->detect_resized(img, init_w, init_h, thresh, use_mean);
	*result_size = c_result_vec.size();
	return c_result_vec.data();
}

bbox_t* detect(image_t img, int *result_size) {
	return detect_custom(img, 0.24, true, result_size);
}

image_t load_img(char *image_filename) {
	return static_cast<Detector*>(c_detector_ptr.get())->load_image(image_filename);
}
void free_img(image_t m) {
	static_cast<Detector*>(c_detector_ptr.get())->free_image(m);
}

#endif	// __cplusplus
*/