From e947bf29af0540eda50fd298bb5492c2d8fa7680 Mon Sep 17 00:00:00 2001
From: AlexeyAB <alexeyab84@gmail.com>
Date: Fri, 16 Mar 2018 22:03:56 +0000
Subject: [PATCH] C wrappers
---
src/yolo_v2_class.cpp | 28 ++++++---
src/yolo_console_dll.cpp | 3
src/yolo_v2_class.hpp | 95 ++++++++++++++++++++++++-------
3 files changed, 93 insertions(+), 33 deletions(-)
diff --git a/src/yolo_console_dll.cpp b/src/yolo_console_dll.cpp
index 4a8310a..cb0b063 100644
--- a/src/yolo_console_dll.cpp
+++ b/src/yolo_console_dll.cpp
@@ -361,7 +361,8 @@
auto current_image = det_image;
consumed = true;
while (current_image.use_count() > 0) {
- auto result = detector.detect_resized(*current_image, frame_size, thresh, false); // true
+ auto result = detector.detect_resized(*current_image, frame_size.width, frame_size.height,
+ thresh, false); // true
++fps_det_counter;
std::unique_lock<std::mutex> lock(mtx);
thread_result_vec = result;
diff --git a/src/yolo_v2_class.cpp b/src/yolo_v2_class.cpp
index 8ef5e93..c805e29 100644
--- a/src/yolo_v2_class.cpp
+++ b/src/yolo_v2_class.cpp
@@ -22,7 +22,14 @@
#define FRAMES 3
-struct detector_gpu_t{
+void check_cuda(cudaError_t status) {
+ if (status != cudaSuccess) {
+ const char *s = cudaGetErrorString(status);
+ printf("CUDA Error Prev: %s\n", s);
+ }
+}
+
+struct detector_gpu_t {
float **probs;
box *boxes;
network net;
@@ -38,14 +45,15 @@
wait_stream = 0;
int old_gpu_index;
#ifdef GPU
- cudaGetDevice(&old_gpu_index);
+ check_cuda( 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());
+ detector_gpu_t &detector_gpu = *static_cast<detector_gpu_t *>(detector_gpu_ptr.get());
#ifdef GPU
- cudaSetDevice(gpu_id);
+ check_cuda( cudaSetDevice(gpu_id) );
+ printf(" Used GPU %d \n", gpu_id);
#endif
network &net = detector_gpu.net;
net.gpu_index = gpu_id;
@@ -76,14 +84,14 @@
for (j = 0; j < l.classes; ++j) detector_gpu.track_id[j] = 1;
#ifdef GPU
- cudaSetDevice(old_gpu_index);
+ check_cuda( cudaSetDevice(old_gpu_index) );
#endif
}
YOLODLL_API Detector::~Detector()
{
- detector_gpu_t &detector_gpu = *reinterpret_cast<detector_gpu_t *>(detector_gpu_ptr.get());
+ 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];
free(detector_gpu.track_id);
@@ -110,11 +118,11 @@
}
YOLODLL_API int Detector::get_net_width() const {
- detector_gpu_t &detector_gpu = *reinterpret_cast<detector_gpu_t *>(detector_gpu_ptr.get());
+ detector_gpu_t &detector_gpu = *static_cast<detector_gpu_t *>(detector_gpu_ptr.get());
return detector_gpu.net.w;
}
YOLODLL_API int Detector::get_net_height() const {
- detector_gpu_t &detector_gpu = *reinterpret_cast<detector_gpu_t *>(detector_gpu_ptr.get());
+ detector_gpu_t &detector_gpu = *static_cast<detector_gpu_t *>(detector_gpu_ptr.get());
return detector_gpu.net.h;
}
@@ -172,7 +180,7 @@
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());
+ detector_gpu_t &detector_gpu = *static_cast<detector_gpu_t *>(detector_gpu_ptr.get());
network &net = detector_gpu.net;
int old_gpu_index;
#ifdef GPU
@@ -254,7 +262,7 @@
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 = *reinterpret_cast<detector_gpu_t *>(detector_gpu_ptr.get());
+ detector_gpu_t &det_gpu = *static_cast<detector_gpu_t *>(detector_gpu_ptr.get());
bool prev_track_id_present = false;
for (auto &i : prev_bbox_vec_deque)
diff --git a/src/yolo_v2_class.hpp b/src/yolo_v2_class.hpp
index b1b5bf7..68482e6 100644
--- a/src/yolo_v2_class.hpp
+++ b/src/yolo_v2_class.hpp
@@ -1,15 +1,4 @@
#pragma once
-#include <memory>
-#include <vector>
-#include <deque>
-#include <algorithm>
-
-#ifdef OPENCV
-#include <opencv2/opencv.hpp> // C++
-#include "opencv2/highgui/highgui_c.h" // C
-#include "opencv2/imgproc/imgproc_c.h" // C
-#endif // OPENCV
-
#ifdef YOLODLL_EXPORTS
#if defined(_MSC_VER)
#define YOLODLL_API __declspec(dllexport)
@@ -39,6 +28,17 @@
float *data; // pointer to the image data
};
+#ifdef __cplusplus
+#include <memory>
+#include <vector>
+#include <deque>
+#include <algorithm>
+
+#ifdef OPENCV
+#include <opencv2/opencv.hpp> // C++
+#include "opencv2/highgui/highgui_c.h" // C
+#include "opencv2/imgproc/imgproc_c.h" // C
+#endif // OPENCV
class Detector {
std::shared_ptr<void> detector_gpu_ptr;
@@ -61,23 +61,23 @@
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;
+ }
+
#ifdef OPENCV
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.size(), thresh, use_mean);
- }
-
- std::vector<bbox_t> detect_resized(image_t img, cv::Size init_size, 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_size.width / img.w, hk = (float)init_size.height / img.h;
- for (auto &i : detection_boxes) i.x *= wk, i.w *= wk, i.y *= hk, i.h *= hk;
- return detection_boxes;
+ 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
@@ -588,3 +588,54 @@
}
};
#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
+*/
--
Gitblit v1.10.0