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Fixed memory leak in DLL, added load_image() & free_image(), added read_names_from_file()

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This commit is contained in:
AlexeyAB
2017-03-16 21:49:36 +03:00
parent ed56fbbc90
commit 351996d9f0
4 changed files with 99 additions and 45 deletions
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4
src/layer.c
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@ -28,8 +28,8 @@ void free_layer(layer l)
#ifdef GPU
if(l.indexes_gpu) cuda_free((float *)l.indexes_gpu);
if(l.weights_gpu) cuda_free(l.weights_gpu);
if(l.weight_updates_gpu) cuda_free(l.weight_updates_gpu);
//if(l.weights_gpu) cuda_free(l.weights_gpu); // duplicated
//if(l.weight_updates_gpu) cuda_free(l.weight_updates_gpu); // duplicated
if(l.col_image_gpu) cuda_free(l.col_image_gpu);
if(l.weights_gpu) cuda_free(l.weights_gpu);
if(l.biases_gpu) cuda_free(l.biases_gpu);

33
src/yolo_console_dll.cpp
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@ -1,6 +1,7 @@
#include <iostream>
#include <string>
#include <vector>
#include <fstream>
//#define OPENCV
@ -21,21 +22,31 @@ void draw_boxes(cv::Mat mat_img, std::vector<bbox_t> result_vec) {
}
#endif // OPENCV
void show_result(std::vector<bbox_t> result_vec) {
void show_result(std::vector<bbox_t> const result_vec, std::vector<std::string> const obj_names) {
for (auto &i : result_vec) {
if (obj_names.size() > i.obj_id) std::cout << obj_names[i.obj_id] << " - ";
std::cout << "obj_id = " << i.obj_id << " - x = " << i.x << ", y = " << i.y
<< ", w = " << i.w << ", h = " << i.h
<< ", prob = " << i.prob << std::endl;
}
}
std::vector<std::string> objects_names_from_file(std::string const filename) {
std::ifstream file(filename);
std::vector<std::string> file_lines;
if (!file.is_open()) return file_lines;
for(std::string line; file >> line;) file_lines.push_back(line);
std::cout << "object names loaded \n";
return file_lines;
}
int main()
{
Detector detector("yolo-voc.cfg", "yolo-voc.weights");
auto obj_names = objects_names_from_file("data/voc.names");
while (true)
{
std::string filename;
@ -43,14 +54,22 @@ int main()
std::cin >> filename;
if (filename.size() == 0) break;
try {
#ifdef OPENCV
cv::Mat mat_img = cv::imread(filename);
std::vector<bbox_t> result_vec = detector.detect(mat_img);
draw_boxes(mat_img, result_vec);
cv::Mat mat_img = cv::imread(filename);
std::vector<bbox_t> result_vec = detector.detect(mat_img);
draw_boxes(mat_img, result_vec);
#else
std::vector<bbox_t> result_vec = detector.detect(filename);
//std::vector<bbox_t> result_vec = detector.detect(filename);
auto img = detector.load_image(filename);
std::vector<bbox_t> result_vec = detector.detect(img);
detector.free_image(img);
#endif
show_result(result_vec);
show_result(result_vec, obj_names);
}
catch (std::exception &e) { std::cerr << "exception: " << e.what() << "\n"; getchar(); }
catch (...) { std::cerr << "unknown exception \n"; getchar(); }
}
return 0;

75
src/yolo_v2_class.cpp
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@ -1,6 +1,5 @@
#include "yolo_v2_class.hpp"
#include "network.h"
extern "C" {
@ -12,40 +11,32 @@ extern "C" {
#include "box.h"
#include "image.h"
#include "demo.h"
#include "option_list.h"
#include "stb_image.h"
}
//#include <sys/time.h>
#include <vector>
#include <iostream>
#define FRAMES 3
#define ROI_PER_DETECTOR 100
struct detector_gpu_t{
float **probs;
box *boxes;
network net;
//image det;
//image det_s;
image images[FRAMES];
float *avg;
float *predictions[FRAMES];
};
YOLODLL_API Detector::Detector(std::string cfg_filename, std::string weight_filename, int gpu_id)
{
int old_gpu_index;
cudaGetDevice(&old_gpu_index);
detector_gpu_ptr = std::make_shared<detector_gpu_t>();
detector_gpu_t &detector_gpu = *reinterpret_cast<detector_gpu_t *>(detector_gpu_ptr.get());
cudaSetDevice(gpu_id);
@ -77,23 +68,63 @@ YOLODLL_API Detector::Detector(std::string cfg_filename, std::string weight_file
cudaSetDevice(old_gpu_index);
}
YOLODLL_API Detector::~Detector()
{
detector_gpu_t &detector_gpu = *reinterpret_cast<detector_gpu_t *>(detector_gpu_ptr.get());
layer l = detector_gpu.net.layers[detector_gpu.net.n - 1];
free(detector_gpu.boxes);
free(detector_gpu.avg);
free(detector_gpu.predictions);
for (int j = 0; j < l.w*l.h*l.n; ++j) free(detector_gpu.probs[j]);
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);
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;
cudaGetDevice(&old_gpu_index);
cudaSetDevice(detector_gpu.net.gpu_index);
free_network(detector_gpu.net);
cudaSetDevice(old_gpu_index);
}
YOLODLL_API std::vector<bbox_t> Detector::detect(std::string image_filename, float thresh)
{
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);
}
static image load_image_stb(char *filename, int channels)
{
int w, h, c;
unsigned char *data = stbi_load(filename, &w, &h, &c, channels);
if (!data)
throw std::runtime_error("file not found");
if (channels) c = channels;
int i, j, k;
image im = make_image(w, h, c);
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;
im.data[dst_index] = (float)data[src_index] / 255.;
}
}
}
free(data);
return im;
}
YOLODLL_API image_t Detector::load_image(std::string image_filename)
{
char *input = const_cast<char *>(image_filename.data());
image im = load_image_color(input, 0, 0);
image im = load_image_stb(input, 3);
image_t img;
img.c = im.c;
@ -101,10 +132,17 @@ YOLODLL_API std::vector<bbox_t> Detector::detect(std::string image_filename, flo
img.h = im.h;
img.w = im.w;
return detect(img, thresh);
return img;
}
YOLODLL_API void Detector::free_image(image_t m)
{
if (m.data) {
free(m.data);
}
}
YOLODLL_API std::vector<bbox_t> Detector::detect(image_t img, float thresh)
{
@ -126,10 +164,6 @@ YOLODLL_API std::vector<bbox_t> Detector::detect(image_t img, float thresh)
image sized = resize_image(im, net.w, net.h);
layer l = net.layers[net.n - 1];
//box *boxes = (box *)calloc(l.w*l.h*l.n, sizeof(box));
//float **probs = (float **)calloc(l.w*l.h*l.n, sizeof(float *));
// (int j = 0; j < l.w*l.h*l.n; ++j) probs[j] = (float *)calloc(l.classes, sizeof(float *));
float *X = sized.data;
network_predict(net, X);
@ -159,6 +193,9 @@ YOLODLL_API std::vector<bbox_t> Detector::detect(image_t img, float thresh)
}
}
if(sized.data)
free(sized.data);
cudaSetDevice(old_gpu_index);
return bbox_vec;

30
src/yolo_v2_class.hpp
View File

@ -15,17 +15,17 @@
#endif
struct bbox_t {
unsigned int x, y, w, h;
float prob;
unsigned int obj_id;
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]
};
typedef struct {
int h;
int w;
int c;
float *data;
} image_t;
struct image_t {
int h; // height
int w; // width
int c; // number of chanels (3 - for RGB)
float *data; // pointer to the image data
};
class Detector {
@ -37,11 +37,15 @@ public:
YOLODLL_API std::vector<bbox_t> detect(std::string image_filename, float thresh = 0.2);
YOLODLL_API std::vector<bbox_t> detect(image_t img, float thresh = 0.2);
static YOLODLL_API image_t load_image(std::string image_filename);
static YOLODLL_API void free_image(image_t m);
#ifdef OPENCV
std::vector<bbox_t> detect(cv::Mat mat, float thresh = 0.2)
{
std::shared_ptr<image_t> image_ptr(new image_t, [](image_t *img) { free_image(*img); } );
if(mat.data == NULL)
throw std::runtime_error("file not found");
std::shared_ptr<image_t> image_ptr(new image_t, [](image_t *img) { free_image(*img); delete img; });
*image_ptr = mat_to_image(mat);
return detect(*image_ptr, thresh);
}
@ -102,12 +106,6 @@ private:
}
}
static void free_image(image_t m)
{
if (m.data) {
free(m.data);
}
}
#endif // OPENCV
};