yolov3的缺点_YOLOv3：训练自己的数据（附优化与问题总结）

如何批量检测？

可以看我github的修改，也可以按照下面的修改。修改传送门

首先在添加一个获取图片名字的函数：

#include "darknet.h"

#include

static int coco_ids[]={1,2,3,4,5,6,7,8,9,10,11,13,14,15,16,17,18,19,20,21,22,23,24,25,27,28,31,32,33,34,35,36,37,38,39,40,41,42,43,44,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,67,70,72,73,74,75,76,77,78,79,80,81,82,84,85,86,87,88,89,90};

char *GetFilename(char *p)

{

static char name[20]={""};

char *q = strrchr(p,'/') + 1;

strncpy(name,q,10);//后面的10是你自己图片名的长度，可修改

return name;

}

替换examples/detector.c 中的test_detector函数

void test_detector(char *datacfg, char *cfgfile, char *weightfile, char *filename, float thresh, float hier_thresh, char *outfile, int fullscreen)

{

list *options = read_data_cfg(datacfg);

char *name_list = option_find_str(options, "names", "data/names.list");

char **names = get_labels(name_list);

image **alphabet = load_alphabet();

network *net = load_network(cfgfile, weightfile, 0);

set_batch_network(net, 1);

srand(2222222);

double time;

char buff[256];

char *input = buff;

float nms=.45;

int i=0;

while(1){

if(filename){

strncpy(input, filename, 256);

image im = load_image_color(input,0,0);

image sized = letterbox_image(im, net->w, net->h);

layer l = net->layers[net->n-1];

float *X = sized.data;

time=what_time_is_it_now();

network_predict(net, X);

printf("%s: Predicted in %f seconds.\n", input, what_time_is_it_now()-time);

int nboxes = 0;

detection *dets = get_network_boxes(net, im.w, im.h, thresh, hier_thresh, 0, 1, &nboxes);

if (nms) do_nms_sort(dets, nboxes, l.classes, nms);

draw_detections(im, dets, nboxes, thresh, names, alphabet, l.classes);

free_detections(dets, nboxes);

if(outfile)

{

save_image(im, outfile);

}

else{

save_image(im, "predictions");

#ifdef OPENCV

cvNamedWindow("predictions", CV_WINDOW_NORMAL);

if(fullscreen){

cvSetWindowProperty("predictions", CV_WND_PROP_FULLSCREEN, CV_WINDOW_FULLSCREEN);

}

show_image(im, "predictions",0);

cvWaitKey(0);

cvDestroyAllWindows();

#endif

}

free_image(im);

free_image(sized);

if (filename) break;

}

else {

printf("Enter Image Path: ");

fflush(stdout);

input = fgets(input, 256, stdin);

if(!input) return;

strtok(input, "\n");

list *plist = get_paths(input);

char **paths = (char **)list_to_array(plist);

printf("Start Testing!\n");

int m = plist->size;

if(access("/home/lzm/data/test_folder/darknet/car_person/out",0)==-1)//"/homelzm/......"修改成自己要保存图片的的路径

{

if (mkdir("/home/lzm/data/test_folder/darknet/car_person/out",0777))//"/homelzm/......"修改成自己要保存图片的的路径

{

printf("creat folder failed!!!");

}

for(i = 0; i < m; ++i){

char *path = paths[i];

image im = load_image_color(path,0,0);

image sized = letterbox_image(im, net->w, net->h);

//image sized = resize_image(im, net->w, net->h);

//image sized2 = resize_max(im, net->w);

//image sized = crop_image(sized2, -((net->w - sized2.w)/2), -((net->h - sized2.h)/2), net->w, net->h);

//resize_network(net, sized.w, sized.h);

layer l = net->layers[net->n-1];

float *X = sized.data;

time=what_time_is_it_now();

network_predict(net, X);

printf("Try Very Hard:");

printf("%s: Predicted in %f seconds.\n", path, what_time_is_it_now()-time);

int nboxes = 0;

detection *dets = get_network_boxes(net, im.w, im.h, thresh, hier_thresh, 0, 1, &nboxes);

//printf("%d\n", nboxes);

//if (nms) do_nms_obj(boxes, probs, l.w*l.h*l.n, l.classes, nms);

if (nms) do_nms_sort(dets, nboxes, l.classes, nms);

draw_detections(im, dets, nboxes, thresh, names, alphabet, l.classes);

free_detections(dets, nboxes);

if(outfile){

save_image(im, outfile);

}

else{

char b[2048];

sprintf(b,"/home/lzm/data/test_folder/darknet/car_person/out/%s",GetFilename(path));//"/homelzm/......"修改成自己要保存图片的的路径

save_image(im, b);

printf("OJBK!\n",GetFilename(path));