Added flag -show_imgs for Training, to show augmented images with bboxes

include/darknet.h

@@ -706,6 +706,7 @@ typedef struct load_args {
     int mini_batch;
     int track;
     int augment_speed;
+    int show_imgs;
     float jitter;
     int flip;
     float angle;
@@ -771,7 +772,7 @@ LIB_API detection *make_network_boxes(network *net, float thresh, int *num);
 LIB_API void reset_rnn(network *net);
 LIB_API float *network_predict_image(network *net, image im);
 LIB_API float validate_detector_map(char *datacfg, char *cfgfile, char *weightfile, float thresh_calc_avg_iou, const float iou_thresh, const int map_points, network *existing_net);
-LIB_API void train_detector(char *datacfg, char *cfgfile, char *weightfile, int *gpus, int ngpus, int clear, int dont_show, int calc_map, int mjpeg_port);
+LIB_API void train_detector(char *datacfg, char *cfgfile, char *weightfile, int *gpus, int ngpus, int clear, int dont_show, int calc_map, int mjpeg_port, int show_imgs);
 LIB_API void test_detector(char *datacfg, char *cfgfile, char *weightfile, char *filename, float thresh,
     float hier_thresh, int dont_show, int ext_output, int save_labels, char *outfile);
 LIB_API int network_width(network *net);

src/data.c

@@ -769,7 +769,8 @@ static box float_to_box_stride(float *f, int stride)
 
 #include "http_stream.h"
 
-data load_data_detection(int n, char **paths, int m, int w, int h, int c, int boxes, int classes, int use_flip, float jitter, float hue, float saturation, float exposure, int mini_batch, int track, int augment_speed)
+data load_data_detection(int n, char **paths, int m, int w, int h, int c, int boxes, int classes, int use_flip, float jitter,
+    float hue, float saturation, float exposure, int mini_batch, int track, int augment_speed, int show_imgs)
 {
     c = c ? c : 3;
     char **random_paths;
@@ -844,10 +845,9 @@ data load_data_detection(int n, char **paths, int m, int w, int h, int c, int bo
 
         fill_truth_detection(filename, boxes, d.y.vals[i], classes, flip, dx, dy, 1./sx, 1./sy, w, h);
 
-        const int show_augmented_images = 0;
+        if(show_imgs)
-        if(show_augmented_images)
         {
-            char buff[10];
+            char buff[1000];
             sprintf(buff, "aug_%s_%d", random_paths[i], random_gen());
             int t;
             for (t = 0; t < boxes; ++t) {
@@ -860,18 +860,20 @@ data load_data_detection(int n, char **paths, int m, int w, int h, int c, int bo
                 draw_box_width(ai, left, top, right, bot, 3, 150, 100, 50); // 3 channels RGB
             }
 
+            save_image(ai, buff);
             show_image(ai, buff);
             wait_until_press_key_cv();
+            printf("\nYou use flag -show_imgs, so will be saved aug_...jpg images. Click on window and press ESC button \n");
         }
 
-
         release_ipl(&src);
     }
     free(random_paths);
     return d;
 }
 #else    // OPENCV
-data load_data_detection(int n, char **paths, int m, int w, int h, int c, int boxes, int classes, int use_flip, float jitter, float hue, float saturation, float exposure, int mini_batch, int track, int augment_speed)
+data load_data_detection(int n, char **paths, int m, int w, int h, int c, int boxes, int classes, int use_flip, float jitter,
+    float hue, float saturation, float exposure, int mini_batch, int track, int augment_speed, int show_imgs)
 {
     c = c ? c : 3;
     char **random_paths;
@@ -938,10 +940,10 @@ data load_data_detection(int n, char **paths, int m, int w, int h, int c, int bo
 
         fill_truth_detection(random_paths[i], boxes, d.y.vals[i], classes, flip, dx, dy, 1. / sx, 1. / sy, w, h);
 
-        /*
+        if(show_imgs)
         {
-            char buff[10];
+            char buff[1000];
-            sprintf(buff, "aug_%s_%d", random_paths[i], random_gen());
+            sprintf(buff, "aug_%s_%d", basecfg(random_paths[i]), random_gen());
             int t;
             for (t = 0; t < boxes; ++t) {
                 box b = float_to_box_stride(d.y.vals[i] + t*(4 + 1), 1);
@@ -954,8 +956,11 @@ data load_data_detection(int n, char **paths, int m, int w, int h, int c, int bo
             }
 
             show_image(sized, buff);
+            save_image(sized, buff);
             wait_until_press_key_cv();
-        }*/
+            printf("\nYou use flag -show_imgs, so will be saved aug_...jpg images. Press Enter: \n");
+            getchar();
+        }
 
         free_image(orig);
         free_image(cropped);
@@ -985,7 +990,8 @@ void *load_thread(void *ptr)
     } else if (a.type == REGION_DATA){
         *a.d = load_data_region(a.n, a.paths, a.m, a.w, a.h, a.num_boxes, a.classes, a.jitter, a.hue, a.saturation, a.exposure);
     } else if (a.type == DETECTION_DATA){
-        *a.d = load_data_detection(a.n, a.paths, a.m, a.w, a.h, a.c, a.num_boxes, a.classes, a.flip, a.jitter, a.hue, a.saturation, a.exposure, a.mini_batch, a.track, a.augment_speed);
+        *a.d = load_data_detection(a.n, a.paths, a.m, a.w, a.h, a.c, a.num_boxes, a.classes, a.flip, a.jitter,
+            a.hue, a.saturation, a.exposure, a.mini_batch, a.track, a.augment_speed, a.show_imgs);
     } else if (a.type == SWAG_DATA){
         *a.d = load_data_swag(a.paths, a.n, a.classes, a.jitter);
     } else if (a.type == COMPARE_DATA){

src/data.h

@@ -86,7 +86,8 @@ void print_letters(float *pred, int n);
 data load_data_captcha(char **paths, int n, int m, int k, int w, int h);
 data load_data_captcha_encode(char **paths, int n, int m, int w, int h);
 data load_data_old(char **paths, int n, int m, char **labels, int k, int w, int h);
-data load_data_detection(int n, char **paths, int m, int w, int h, int c, int boxes, int classes, int use_flip, float jitter, float hue, float saturation, float exposure, int mini_batch, int track, int augment_speed);
+data load_data_detection(int n, char **paths, int m, int w, int h, int c, int boxes, int classes, int use_flip, float jitter,
+    float hue, float saturation, float exposure, int mini_batch, int track, int augment_speed, int show_imgs);
 data load_data_tag(char **paths, int n, int m, int k, int use_flip, int min, int max, int size, float angle, float aspect, float hue, float saturation, float exposure);
 matrix load_image_augment_paths(char **paths, int n, int use_flip, int min, int max, int size, float angle, float aspect, float hue, float saturation, float exposure);
 data load_data_super(char **paths, int n, int m, int w, int h, int scale);

src/detector.c

@@ -22,7 +22,7 @@ int check_mistakes;
 
 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 };
 
-void train_detector(char *datacfg, char *cfgfile, char *weightfile, int *gpus, int ngpus, int clear, int dont_show, int calc_map, int mjpeg_port)
+void train_detector(char *datacfg, char *cfgfile, char *weightfile, int *gpus, int ngpus, int clear, int dont_show, int calc_map, int mjpeg_port, int show_imgs)
 {
     list *options = read_data_cfg(datacfg);
     char *train_images = option_find_str(options, "train", "data/train.txt");
@@ -127,6 +127,7 @@ void train_detector(char *datacfg, char *cfgfile, char *weightfile, int *gpus, i
     args.exposure = net.exposure;
     args.saturation = net.saturation;
     args.hue = net.hue;
+    args.show_imgs = show_imgs;
 
 #ifdef OPENCV
     args.threads = 3 * ngpus;   // Amazon EC2 Tesla V100: p3.2xlarge (8 logical cores) - p3.16xlarge
@@ -1388,6 +1389,7 @@ void run_detector(int argc, char **argv)
     int calc_map = find_arg(argc, argv, "-map");
     int map_points = find_int_arg(argc, argv, "-points", 0);
     check_mistakes = find_arg(argc, argv, "-check_mistakes");
+    int show_imgs = find_arg(argc, argv, "-show_imgs");
     int mjpeg_port = find_int_arg(argc, argv, "-mjpeg_port", -1);
     int json_port = find_int_arg(argc, argv, "-json_port", -1);
     char *out_filename = find_char_arg(argc, argv, "-out_filename", 0);
@@ -1443,7 +1445,7 @@ void run_detector(int argc, char **argv)
             if (weights[strlen(weights) - 1] == 0x0d) weights[strlen(weights) - 1] = 0;
     char *filename = (argc > 6) ? argv[6] : 0;
     if (0 == strcmp(argv[2], "test")) test_detector(datacfg, cfg, weights, filename, thresh, hier_thresh, dont_show, ext_output, save_labels, outfile);
-    else if (0 == strcmp(argv[2], "train")) train_detector(datacfg, cfg, weights, gpus, ngpus, clear, dont_show, calc_map, mjpeg_port);
+    else if (0 == strcmp(argv[2], "train")) train_detector(datacfg, cfg, weights, gpus, ngpus, clear, dont_show, calc_map, mjpeg_port, show_imgs);
     else if (0 == strcmp(argv[2], "valid")) validate_detector(datacfg, cfg, weights, outfile);
     else if (0 == strcmp(argv[2], "recall")) validate_detector_recall(datacfg, cfg, weights);
     else if (0 == strcmp(argv[2], "map")) validate_detector_map(datacfg, cfg, weights, thresh, iou_thresh, map_points, NULL);