Added -chart argument

include/darknet.h

@@ -914,7 +914,7 @@ LIB_API void reset_rnn(network *net);
 LIB_API float *network_predict_image(network *net, image im);
 LIB_API float *network_predict_image_letterbox(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, int letter_box, 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, int show_imgs, int benchmark_layers);
+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, int benchmark_layers, char* chart_path);
 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, int letter_box, int benchmark_layers);
 LIB_API int network_width(network *net);

src/classifier.c

@@ -27,7 +27,7 @@ float *get_regression_values(char **labels, int n)
     return v;
 }
 
-void train_classifier(char *datacfg, char *cfgfile, char *weightfile, int *gpus, int ngpus, int clear, int dontuse_opencv, int dont_show, int mjpeg_port, int calc_topk, int show_imgs)
+void train_classifier(char *datacfg, char *cfgfile, char *weightfile, int *gpus, int ngpus, int clear, int dontuse_opencv, int dont_show, int mjpeg_port, int calc_topk, int show_imgs, char* chart_path)
 {
     int i;
 
@@ -113,7 +113,7 @@ void train_classifier(char *datacfg, char *cfgfile, char *weightfile, int *gpus,
     int img_size = 1000;
     char windows_name[100];
     sprintf(windows_name, "average loss (id:%d)", random_gen());
-    if (!dontuse_opencv) img = draw_train_chart(windows_name, max_img_loss, net.max_batches, number_of_lines, img_size, dont_show);
+    if (!dontuse_opencv) img = draw_train_chart(windows_name, max_img_loss, net.max_batches, number_of_lines, img_size, dont_show, chart_path);
 #endif  //OPENCV
 
     data train;
@@ -1349,9 +1349,10 @@ void run_classifier(int argc, char **argv)
     char *filename = (argc > 6) ? argv[6]: 0;
     char *layer_s = (argc > 7) ? argv[7]: 0;
     int layer = layer_s ? atoi(layer_s) : -1;
+    char* chart_path = find_char_arg(argc, argv, "-chart", 0);
     if(0==strcmp(argv[2], "predict")) predict_classifier(data, cfg, weights, filename, top);
     else if(0==strcmp(argv[2], "try")) try_classifier(data, cfg, weights, filename, atoi(layer_s));
-    else if(0==strcmp(argv[2], "train")) train_classifier(data, cfg, weights, gpus, ngpus, clear, dontuse_opencv, dont_show, mjpeg_port, calc_topk, show_imgs);
+    else if(0==strcmp(argv[2], "train")) train_classifier(data, cfg, weights, gpus, ngpus, clear, dontuse_opencv, dont_show, mjpeg_port, calc_topk, show_imgs, chart_path);
     else if(0==strcmp(argv[2], "demo")) demo_classifier(data, cfg, weights, cam_index, filename, benchmark, benchmark_layers);
     else if(0==strcmp(argv[2], "gun")) gun_classifier(data, cfg, weights, cam_index, filename);
     else if(0==strcmp(argv[2], "threat")) threat_classifier(data, cfg, weights, cam_index, filename);

src/detector.c

@@ -22,7 +22,7 @@ int check_mistakes = 0;
 
 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, int show_imgs, int benchmark_layers)
+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, int benchmark_layers, char* chart_path)
 {
     list *options = read_data_cfg(datacfg);
     char *train_images = option_find_str(options, "train", "data/train.txt");
@@ -150,7 +150,7 @@ void train_detector(char *datacfg, char *cfgfile, char *weightfile, int *gpus, i
     int img_size = 1000;
     char windows_name[100];
     sprintf(windows_name, "chart_%s.png", base);
-    img = draw_train_chart(windows_name, max_img_loss, net.max_batches, number_of_lines, img_size, dont_show);
+    img = draw_train_chart(windows_name, max_img_loss, net.max_batches, number_of_lines, img_size, dont_show, chart_path);
 #endif    //OPENCV
     if (net.track) {
         args.track = net.track;
@@ -1635,6 +1635,7 @@ void run_detector(int argc, char **argv)
     // and for recall mode (extended output table-like format with results for best_class fit)
     int ext_output = find_arg(argc, argv, "-ext_output");
     int save_labels = find_arg(argc, argv, "-save_labels");
+    char* chart_path = find_char_arg(argc, argv, "-chart", 0);
     if (argc < 4) {
         fprintf(stderr, "usage: %s %s [train/test/valid/demo/map] [data] [cfg] [weights (optional)]\n", argv[0], argv[1]);
         return;
@@ -1673,7 +1674,7 @@ 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, letter_box, benchmark_layers);
-    else if (0 == strcmp(argv[2], "train")) train_detector(datacfg, cfg, weights, gpus, ngpus, clear, dont_show, calc_map, mjpeg_port, show_imgs, benchmark_layers);
+    else if (0 == strcmp(argv[2], "train")) train_detector(datacfg, cfg, weights, gpus, ngpus, clear, dont_show, calc_map, mjpeg_port, show_imgs, benchmark_layers, chart_path);
     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, letter_box, NULL);

src/image_opencv.cpp

@@ -1003,8 +1003,13 @@ extern "C" void draw_detections_cv_v3(mat_cv* mat, detection *dets, int num, flo
 // ====================================================================
 // Draw Loss & Accuracy chart
 // ====================================================================
-extern "C" mat_cv* draw_train_chart(char *windows_name, float max_img_loss, int max_batches, int number_of_lines, int img_size, int dont_show)
+extern "C" mat_cv* draw_train_chart(char *windows_name, float max_img_loss, int max_batches, int number_of_lines, int img_size, int dont_show, char* chart_path)
 {
+    if (chart_path != NULL && chart_path[0] != '\0'){
+        cv::Mat* img_ptr = new cv::Mat(cv::imread(chart_path));
+        return (mat_cv*)img_ptr;
+    }
+
     int img_offset = 60;
     int draw_size = img_size - img_offset;
     cv::Mat *img_ptr = new cv::Mat(img_size, img_size, CV_8UC3, CV_RGB(255, 255, 255));
@@ -1085,10 +1090,12 @@ extern "C" void draw_train_loss(char *windows_name, mat_cv* img_src, int img_siz
             if (iteration_old == 0)
                 cv::putText(img, accuracy_name, cv::Point(10, 12), cv::FONT_HERSHEY_COMPLEX_SMALL, 0.7, CV_RGB(255, 0, 0), 1, CV_AA);
 
-            cv::line(img,
-                cv::Point(img_offset + draw_size * (float)iteration_old / max_batches, draw_size * (1 - old_precision)),
-                cv::Point(img_offset + draw_size * (float)current_batch / max_batches, draw_size * (1 - precision)),
-                CV_RGB(255, 0, 0), 1, 8, 0);
+	    if (iteration_old != 0){
+            	cv::line(img,
+                    cv::Point(img_offset + draw_size * (float)iteration_old / max_batches, draw_size * (1 - old_precision)),
+                    cv::Point(img_offset + draw_size * (float)current_batch / max_batches, draw_size * (1 - precision)),
+                    CV_RGB(255, 0, 0), 1, 8, 0);
+	    }
 
             sprintf(char_buff, "%2.1f%% ", precision * 100);
             cv::putText(img, char_buff, cv::Point(10, 28), cv::FONT_HERSHEY_COMPLEX_SMALL, 0.7, CV_RGB(255, 255, 255), 5, CV_AA);

src/image_opencv.h

@@ -92,7 +92,7 @@ void save_cv_jpg(mat_cv *img, const char *name);
 void draw_detections_cv_v3(mat_cv* show_img, detection *dets, int num, float thresh, char **names, image **alphabet, int classes, int ext_output);
 
 // Draw Loss & Accuracy chart
-mat_cv* draw_train_chart(char *windows_name, float max_img_loss, int max_batches, int number_of_lines, int img_size, int dont_show);
+mat_cv* draw_train_chart(char *windows_name, float max_img_loss, int max_batches, int number_of_lines, int img_size, int dont_show, char* chart_path);
 void draw_train_loss(char *windows_name, mat_cv* img, int img_size, float avg_loss, float max_img_loss, int current_batch, int max_batches,
     float precision, int draw_precision, char *accuracy_name, int dont_show, int mjpeg_port);
 
@@ -126,4 +126,4 @@ void destroy_all_windows_cv();
 }
 #endif
 
-#endif // IMAGE_OPENCV_H
+#endif // IMAGE_OPENCV_H