this'll teach me to mess with maxpooling

Makefile

@@ -57,8 +57,8 @@ CFLAGS+= -DCUDNN
 LDFLAGS+= -lcudnn
 endif
 
-OBJ=gemm.o utils.o cuda.o deconvolutional_layer.o convolutional_layer.o list.o image.o activations.o im2col.o col2im.o blas.o crop_layer.o dropout_layer.o maxpool_layer.o softmax_layer.o data.o matrix.o network.o connected_layer.o cost_layer.o parser.o option_list.o detection_layer.o route_layer.o upsample_layer.o box.o normalization_layer.o avgpool_layer.o layer.o local_layer.o shortcut_layer.o logistic_layer.o activation_layer.o rnn_layer.o gru_layer.o crnn_layer.o demo.o batchnorm_layer.o region_layer.o reorg_layer.o tree.o  lstm_layer.o l2norm_layer.o yolo_layer.o
-EXECOBJA=captcha.o lsd.o super.o art.o tag.o cifar.o go.o rnn.o segmenter.o regressor.o classifier.o coco.o yolo.o detector.o nightmare.o darknet.o
+OBJ=gemm.o utils.o cuda.o deconvolutional_layer.o convolutional_layer.o list.o image.o activations.o im2col.o col2im.o blas.o crop_layer.o dropout_layer.o maxpool_layer.o softmax_layer.o data.o matrix.o network.o connected_layer.o cost_layer.o parser.o option_list.o detection_layer.o route_layer.o upsample_layer.o box.o normalization_layer.o avgpool_layer.o layer.o local_layer.o shortcut_layer.o logistic_layer.o activation_layer.o rnn_layer.o gru_layer.o crnn_layer.o demo.o batchnorm_layer.o region_layer.o reorg_layer.o tree.o  lstm_layer.o l2norm_layer.o yolo_layer.o iseg_layer.o
+EXECOBJA=captcha.o lsd.o super.o art.o tag.o cifar.o go.o rnn.o segmenter.o regressor.o classifier.o coco.o yolo.o detector.o nightmare.o instance-segmenter.o darknet.o
 ifeq ($(GPU), 1) 
 LDFLAGS+= -lstdc++ 
 OBJ+=convolutional_kernels.o deconvolutional_kernels.o activation_kernels.o im2col_kernels.o col2im_kernels.o blas_kernels.o crop_layer_kernels.o dropout_layer_kernels.o maxpool_layer_kernels.o avgpool_layer_kernels.o

examples/art.c

@@ -24,7 +24,6 @@ void demo_art(char *cfgfile, char *weightfile, int cam_index)
     while(1){
         image in = get_image_from_stream(cap);
         image in_s = resize_image(in, net->w, net->h);
-        show_image(in, window);
 
         float *p = network_predict(net, in_s.data);
 
@@ -45,10 +44,9 @@ void demo_art(char *cfgfile, char *weightfile, int cam_index)
         }
         printf("]\n");
 
+        show_image(in, window, 1);
         free_image(in_s);
         free_image(in);
-
-        cvWaitKey(1);
     }
 #endif
 }

examples/classifier.c

@@ -645,6 +645,45 @@ void label_classifier(char *datacfg, char *filename, char *weightfile)
     }
 }
 
+void csv_classifier(char *datacfg, char *cfgfile, char *weightfile)
+{
+    int i,j;
+    network *net = load_network(cfgfile, weightfile, 0);
+    srand(time(0));
+
+    list *options = read_data_cfg(datacfg);
+
+    char *test_list = option_find_str(options, "test", "data/test.list");
+    int top = option_find_int(options, "top", 1);
+
+    list *plist = get_paths(test_list);
+
+    char **paths = (char **)list_to_array(plist);
+    int m = plist->size;
+    free_list(plist);
+    int *indexes = calloc(top, sizeof(int));
+
+    for(i = 0; i < m; ++i){
+        double time = what_time_is_it_now();
+        char *path = paths[i];
+        image im = load_image_color(path, 0, 0);
+        image r = letterbox_image(im, net->w, net->h);
+        float *predictions = network_predict(net, r.data);
+        if(net->hierarchy) hierarchy_predictions(predictions, net->outputs, net->hierarchy, 1, 1);
+        top_k(predictions, net->outputs, top, indexes);
+
+        printf("%s", path);
+        for(j = 0; j < top; ++j){
+            printf("\t%d", indexes[j]);
+        }
+        printf("\n");
+
+        free_image(im);
+        free_image(r);
+
+        fprintf(stderr, "%lf seconds, %d images, %d total\n", what_time_is_it_now() - time, i+1, m);
+    }
+}
 
 void test_classifier(char *datacfg, char *cfgfile, char *weightfile, int target_layer)
 {
@@ -869,8 +908,7 @@ void threat_classifier(char *datacfg, char *cfgfile, char *weightfile, int cam_i
         }
 
         if(1){
-            show_image(out, "Threat");
-            cvWaitKey(10);
+            show_image(out, "Threat", 10);
         }
         free_image(in_s);
         free_image(in);
@@ -922,7 +960,6 @@ void gun_classifier(char *datacfg, char *cfgfile, char *weightfile, int cam_inde
 
         image in = get_image_from_stream(cap);
         image in_s = resize_image(in, net->w, net->h);
-        show_image(in, "Threat Detection");
 
         float *predictions = network_predict(net, in_s.data);
         top_predictions(net, top, indexes);
@@ -947,11 +984,10 @@ void gun_classifier(char *datacfg, char *cfgfile, char *weightfile, int cam_inde
             }
         }
 
+        show_image(in, "Threat Detection", 10);
         free_image(in_s);
         free_image(in);
 
-        cvWaitKey(10);
-
         gettimeofday(&tval_after, NULL);
         timersub(&tval_after, &tval_before, &tval_result);
         float curr = 1000000.f/((long int)tval_result.tv_usec);
@@ -1036,12 +1072,10 @@ void demo_classifier(char *datacfg, char *cfgfile, char *weightfile, int cam_ind
             free_image(label);
         }
 
-        show_image(in, base);
+        show_image(in, base, 10);
         free_image(in_s);
         free_image(in);
 
-        cvWaitKey(10);
-
         gettimeofday(&tval_after, NULL);
         timersub(&tval_after, &tval_before, &tval_result);
         float curr = 1000000.f/((long int)tval_result.tv_usec);
@@ -1080,6 +1114,7 @@ void run_classifier(int argc, char **argv)
     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);
     else if(0==strcmp(argv[2], "test")) test_classifier(data, cfg, weights, layer);
+    else if(0==strcmp(argv[2], "csv")) csv_classifier(data, cfg, weights);
     else if(0==strcmp(argv[2], "label")) label_classifier(data, cfg, weights);
     else if(0==strcmp(argv[2], "valid")) validate_classifier_single(data, cfg, weights);
     else if(0==strcmp(argv[2], "validmulti")) validate_classifier_multi(data, cfg, weights);

examples/coco.c

@@ -325,14 +325,10 @@ void test_coco(char *cfgfile, char *weightfile, char *filename, float thresh)
 
         draw_detections(im, dets, l.side*l.side*l.n, thresh, coco_classes, alphabet, 80);
         save_image(im, "prediction");
-        show_image(im, "predictions");
+        show_image(im, "predictions", 0);
         free_detections(dets, nboxes);
         free_image(im);
         free_image(sized);
-#ifdef OPENCV
-        cvWaitKey(0);
-        cvDestroyAllWindows();
-#endif
         if (filename) break;
     }
 }

examples/darknet.c

@@ -14,6 +14,7 @@ extern void run_nightmare(int argc, char **argv);
 extern void run_classifier(int argc, char **argv);
 extern void run_regressor(int argc, char **argv);
 extern void run_segmenter(int argc, char **argv);
+extern void run_isegmenter(int argc, char **argv);
 extern void run_char_rnn(int argc, char **argv);
 extern void run_tag(int argc, char **argv);
 extern void run_cifar(int argc, char **argv);
@@ -452,6 +453,8 @@ int main(int argc, char **argv)
         run_classifier(argc, argv);
     } else if (0 == strcmp(argv[1], "regressor")){
         run_regressor(argc, argv);
+    } else if (0 == strcmp(argv[1], "isegmenter")){
+        run_isegmenter(argc, argv);
     } else if (0 == strcmp(argv[1], "segmenter")){
         run_segmenter(argc, argv);
     } else if (0 == strcmp(argv[1], "art")){

examples/detector.c

@@ -613,9 +613,7 @@ void test_detector(char *datacfg, char *cfgfile, char *weightfile, char *filenam
             if(fullscreen){
                 cvSetWindowProperty("predictions", CV_WND_PROP_FULLSCREEN, CV_WINDOW_FULLSCREEN);
             }
-            show_image(im, "predictions");
-            cvWaitKey(0);
-            cvDestroyAllWindows();
+            show_image(im, "predictions", 0);
 #endif
         }