testing on one image

Makefile

@@ -1,5 +1,5 @@
-GPU=1
+GPU=0
-OPENCV=1
+OPENCV=0
 DEBUG=0
 
 ARCH= -arch=sm_52

src/convolutional_layer.c

@@ -232,7 +232,9 @@ void rgbgr_filters(convolutional_layer l)
     int i;
     for(i = 0; i < l.n; ++i){
         image im = get_convolutional_filter(l, i);
-        if (im.c == 3) rgbgr_image(im);
+        if (im.c == 3) {
+            rgbgr_image(im);
+        }
     }
 }
 

src/darknet.c

@@ -77,6 +77,7 @@ void partial(char *cfgfile, char *weightfile, char *outfile, int max)
 void rgbgr_filters(convolutional_layer l);
 void rgbgr_net(char *cfgfile, char *weightfile, char *outfile)
 {
+    gpu_index = -1;
     network net = parse_network_cfg(cfgfile);
     if(weightfile){
         load_weights(&net, weightfile);

src/detection.c

@@ -18,7 +18,7 @@ void draw_detection(image im, float *box, int side, char *label)
         for(c = 0; c < side; ++c){
             j = (r*side + c) * elems;
             int class = max_index(box+j, classes);
-            if(box[j+class] > 0){
+            if(box[j+class] > 0.2){
                 printf("%f %s\n", box[j+class], class_names[class]);
                 float red = get_color(0,class,classes);
                 float green = get_color(1,class,classes);
@@ -67,6 +67,7 @@ void train_detection(char *cfgfile, char *weightfile)
 
     int classes = layer.classes;
     int background = (layer.background || layer.objectness);
+    printf("%d\n", background);
     int side = sqrt(get_detection_layer_locations(layer));
 
     char **paths;
@@ -205,8 +206,9 @@ void validate_detection(char *cfgfile, char *weightfile)
     fprintf(stderr, "Total Detection Time: %f Seconds\n", (double)(time(0) - start));
 }
 
-void test_detection(char *cfgfile, char *weightfile)
+void test_detection(char *cfgfile, char *weightfile, char *filename)
 {
+
     network net = parse_network_cfg(cfgfile);
     if(weightfile){
         load_weights(&net, weightfile);
@@ -217,24 +219,30 @@ void test_detection(char *cfgfile, char *weightfile)
     set_batch_network(&net, 1);
     srand(2222222);
     clock_t time;
-    char filename[256];
+    char input[256];
     while(1){
-        printf("Image Path: ");
+        if(filename){
-        fflush(stdout);
+            strncpy(input, filename, 256);
-        fgets(filename, 256, stdin);
+        } else {
-        strtok(filename, "\n");
+            printf("Enter Image Path: ");
-        image im = load_image_color(filename,0,0);
+            fflush(stdout);
+            fgets(input, 256, stdin);
+            strtok(input, "\n");
+        }
+        image im = load_image_color(input,0,0);
         image sized = resize_image(im, im_size, im_size);
         float *X = sized.data;
         time=clock();
         float *predictions = network_predict(net, X);
-        printf("%s: Predicted in %f seconds.\n", filename, sec(clock()-time));
+        printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time));
         draw_detection(im, predictions, 7, "predictions");
         free_image(im);
         free_image(sized);
-        #ifdef OPENCV
+#ifdef OPENCV
         cvWaitKey(0);
-        #endif
+        cvDestroyAllWindows();
+#endif
+        if (filename) break;
     }
 }
 
@@ -247,7 +255,8 @@ void run_detection(int argc, char **argv)
 
     char *cfg = argv[3];
     char *weights = (argc > 4) ? argv[4] : 0;
-    if(0==strcmp(argv[2], "test")) test_detection(cfg, weights);
+    char *filename = (argc > 5) ? argv[5]: 0;
+    if(0==strcmp(argv[2], "test")) test_detection(cfg, weights, filename);
     else if(0==strcmp(argv[2], "train")) train_detection(cfg, weights);
     else if(0==strcmp(argv[2], "valid")) validate_detection(cfg, weights);
 }

src/detection_layer.c

@@ -29,10 +29,10 @@ detection_layer make_detection_layer(int batch, int inputs, int classes, int coo
     l.coords = coords;
     l.rescore = rescore;
     l.objectness = objectness;
+    l.background = background;
     l.joint = joint;
     l.cost = calloc(1, sizeof(float));
     l.does_cost=1;
-    l.background = background;
     int outputs = get_detection_layer_output_size(l);
     l.outputs = outputs;
     l.output = calloc(batch*outputs, sizeof(float));

src/imagenet.c

@@ -101,37 +101,40 @@ void validate_imagenet(char *filename, char *weightfile)
     }
 }
 
-void test_imagenet(char *cfgfile, char *weightfile)
+void test_imagenet(char *cfgfile, char *weightfile, char *filename)
 {
     network net = parse_network_cfg(cfgfile);
     if(weightfile){
         load_weights(&net, weightfile);
     }
     set_batch_network(&net, 1);
-    //imgs=1;
     srand(2222222);
     int i = 0;
-    char **names = get_labels("cfg/shortnames.txt");
+    char **names = get_labels("data/shortnames.txt");
     clock_t time;
-    char filename[256];
+    char input[256];
     int indexes[10];
     while(1){
-        fgets(filename, 256, stdin);
+        if(filename){
-        strtok(filename, "\n");
+            strncpy(input, filename, 256);
-        image im = load_image_color(filename, 256, 256);
+        }else{
-        scale_image(im, 2.);
+            printf("Enter Image Path: ");
-        translate_image(im, -1.);
+            fflush(stdout);
-        printf("%d %d %d\n", im.h, im.w, im.c);
+            fgets(input, 256, stdin);
+            strtok(input, "\n");
+        }
+        image im = load_image_color(input, 256, 256);
         float *X = im.data;
         time=clock();
         float *predictions = network_predict(net, X);
         top_predictions(net, 10, indexes);
-        printf("%s: Predicted in %f seconds.\n", filename, sec(clock()-time));
+        printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time));
         for(i = 0; i < 10; ++i){
             int index = indexes[i];
             printf("%s: %f\n", names[index], predictions[index]);
         }
         free_image(im);
+        if (filename) break;
     }
 }
 
@@ -144,7 +147,8 @@ void run_imagenet(int argc, char **argv)
 
     char *cfg = argv[3];
     char *weights = (argc > 4) ? argv[4] : 0;
-    if(0==strcmp(argv[2], "test")) test_imagenet(cfg, weights);
+    char *filename = (argc > 5) ? argv[5]: 0;
+    if(0==strcmp(argv[2], "test")) test_imagenet(cfg, weights, filename);
     else if(0==strcmp(argv[2], "train")) train_imagenet(cfg, weights);
     else if(0==strcmp(argv[2], "valid")) validate_imagenet(cfg, weights);
 }

src/utils.c

@@ -73,11 +73,11 @@ float sec(clock_t clocks)
 void top_k(float *a, int n, int k, int *index)
 {
     int i,j;
-    for(j = 0; j < k; ++j) index[j] = 0;
+    for(j = 0; j < k; ++j) index[j] = -1;
     for(i = 0; i < n; ++i){
         int curr = i;
         for(j = 0; j < k; ++j){
-            if(a[curr] > a[index[j]]){
+            if((index[j] < 0) || a[curr] > a[index[j]]){
                 int swap = curr;
                 curr = index[j];
                 index[j] = swap;