fixed nan

box-metrics.py

@@ -156,7 +156,7 @@ class box_metrics(evaluate.Metric):
                     detections_i = detections_i.astype(int)
 
                     for pair in zip(labels_i, detections_i, ious_v):
-                        print(pair)
+
                         iou = pair[2]
                         t_box = frame_labels[pair[0]][1:]
                         p_box = frame_detections[pair[1]][:4]
@@ -176,9 +176,6 @@ class box_metrics(evaluate.Metric):
                         p_w = p_box[2].item()-p_box[0].item()
                         t_h = t_box[3].item()-t_box[1].item()
                         p_h = p_box[3].item()-p_box[1].item()
-                        
-                        if t_h < 10:
-                            continue
 
                         ious = np.append(ious, iou)
                         beps = np.append(beps, bep)
@@ -192,7 +189,7 @@ class box_metrics(evaluate.Metric):
                         e_n_heights = np.append(e_n_heights, (p_h-t_h)/t_h)
                         e_n_bottom_x = np.append(e_n_bottom_x, (p_xc-t_xc)/t_w)
                         e_n_bottom_y = np.append(e_n_bottom_y, (p_yc-t_yc)/t_h)
-            print(ious)
+
             output[sequence][model] = {
                                     "iou": np.mean(ious),
                                     "bep": np.mean(beps),