diff --git a/utils/metrics.py b/utils/metrics.py
index ba812ff13a58..666b8c7ec1c0 100644
--- a/utils/metrics.py
+++ b/utils/metrics.py
@@ -147,12 +147,12 @@ def process_batch(self, detections, labels):
             if n and sum(j) == 1:
                 self.matrix[gc, detection_classes[m1[j]]] += 1  # correct
             else:
-                self.matrix[gc, self.nc] += 1  # background FP
+                self.matrix[self.nc, gc] += 1  # background FP
 
         if n:
             for i, dc in enumerate(detection_classes):
                 if not any(m1 == i):
-                    self.matrix[self.nc, dc] += 1  # background FN
+                    self.matrix[dc, self.nc] += 1  # background FN
 
     def matrix(self):
         return self.matrix
@@ -168,8 +168,8 @@ def plot(self, save_dir='', names=()):
             sn.set(font_scale=1.0 if self.nc < 50 else 0.8)  # for label size
             labels = (0 < len(names) < 99) and len(names) == self.nc  # apply names to ticklabels
             sn.heatmap(array, annot=self.nc < 30, annot_kws={"size": 8}, cmap='Blues', fmt='.2f', square=True,
-                       xticklabels=names + ['background FN'] if labels else "auto",
-                       yticklabels=names + ['background FP'] if labels else "auto").set_facecolor((1, 1, 1))
+                       xticklabels=names + ['background FP'] if labels else "auto",
+                       yticklabels=names + ['background FN'] if labels else "auto").set_facecolor((1, 1, 1))
             fig.axes[0].set_xlabel('True')
             fig.axes[0].set_ylabel('Predicted')
             fig.savefig(Path(save_dir) / 'confusion_matrix.png', dpi=250)