Fix confusion matrix update when no predictions are made

utils/metrics.py

@@ -169,6 +169,19 @@ def process_batch(self, detections, labels):
                 if not any(m1 == i):
                     self.matrix[dc, self.nc] += 1  # background FN
 
+    def process_batch_no_detections(self, labels):
+        """
+                Updates confusion matrix when model made zero predictions but the image contains groundtruth objects.
+                Every label passed in is considered a False Negative (a missed detection)
+                Arguments:
+                    labels (Array[M, 1]), [class]
+                Returns:
+                    None, updates confusion matrix accordingly
+                """
+        gt_classes = labels.int()
+        for i, gc in enumerate(gt_classes):
+            self.matrix[self.nc, gc] += 1  # background FN
+
     def matrix(self):
         return self.matrix
 

val.py

@@ -228,6 +228,8 @@ def run(
             if npr == 0:
                 if nl:
                     stats.append((correct, *torch.zeros((2, 0), device=device), labels[:, 0]))
+                    if plots:
+                        confusion_matrix.process_batch_no_detections(labels[:, 0])
                 continue
 
             # Predictions