Merge branch 'master' into feature-#672

Author: Borda

tests/detection/test_map.py

@@ -215,6 +215,26 @@ def test_empty_preds():
     metric.compute()
 
 
+@pytest.mark.skipif(_pytest_condition, reason="test requires that torchvision=>0.8.0 is installed")
+def test_empty_ground_truths():
+    """Test empty ground truths."""
+    metric = MAP()
+
+    metric.update(
+        [
+            dict(
+                boxes=torch.Tensor([[214.1500, 41.2900, 562.4100, 285.0700]]),
+                scores=torch.Tensor([0.5]),
+                labels=torch.IntTensor([4]),
+            ),
+        ],
+        [
+            dict(boxes=torch.Tensor([]), labels=torch.IntTensor([])),
+        ],
+    )
+    metric.compute()
+
+
 _gpu_test_condition = not torch.cuda.is_available()
 
 

torchmetrics/detection/map.py

@@ -356,7 +356,7 @@ def _compute_iou(self, id: int, class_id: int, max_det: int) -> Tensor:
         det = self.detection_boxes[id]
         gt_label_mask = self.groundtruth_labels[id] == class_id
         det_label_mask = self.detection_labels[id] == class_id
-        if len(det_label_mask) == 0 or len(det_label_mask) == 0:
+        if len(gt_label_mask) == 0 or len(det_label_mask) == 0:
             return Tensor([])
         gt = gt[gt_label_mask]
         det = det[det_label_mask]
@@ -396,7 +396,7 @@ def _evaluate_image(
         det = self.detection_boxes[id]
         gt_label_mask = self.groundtruth_labels[id] == class_id
         det_label_mask = self.detection_labels[id] == class_id
-        if len(det_label_mask) == 0 or len(det_label_mask) == 0:
+        if len(gt_label_mask) == 0 or len(det_label_mask) == 0:
             return None
         gt = gt[gt_label_mask]
         det = det[det_label_mask]