Fix unexpected key pixel_metrics.AUPRO.fpr_limit

src/anomalib/models/components/base/anomaly_module.py

@@ -5,6 +5,7 @@
 
 from __future__ import annotations
 
+import importlib
 import logging
 from abc import ABC
 from typing import Any, OrderedDict
@@ -234,11 +235,38 @@ def _load_normalization_class(self, state_dict: OrderedDict[str, Tensor]) -> Non
         else:
             warn("No known normalization found in model weights.")
 
+    def _load_metrics(self, state_dict: OrderedDict[str, Tensor]) -> None:
+        """Load metrics from saved checkpoint."""
+        self._set_metrics("pixel", state_dict)
+        self._set_metrics("image", state_dict)
+
+    def _set_metrics(self, name: str, state_dict: OrderedDict[str, Tensor]):
+        """Sets the pixel/image metrics.
+
+        Args:
+        name (str): is it pixel or image.
+        state_dict (OrderedDict[str, Tensor]): state dict of the model.
+        """
+        metric_keys = [key for key in state_dict.keys() if key.startswith(f"{name}_metrics")]
+        if not hasattr(self, f"{name}_metrics") and any(metric_keys):
+            metrics = AnomalibMetricCollection([], prefix=f"{name}_")
+            for key in metric_keys:
+                class_name = key.split(".")[1]
+                try:
+                    metrics_module = importlib.import_module("anomalib.utils.metrics")
+                    metrics_cls = getattr(metrics_module, class_name)
+                except Exception as exception:
+                    raise ImportError(f"Class {class_name} not found in module anomalib.utils.metrics") from exception
+                metrics.add_metrics(metrics_cls())
+            setattr(self, f"{name}_metrics", metrics)
+
     def load_state_dict(self, state_dict: OrderedDict[str, Tensor], strict: bool = True):
         """Load state dict from checkpoint.
 
         Ensures that normalization and thresholding attributes is properly setup before model is loaded.
         """
         # Used to load missing normalization and threshold parameters
         self._load_normalization_class(state_dict)
+        # Used to load metrics if there is any related data in state_dict
+        self._load_metrics(state_dict)
         return super().load_state_dict(state_dict, strict=strict)

src/anomalib/utils/callbacks/metrics_configuration.py

@@ -77,7 +77,13 @@ def setup(
 
         if isinstance(pl_module, AnomalyModule):
             pl_module.image_metrics = create_metric_collection(image_metric_names, "image_")
-            pl_module.pixel_metrics = create_metric_collection(pixel_metric_names, "pixel_")
+            if hasattr(pl_module, "pixel_metrics"):
+                new_metrics = create_metric_collection(pixel_metric_names, "pixel_")
+                for name in new_metrics.keys():
+                    if name not in pl_module.pixel_metrics.keys():
+                        pl_module.pixel_metrics.add_metrics(new_metrics[name.split("_")[1]])
+            else:
+                pl_module.pixel_metrics = create_metric_collection(pixel_metric_names, "pixel_")
 
             pl_module.image_metrics.set_threshold(pl_module.image_threshold.value)
             pl_module.pixel_metrics.set_threshold(pl_module.pixel_threshold.value)