metrics[0]: add per-image overlap (pimo) [GSoC 2023 @ OpenVINO]

src/anomalib/utils/metrics/__init__.py

@@ -20,9 +20,22 @@
 from .collection import AnomalibMetricCollection
 from .min_max import MinMax
 from .optimal_f1 import OptimalF1
+from .perimg import AUPImO, PerImageBinClfCurve, PImO
 from .pro import PRO
 
-__all__ = ["AUROC", "AUPR", "AUPRO", "OptimalF1", "AnomalyScoreThreshold", "AnomalyScoreDistribution", "MinMax", "PRO"]
+__all__ = [
+    "AUROC",
+    "AUPR",
+    "AUPRO",
+    "OptimalF1",
+    "AnomalyScoreThreshold",
+    "AnomalyScoreDistribution",
+    "MinMax",
+    "PRO",
+    "PerImageBinClfCurve",
+    "PImO",
+    "AUPImO",
+]
 
 
 def metric_collection_from_names(metric_names: list[str], prefix: str | None) -> AnomalibMetricCollection:

src/anomalib/utils/metrics/perimg/.gitignore

@@ -0,0 +1,27 @@
+# temporary file to manage branches/PRs so they are simpler
+
+fpr.py
+
+
+tpr.py
+
+
+
+
+
+slogroc.py
+
+
+tpatfp.py
+
+
+
+fp_requirement.py
+
+
+
+precisionroc.py
+
+
+
+scratch.py

src/anomalib/utils/metrics/perimg/__init__.py

@@ -0,0 +1,15 @@
+"""Per-Image Metrics.
+
+Overall approach:
+Thresholds are computed across all images, but the metrics are computed per-image.
+Metrics here are based on binary classification metrics (e.g. FPR, TPR, Precision) over a range of thresholds.
+"""
+
+from .binclf_curve import PerImageBinClfCurve
+from .pimo import AUPImO, PImO
+
+__all__ = [
+    "PerImageBinClfCurve",
+    "PImO",
+    "AUPImO",
+]