fix #5254

fiftyone/operators/builtins/panels/model_evaluation/__init__.py

@@ -5,16 +5,17 @@
 | `voxel51.com <https://voxel51.com/>`_
 |
 """
-
+from collections import defaultdict, Counter
 import os
 import traceback
-import fiftyone.operators.types as types
 
-from collections import defaultdict, Counter
+import numpy as np
+
 from fiftyone import ViewField as F
 from fiftyone.operators.categories import Categories
 from fiftyone.operators.panel import Panel, PanelConfig
 from fiftyone.core.plots.plotly import _to_log_colorscale
+import fiftyone.operators.types as types
 
 
 STORE_NAME = "model_evaluation_panel_builtin"
@@ -104,29 +105,32 @@ def get_avg_confidence(self, per_class_metrics):
                 total += metrics["confidence"]
         return total / count if count > 0 else None
 
-    def get_tp_fp_fn(self, ctx):
-        view_state = ctx.panel.get_state("view") or {}
-        key = view_state.get("key")
-        dataset = ctx.dataset
-        tp_key = f"{key}_tp"
-        fp_key = f"{key}_fp"
-        fn_key = f"{key}_fn"
-        tp_total = (
-            sum(ctx.dataset.values(tp_key))
-            if dataset.has_field(tp_key)
-            else None
-        )
-        fp_total = (
-            sum(ctx.dataset.values(fp_key))
-            if dataset.has_field(fp_key)
-            else None
-        )
-        fn_total = (
-            sum(ctx.dataset.values(fn_key))
-            if dataset.has_field(fn_key)
-            else None
-        )
-        return tp_total, fp_total, fn_total
+    def get_tp_fp_fn(self, info, results):
+        # Binary classification
+        if (
+            info.config.type == "classification"
+            and info.config.method == "binary"
+        ):
+            neg_label, pos_label = results.classes
+            tp_count = np.count_nonzero(
+                (results.ytrue == pos_label) & (results.ypred == pos_label)
+            )
+            fp_count = np.count_nonzero(
+                (results.ytrue != pos_label) & (results.ypred == pos_label)
+            )
+            fn_count = np.count_nonzero(
+                (results.ytrue == pos_label) & (results.ypred != pos_label)
+            )
+            return tp_count, fp_count, fn_count
+
+        # Object detection
+        if info.config.type == "detection":
+            tp_count = np.count_nonzero(results.ytrue == results.ypred)
+            fp_count = np.count_nonzero(results.ytrue == results.missing)
+            fn_count = np.count_nonzero(results.ypred == results.missing)
+            return tp_count, fp_count, fn_count
+
+        return None, None, None
 
     def get_map(self, results):
         try:
@@ -298,7 +302,7 @@ def load_evaluation(self, ctx):
                 per_class_metrics
             )
             metrics["tp"], metrics["fp"], metrics["fn"] = self.get_tp_fp_fn(
-                ctx
+                info, results
             )
             metrics["mAP"] = self.get_map(results)
             evaluation_data = {