Update Obj Det iou thresholds to [0.1, 0.5, 0.75] (#832)

Author: czaloom

Makefile

@@ -1,4 +1,4 @@
-.PHONY: install pre-commit tests clean help
+.PHONY: install pre-commit test help
 
 install:
 	@echo "Installing from source..."

benchmarks/benchmark_objdet.py

@@ -323,7 +323,10 @@ def run_benchmarking_analysis(
                 )
 
             # evaluate - base metrics only
-            eval_time, metrics = time_it(evaluator.compute_precision_recall)()
+            eval_time, metrics = time_it(evaluator.compute_precision_recall)(
+                score_thresholds=[0.5, 0.75, 0.9],
+                iou_thresholds=[0.1, 0.5, 0.75],
+            )
             if eval_time > evaluation_timeout and evaluation_timeout != -1:
                 raise TimeoutError(
                     f"Base evaluation timed out with {evaluator.n_datums} datums."
@@ -333,6 +336,8 @@ def run_benchmarking_analysis(
             detailed_counts_time_no_samples, metrics = time_it(
                 evaluator.compute_confusion_matrix
             )(
+                score_thresholds=[0.5, 0.75, 0.9],
+                iou_thresholds=[0.1, 0.5, 0.75],
                 number_of_examples=0,
             )
             if (
@@ -347,6 +352,8 @@ def run_benchmarking_analysis(
             detailed_counts_time_three_samples, metrics = time_it(
                 evaluator.compute_confusion_matrix
             )(
+                score_thresholds=[0.5, 0.75, 0.9],
+                iou_thresholds=[0.1, 0.5, 0.75],
                 number_of_examples=3,
             )
             if (

src/valor_lite/object_detection/manager.py

@@ -195,8 +195,8 @@ def create_filter(
 
     def compute_precision_recall(
         self,
-        iou_thresholds: list[float] = [0.5, 0.75, 0.9],
-        score_thresholds: list[float] = [0.5],
+        iou_thresholds: list[float],
+        score_thresholds: list[float],
         filter_: Filter | None = None,
     ) -> dict[MetricType, list[Metric]]:
         """
@@ -240,9 +240,9 @@ def compute_precision_recall(
 
     def compute_confusion_matrix(
         self,
-        iou_thresholds: list[float] = [0.5, 0.75, 0.9],
-        score_thresholds: list[float] = [0.5],
-        number_of_examples: int = 0,
+        iou_thresholds: list[float],
+        score_thresholds: list[float],
+        number_of_examples: int,
         filter_: Filter | None = None,
     ) -> list[Metric]:
         """
@@ -254,7 +254,7 @@ def compute_confusion_matrix(
             A list of IOU thresholds to compute metrics over.
         score_thresholds : list[float]
             A list of score thresholds to compute metrics over.
-        number_of_examples : int, default=0
+        number_of_examples : int
             Maximum number of annotation examples to return in ConfusionMatrix.
         filter_ : Filter, optional
             An optional filter object.
@@ -295,7 +295,7 @@ def compute_confusion_matrix(
 
     def evaluate(
         self,
-        iou_thresholds: list[float] = [0.5, 0.75, 0.9],
+        iou_thresholds: list[float] = [0.1, 0.5, 0.75],
         score_thresholds: list[float] = [0.5],
         number_of_examples: int = 0,
         filter_: Filter | None = None,
@@ -305,9 +305,9 @@ def evaluate(
 
         Parameters
         ----------
-        iou_thresholds : list[float]
+        iou_thresholds : list[float], default=[0.1, 0.5, 0.75]
             A list of IOU thresholds to compute metrics over.
-        score_thresholds : list[float]
+        score_thresholds : list[float], default=[0.5]
             A list of score thresholds to compute metrics over.
         number_of_examples : int, default=0
             Maximum number of annotation examples to return in ConfusionMatrix.

tests/object_detection/test_filtering.py

@@ -572,6 +572,8 @@ def test_filtering_all_detections(four_detections: list[Detection]):
     )
     evaluator.compute_confusion_matrix(
         iou_thresholds=[0.5],
+        score_thresholds=[0.5],
+        number_of_examples=0,
         filter_=filter_,
     )