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Code Issues Projects Releases Packages Wiki Activity Actions 8

Fix AP calculation precision in compute_ap (#24175)

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Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Jing Qiu 2026-04-09 18:50:30 +08:00 committed by GitHub
parent fa3dd8d96e
commit a481399723
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3 changed files with 13 additions and 10 deletions
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16
.github/workflows/ci.yml vendored
View file

@ -74,19 +74,19 @@ jobs:
uv pip list
- name: Benchmark DetectionModel
shell: bash
run: coverage run -a --source=ultralytics -m ultralytics.cfg.__init__ benchmark model='path with spaces/${{ matrix.model }}.pt' imgsz=160 verbose=0.218
run: coverage run -a --source=ultralytics -m ultralytics.cfg.__init__ benchmark model='path with spaces/${{ matrix.model }}.pt' imgsz=160 verbose=0.216
- name: Benchmark ClassificationModel
shell: bash
run: coverage run -a --source=ultralytics -m ultralytics.cfg.__init__ benchmark model='path with spaces/${{ matrix.model }}-cls.pt' imgsz=160 verbose=0.249
- name: Benchmark YOLOWorld DetectionModel
shell: bash
run: coverage run -a --source=ultralytics -m ultralytics.cfg.__init__ benchmark model='path with spaces/yolov8s-worldv2.pt' imgsz=160 verbose=0.337
run: coverage run -a --source=ultralytics -m ultralytics.cfg.__init__ benchmark model='path with spaces/yolov8s-worldv2.pt' imgsz=160 verbose=0.335
- name: Benchmark SegmentationModel
shell: bash
run: coverage run -a --source=ultralytics -m ultralytics.cfg.__init__ benchmark model='path with spaces/${{ matrix.model }}-seg.pt' imgsz=160 verbose=0.230
run: coverage run -a --source=ultralytics -m ultralytics.cfg.__init__ benchmark model='path with spaces/${{ matrix.model }}-seg.pt' imgsz=160 verbose=0.229
- name: Benchmark PoseModel
shell: bash
run: coverage run -a --source=ultralytics -m ultralytics.cfg.__init__ benchmark model='path with spaces/${{ matrix.model }}-pose.pt' imgsz=160 verbose=0.194
run: coverage run -a --source=ultralytics -m ultralytics.cfg.__init__ benchmark model='path with spaces/${{ matrix.model }}-pose.pt' imgsz=160 verbose=0.185
- name: Benchmark OBBModel
shell: bash
run: coverage run -a --source=ultralytics -m ultralytics.cfg.__init__ benchmark model='path with spaces/${{ matrix.model }}-obb.pt' imgsz=160 verbose=0.372
@ -345,15 +345,15 @@ jobs:
yolo checks
uv pip list
- name: Benchmark DetectionModel
run: python -m ultralytics.cfg.__init__ benchmark model='yolo26n.pt' imgsz=160 verbose=0.218
run: python -m ultralytics.cfg.__init__ benchmark model='yolo26n.pt' imgsz=160 verbose=0.216
- name: Benchmark ClassificationModel
run: python -m ultralytics.cfg.__init__ benchmark model='yolo26n-cls.pt' imgsz=160 verbose=0.249
- name: Benchmark YOLOWorld DetectionModel
run: python -m ultralytics.cfg.__init__ benchmark model='yolov8s-worldv2.pt' imgsz=160 verbose=0.337
run: python -m ultralytics.cfg.__init__ benchmark model='yolov8s-worldv2.pt' imgsz=160 verbose=0.335
- name: Benchmark SegmentationModel
run: python -m ultralytics.cfg.__init__ benchmark model='yolo26n-seg.pt' imgsz=160 verbose=0.230
run: python -m ultralytics.cfg.__init__ benchmark model='yolo26n-seg.pt' imgsz=160 verbose=0.229
- name: Benchmark PoseModel
run: python -m ultralytics.cfg.__init__ benchmark model='yolo26n-pose.pt' imgsz=160 verbose=0.194
run: python -m ultralytics.cfg.__init__ benchmark model='yolo26n-pose.pt' imgsz=160 verbose=0.185
- name: Benchmark OBBModel
run: python -m ultralytics.cfg.__init__ benchmark model='yolo26n-obb.pt' imgsz=160 verbose=0.372
- name: Benchmark Summary

3
docs/mkdocs_github_authors.yaml
View file

@ -217,6 +217,9 @@ davis.justin@mssm.org:
esat@ultralytics.com:
avatar: https://avatars.githubusercontent.com/u/43647848?v=4
username: artest08
faruk.gmstss@gmail.com:
avatar: null
username: null
fatih@ultralytics.com:
avatar: https://avatars.githubusercontent.com/u/34196005?v=4
username: fcakyon

4
ultralytics/utils/metrics.py
View file

@ -728,8 +728,8 @@ def compute_ap(recall: list[float], precision: list[float]) -> tuple[float, np.n
mrec (np.ndarray): Modified recall curve with sentinel values added at the beginning and end.
"""
# Append sentinel values to beginning and end
mrec = np.concatenate(([0.0], recall, [1.0]))
mpre = np.concatenate(([1.0], precision, [0.0]))
mrec = np.concatenate(([0.0], recall, [recall[-1] if len(recall) else 1.0], [1.0]))
mpre = np.concatenate(([1.0], precision, [0.0], [0.0]))
# Compute the precision envelope
mpre = np.flip(np.maximum.accumulate(np.flip(mpre)))