HongChuang/ultralytics-ascend
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Apply Ruff 0.9.0 (#18622)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Glenn Jocher 2025-01-10 00:05:09 +01:00 • committed by GitHub
parent cc1e77138c
commit 3902e740cf
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22 changed files with 69 additions and 65 deletions
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2
ultralytics/models/yolo/detect/val.py
View file

@ -168,7 +168,7 @@ class DetectionValidator(BaseValidator):
predn,
self.args.save_conf,
pbatch["ori_shape"],
self.save_dir / "labels" / f'{Path(batch["im_file"][si]).stem}.txt',
self.save_dir / "labels" / f"{Path(batch['im_file'][si]).stem}.txt",
)
def finalize_metrics(self, *args, **kwargs):

4
ultralytics/models/yolo/obb/val.py
View file

@ -163,7 +163,7 @@ class OBBValidator(DetectionValidator):
classname = self.names[d["category_id"] - 1].replace(" ", "-")
p = d["poly"]
with open(f'{pred_txt / f"Task1_{classname}"}.txt', "a") as f:
with open(f"{pred_txt / f'Task1_{classname}'}.txt", "a") as f:
f.writelines(f"{image_id} {score} {p[0]} {p[1]} {p[2]} {p[3]} {p[4]} {p[5]} {p[6]} {p[7]}\n")
# Save merged results, this could result slightly lower map than using official merging script,
# because of the probiou calculation.
@ -197,7 +197,7 @@ class OBBValidator(DetectionValidator):
p = [round(i, 3) for i in x[:-2]] # poly
score = round(x[-2], 3)
with open(f'{pred_merged_txt / f"Task1_{classname}"}.txt', "a") as f:
with open(f"{pred_merged_txt / f'Task1_{classname}'}.txt", "a") as f:
f.writelines(f"{image_id} {score} {p[0]} {p[1]} {p[2]} {p[3]} {p[4]} {p[5]} {p[6]} {p[7]}\n")
return stats

2
ultralytics/models/yolo/pose/val.py
View file

@ -153,7 +153,7 @@ class PoseValidator(DetectionValidator):
pred_kpts,
self.args.save_conf,
pbatch["ori_shape"],
self.save_dir / "labels" / f'{Path(batch["im_file"][si]).stem}.txt',
self.save_dir / "labels" / f"{Path(batch['im_file'][si]).stem}.txt",
)
def _process_batch(self, detections, gt_bboxes, gt_cls, pred_kpts=None, gt_kpts=None):

2
ultralytics/models/yolo/segment/val.py
View file

@ -162,7 +162,7 @@ class SegmentationValidator(DetectionValidator):
pred_masks,
self.args.save_conf,
pbatch["ori_shape"],
self.save_dir / "labels" / f'{Path(batch["im_file"][si]).stem}.txt',
self.save_dir / "labels" / f"{Path(batch['im_file'][si]).stem}.txt",
)
def finalize_metrics(self, *args, **kwargs):