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ultralytics 8.1.16 OBB ConfusionMatrix support (#8299)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Laughing 2024-02-19 23:59:24 +08:00 • committed by GitHub
parent 42744a1717
commit de01212465
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12 changed files with 26 additions and 20 deletions
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6
ultralytics/models/yolo/detect/val.py
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@ -132,8 +132,7 @@ class DetectionValidator(BaseValidator):
if nl:
for k in self.stats.keys():
self.stats[k].append(stat[k])
# TODO: obb has not supported confusion_matrix yet.
if self.args.plots and self.args.task != "obb":
if self.args.plots:
self.confusion_matrix.process_batch(detections=None, gt_bboxes=bbox, gt_cls=cls)
continue
@ -147,8 +146,7 @@ class DetectionValidator(BaseValidator):
# Evaluate
if nl:
stat["tp"] = self._process_batch(predn, bbox, cls)
# TODO: obb has not supported confusion_matrix yet.
if self.args.plots and self.args.task != "obb":
if self.args.plots:
self.confusion_matrix.process_batch(predn, bbox, cls)
for k in self.stats.keys():
self.stats[k].append(stat[k])

9
ultralytics/models/yolo/obb/val.py
View file

@ -55,10 +55,11 @@ class OBBValidator(DetectionValidator):
Return correct prediction matrix.
Args:
detections (torch.Tensor): Tensor of shape [N, 6] representing detections.
Each detection is of the format: x1, y1, x2, y2, conf, class.
labels (torch.Tensor): Tensor of shape [M, 5] representing labels.
Each label is of the format: class, x1, y1, x2, y2.
detections (torch.Tensor): Tensor of shape [N, 7] representing detections.
Each detection is of the format: x1, y1, x2, y2, conf, class, angle.
gt_bboxes (torch.Tensor): Tensor of shape [M, 5] representing rotated boxes.
Each box is of the format: x1, y1, x2, y2, angle.
labels (torch.Tensor): Tensor of shape [M] representing labels.
Returns:
(torch.Tensor): Correct prediction matrix of shape [N, 10] for 10 IoU levels.