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Display Val images per class (#12645)

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Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Adamcode 2024-05-29 23:02:41 +08:00 • committed by GitHub
parent b95b583237
commit 7cd871dbd0
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4 changed files with 13 additions and 8 deletions
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ultralytics/models/yolo/pose/val.py
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@ -81,7 +81,7 @@ class PoseValidator(DetectionValidator):
is_pose = self.kpt_shape == [17, 3]
nkpt = self.kpt_shape[0]
self.sigma = OKS_SIGMA if is_pose else np.ones(nkpt) / nkpt
self.stats = dict(tp_p=[], tp=[], conf=[], pred_cls=[], target_cls=[])
self.stats = dict(tp_p=[], tp=[], conf=[], pred_cls=[], target_cls=[], target_img=[])
def _prepare_batch(self, si, batch):
"""Prepares a batch for processing by converting keypoints to float and moving to device."""
@ -118,6 +118,7 @@ class PoseValidator(DetectionValidator):
cls, bbox = pbatch.pop("cls"), pbatch.pop("bbox")
nl = len(cls)
stat["target_cls"] = cls
stat["target_img"] = cls.unique()
if npr == 0:
if nl:
for k in self.stats.keys():