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fix overlap_mask in SegmentationLoss (#2985)

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Laughing 2023-06-05 04:35:33 +08:00 committed by GitHub
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1 changed files with 2 additions and 2 deletions
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ultralytics/yolo/utils/loss.py
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@ -178,10 +178,10 @@ class v8DetectionLoss:
# Criterion class for computing training losses # Criterion class for computing training losses
class v8SegmentationLoss(v8DetectionLoss): class v8SegmentationLoss(v8DetectionLoss):
def __init__(self, model, overlap=True): # model must be de-paralleled def __init__(self, model): # model must be de-paralleled
super().__init__(model) super().__init__(model)
self.nm = model.model[-1].nm # number of masks self.nm = model.model[-1].nm # number of masks
self.overlap = overlap self.overlap = model.args.overlap_mask
def __call__(self, preds, batch): def __call__(self, preds, batch):
"""Calculate and return the loss for the YOLO model.""" """Calculate and return the loss for the YOLO model."""