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# Ultralytics YOLO 🚀, AGPL-3.0 license
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import torch
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from ultralytics.models.yolo.detect import DetectionValidator
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from ultralytics.utils import ops
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__all__ = ['NASValidator']
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class NASValidator(DetectionValidator):
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def postprocess(self, preds_in):
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"""Apply Non-maximum suppression to prediction outputs."""
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boxes = ops.xyxy2xywh(preds_in[0][0])
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preds = torch.cat((boxes, preds_in[0][1]), -1).permute(0, 2, 1)
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return ops.non_max_suppression(preds,
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self.args.conf,
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self.args.iou,
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labels=self.lb,
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multi_label=False,
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agnostic=self.args.single_cls,
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max_det=self.args.max_det,
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max_time_img=0.5)
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