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