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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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