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@ -90,12 +90,14 @@ class SegmentationValidator(DetectionValidator):
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if self.args.single_cls:
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if self.args.single_cls:
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pred[:, 5] = 0
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pred[:, 5] = 0
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predn = pred.clone()
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predn = pred.clone()
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ops.scale_boxes(batch["img"][si].shape[1:], predn[:, :4], shape) # native-space pred
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ops.scale_boxes(batch["img"][si].shape[1:], predn[:, :4], shape,
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ratio_pad=batch["ratio_pad"][si]) # native-space pred
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# Evaluate
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# Evaluate
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if nl:
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if nl:
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tbox = ops.xywh2xyxy(bbox) # target boxes
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tbox = ops.xywh2xyxy(bbox) # target boxes
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ops.scale_boxes(batch["img"][si].shape[1:], tbox, shape) # native-space labels
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ops.scale_boxes(batch["img"][si].shape[1:], tbox, shape,
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ratio_pad=batch["ratio_pad"][si]) # native-space labels
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labelsn = torch.cat((cls, tbox), 1) # native-space labels
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labelsn = torch.cat((cls, tbox), 1) # native-space labels
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correct_bboxes = self._process_batch(predn, labelsn)
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correct_bboxes = self._process_batch(predn, labelsn)
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# TODO: maybe remove these `self.` arguments as they already are member variable
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# TODO: maybe remove these `self.` arguments as they already are member variable
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@ -117,7 +119,9 @@ class SegmentationValidator(DetectionValidator):
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# Save
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# Save
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if self.args.save_json:
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if self.args.save_json:
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pred_masks = ops.scale_image(batch["img"][si].shape[1:],
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pred_masks = ops.scale_image(batch["img"][si].shape[1:],
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pred_masks.permute(1, 2, 0).contiguous().cpu().numpy(), shape)
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pred_masks.permute(1, 2, 0).contiguous().cpu().numpy(),
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shape,
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ratio_pad=batch["ratio_pad"][si])
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self.pred_to_json(predn, batch["im_file"][si], pred_masks)
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self.pred_to_json(predn, batch["im_file"][si], pred_masks)
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# if self.args.save_txt:
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# if self.args.save_txt:
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# save_one_txt(predn, save_conf, shape, file=save_dir / 'labels' / f'{path.stem}.txt')
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# save_one_txt(predn, save_conf, shape, file=save_dir / 'labels' / f'{path.stem}.txt')
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