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[Fix] Fix SegTTAModel with no attribute '_gt_sem_seg' error (#3152)

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## Motivation

When using the - tta command for multi-scale prediction, and the test
set is not annotated, although format_only has been set true in
test_evaluator, but SegTTAModel class still threw error 'AttributeError:
'SegDataSample' object has no attribute '_gt_sem_seg''.

## Modification

The reason is SegTTAModel didn't determine if there were annotations in
the dataset, so I added the code to make the judgment and let the
program run normally on my computer.
This commit is contained in:
ZiAn-Su 2023-07-13 17:06:06 +08:00 committed by GitHub
parent 067a95e40b
commit 7254f5330f
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1 changed files with 4 additions and 6 deletions
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10
mmseg/models/segmentors/seg_tta.py
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@ -6,7 +6,6 @@ from mmengine.model import BaseTTAModel
from mmengine.structures import PixelData from mmengine.structures import PixelData
from mmseg.registry import MODELS from mmseg.registry import MODELS
from mmseg.structures import SegDataSample
from mmseg.utils import SampleList from mmseg.utils import SampleList
@ -39,11 +38,10 @@ class SegTTAModel(BaseTTAModel):
).to(logits).squeeze(1) ).to(logits).squeeze(1)
else: else:
seg_pred = logits.argmax(dim=0) seg_pred = logits.argmax(dim=0)
data_sample = SegDataSample( data_sample.set_data({'pred_sem_seg': PixelData(data=seg_pred)})
**{ if hasattr(data_samples[0], 'gt_sem_seg'):
'pred_sem_seg': PixelData(data=seg_pred), data_sample.set_data(
'gt_sem_seg': data_samples[0].gt_sem_seg {'gt_sem_seg': data_samples[0].gt_sem_seg})
})
data_sample.set_metainfo({'img_path': data_samples[0].img_path}) data_sample.set_metainfo({'img_path': data_samples[0].img_path})
predictions.append(data_sample) predictions.append(data_sample)
return predictions return predictions