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| # Copyright (c) OpenMMLab. All rights reserved. | |
| from mmengine.structures import BaseDataElement, InstanceData | |
| class TextDetDataSample(BaseDataElement): | |
| """A data structure interface of MMOCR. They are used as interfaces between | |
| different components. | |
| The attributes in ``TextDetDataSample`` are divided into two parts: | |
| - ``gt_instances``(InstanceData): Ground truth of instance annotations. | |
| - ``pred_instances``(InstanceData): Instances of model predictions. | |
| Examples: | |
| >>> import torch | |
| >>> import numpy as np | |
| >>> from mmengine.structures import InstanceData | |
| >>> from mmocr.data import TextDetDataSample | |
| >>> # gt_instances | |
| >>> data_sample = TextDetDataSample() | |
| >>> img_meta = dict(img_shape=(800, 1196, 3), | |
| ... pad_shape=(800, 1216, 3)) | |
| >>> gt_instances = InstanceData(metainfo=img_meta) | |
| >>> gt_instances.bboxes = torch.rand((5, 4)) | |
| >>> gt_instances.labels = torch.rand((5,)) | |
| >>> data_sample.gt_instances = gt_instances | |
| >>> assert 'img_shape' in data_sample.gt_instances.metainfo_keys() | |
| >>> len(data_sample.gt_instances) | |
| 5 | |
| >>> print(data_sample) | |
| <TextDetDataSample( | |
| META INFORMATION | |
| DATA FIELDS | |
| gt_instances: <InstanceData( | |
| META INFORMATION | |
| pad_shape: (800, 1216, 3) | |
| img_shape: (800, 1196, 3) | |
| DATA FIELDS | |
| labels: tensor([0.8533, 0.1550, 0.5433, 0.7294, 0.5098]) | |
| bboxes: | |
| tensor([[9.7725e-01, 5.8417e-01, 1.7269e-01, 6.5694e-01], | |
| [1.7894e-01, 5.1780e-01, 7.0590e-01, 4.8589e-01], | |
| [7.0392e-01, 6.6770e-01, 1.7520e-01, 1.4267e-01], | |
| [2.2411e-01, 5.1962e-01, 9.6953e-01, 6.6994e-01], | |
| [4.1338e-01, 2.1165e-01, 2.7239e-04, 6.8477e-01]]) | |
| ) at 0x7f21fb1b9190> | |
| ) at 0x7f21fb1b9880> | |
| >>> # pred_instances | |
| >>> pred_instances = InstanceData(metainfo=img_meta) | |
| >>> pred_instances.bboxes = torch.rand((5, 4)) | |
| >>> pred_instances.scores = torch.rand((5,)) | |
| >>> data_sample = TextDetDataSample(pred_instances=pred_instances) | |
| >>> assert 'pred_instances' in data_sample | |
| >>> data_sample = TextDetDataSample() | |
| >>> gt_instances_data = dict( | |
| ... bboxes=torch.rand(2, 4), | |
| ... labels=torch.rand(2), | |
| ... masks=np.random.rand(2, 2, 2)) | |
| >>> gt_instances = InstanceData(**gt_instances_data) | |
| >>> data_sample.gt_instances = gt_instances | |
| >>> assert 'gt_instances' in data_sample | |
| >>> assert 'masks' in data_sample.gt_instances | |
| """ | |
| def gt_instances(self) -> InstanceData: | |
| """InstanceData: groundtruth instances.""" | |
| return self._gt_instances | |
| def gt_instances(self, value: InstanceData): | |
| """gt_instances setter.""" | |
| self.set_field(value, '_gt_instances', dtype=InstanceData) | |
| def gt_instances(self): | |
| """gt_instances deleter.""" | |
| del self._gt_instances | |
| def pred_instances(self) -> InstanceData: | |
| """InstanceData: prediction instances.""" | |
| return self._pred_instances | |
| def pred_instances(self, value: InstanceData): | |
| """pred_instances setter.""" | |
| self.set_field(value, '_pred_instances', dtype=InstanceData) | |
| def pred_instances(self): | |
| """pred_instances deleter.""" | |
| del self._pred_instances | |