TextSnakePostprocessor

class mmocr.models.textdet.TextSnakePostprocessor(text_repr_type='poly', min_text_region_confidence=0.6, min_center_region_confidence=0.2, min_center_area=30, disk_overlap_thr=0.03, radius_shrink_ratio=1.03, rescale_fields=['polygons'], **kwargs)

Decoding predictions of TextSnake to instances. This was partially adapted from https://github.com/princewang1994/TextSnake.pytorch.

Parameters

• text_repr_type (str) – The boundary encoding type ‘poly’ or ‘quad’.

• min_text_region_confidence (float) – The confidence threshold of text region in TextSnake.

• min_center_region_confidence (float) – The confidence threshold of text center region in TextSnake.

• min_center_area (int) – The minimal text center region area.

• disk_overlap_thr (float) – The radius overlap threshold for merging disks.

• radius_shrink_ratio (float) – The shrink ratio of ordered disks radii.

• rescale_fields (list[str], optional) – The bbox/polygon field names to be rescaled. If None, no rescaling will be performed.

Return type

None

get_text_instances(pred_results, data_sample)

Parameters

• pred_results (torch.Tensor) – Prediction map with shape \((C, H, W)\).

• data_sample (TextDetDataSample) – Datasample of an image.

Returns

The instance boundary and its confidence.

Return type

list[list[float]]

split_results(pred_results)

Split the prediction results into text score and kernel score.

Parameters

pred_results (torch.Tensor) – The prediction results.

Returns

The text score and kernel score.

Return type

List[torch.Tensor]