def get_boundary(self, score_maps, img_metas, rescale):
"""Compute text boundaries via post processing.
Args:
score_maps (Tensor): The text score map.
img_metas (dict): The image meta info.
rescale (bool): Rescale boundaries to the original image resolution
if true, and keep the score_maps resolution if false.
Returns:
dict: A dict where boundary results are stored in
``boundary_result``.
"""
assert check_argument.is_type_list(img_metas, dict)
assert isinstance(rescale, bool)
score_maps = score_maps.squeeze()
boundaries = decode(decoding_type=self.decoding_type,
preds=score_maps,
text_repr_type=self.text_repr_type)
if rescale:
boundaries = self.resize_boundary(
boundaries,
1.0 / self.downsample_ratio / img_metas[0]['scale_factor'])
results = dict(boundary_result=boundaries,
filename=img_metas[0]['filename'])
return results
def get_boundary(self, edges, scores, text_comps, img_metas, rescale):
"""Compute text boundaries via post processing.
Args:
edges (ndarray): The edge array of shape N * 2, each row is a pair
of text component indices that makes up an edge in graph.
scores (ndarray): The edge score array.
text_comps (ndarray): The text components.
img_metas (list[dict]): The image meta infos.
rescale (bool): Rescale boundaries to the original image
resolution.
Returns:
results (dict): The result dict.
"""
assert check_argument.is_type_list(img_metas, dict)
assert isinstance(rescale, bool)
boundaries = []
if edges is not None:
boundaries = decode(decoding_type='drrg',
edges=edges,
scores=scores,
text_comps=text_comps,
link_thr=self.link_thr)
if rescale:
boundaries = self.resize_boundary(
boundaries,
1.0 / self.downsample_ratio / img_metas[0]['scale_factor'])
results = dict(boundary_result=boundaries)
return results
def _get_boundary_single(self, score_map, scale):
assert len(score_map) == 2
assert score_map[1].shape[1] == 4 * self.fourier_degree + 2
return decode(decoding_type=self.decoding_type,
preds=score_map,
fourier_degree=self.fourier_degree,
num_reconstr_points=self.num_reconstr_points,
scale=scale,
alpha=self.alpha,
beta=self.beta,
text_repr_type='poly',
score_thr=self.score_thr,
nms_thr=self.nms_thr)