def test_db_decode():
pred = torch.zeros((1, 8, 8))
pred[0, 2:7, 2:7] = 0.8
expect_result_quad = [[
1.0, 8.0, 1.0, 1.0, 8.0, 1.0, 8.0, 8.0, 0.800000011920929
]]
expect_result_poly = [[
8, 2, 8, 6, 6, 8, 2, 8, 1, 6, 1, 2, 2, 1, 6, 1, 0.800000011920929
]]
with pytest.raises(ValueError):
db_decode(preds=pred, text_repr_type='dummpy')
result_quad = db_decode(
preds=pred, text_repr_type='quad', min_text_width=1)
result_poly = db_decode(
preds=pred, text_repr_type='poly', min_text_width=1)
assert result_quad == expect_result_quad
assert result_poly == expect_result_poly
def test_db_boxes_from_bitmaps():
"""Test the boxes_from_bitmaps function in db_decoder."""
pred = np.array([[[0.8, 0.8, 0.8, 0.8, 0], [0.8, 0.8, 0.8, 0.8, 0],
[0.8, 0.8, 0.8, 0.8, 0], [0.8, 0.8, 0.8, 0.8, 0],
[0.8, 0.8, 0.8, 0.8, 0]]])
preds = torch.FloatTensor(pred).requires_grad_(True)
boxes = db_decode(preds, text_repr_type='quad', min_text_width=0)
assert len(boxes) == 1
def test_db_boxes_from_bitmaps():
"""Test the boxes_from_bitmaps function in db_decoder."""
from mmocr.models.textdet.postprocess.wrapper import db_decode
pred = np.array([[[0.8, 0.8, 0.8, 0.8, 0], [0.8, 0.8, 0.8, 0.8, 0],
[0.8, 0.8, 0.8, 0.8, 0], [0.8, 0.8, 0.8, 0.8, 0],
[0.8, 0.8, 0.8, 0.8, 0]]])
preds = torch.FloatTensor(pred).requires_grad_(True)
boxes = db_decode(preds, text_repr_type='quad', min_text_width=0)
assert len(boxes) == 1