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# Copyright (c) OpenMMLab. All rights reserved.
from unittest import TestCase
import numpy as np
import torch
from mmengine.structures import LabelData
from mmocr.structures import TextRecogDataSample
class TestTextRecogDataSample(TestCase):
def test_init(self):
meta_info = dict(
img_size=[256, 256],
scale_factor=np.array([1.5, 1.5]),
img_shape=torch.rand(4))
recog_data_sample = TextRecogDataSample(metainfo=meta_info)
assert 'img_size' in recog_data_sample
self.assertListEqual(recog_data_sample.img_size, [256, 256])
self.assertListEqual(recog_data_sample.get('img_size'), [256, 256])
def test_setter(self):
recog_data_sample = TextRecogDataSample()
# test gt_text
gt_label_data = dict(item='mmocr')
gt_text = LabelData(**gt_label_data)
recog_data_sample.gt_text = gt_text
assert 'gt_text' in recog_data_sample
self.assertEqual(recog_data_sample.gt_text.item, gt_text.item)
# test pred_text
pred_label_data = dict(item='mmocr')
pred_text = LabelData(**pred_label_data)
recog_data_sample.pred_text = pred_text
assert 'pred_text' in recog_data_sample
self.assertEqual(recog_data_sample.pred_text.item, pred_text.item)
# test type error
with self.assertRaises(AssertionError):
recog_data_sample.gt_text = torch.rand(2, 4)
with self.assertRaises(AssertionError):
recog_data_sample.pred_text = torch.rand(2, 4)
def test_deleter(self):
recog_data_sample = TextRecogDataSample()
# test gt_text
gt_label_data = dict(item='mmocr')
gt_text = LabelData(**gt_label_data)
recog_data_sample.gt_text = gt_text
assert 'gt_text' in recog_data_sample
del recog_data_sample.gt_text
assert 'gt_text' not in recog_data_sample
recog_data_sample.pred_text = gt_text
assert 'pred_text' in recog_data_sample
del recog_data_sample.pred_text
assert 'pred_text' not in recog_data_sample
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