mmocr/tests/test_datasets/test_transforms/test_loading.py

137 lines
4.9 KiB
Python

# Copyright (c) OpenMMLab. All rights reserved.
import copy
from unittest import TestCase
import numpy as np
from mmocr.datasets.transforms import LoadKIEAnnotations, LoadOCRAnnotations
class TestLoadOCRAnnotations(TestCase):
def setUp(self):
self.results = {
'height':
288,
'width':
512,
'instances': [{
'bbox': [0, 0, 10, 20],
'bbox_label': 1,
'polygon': [0, 0, 0, 20, 10, 20, 10, 0],
'text': 'tmp1',
'ignore': False
}, {
'bbox': [10, 10, 110, 120],
'bbox_label': 2,
'polygon': [10, 10, 10, 120, 110, 120, 110, 10],
'text': 'tmp2',
'ignore': False
}, {
'bbox': [0, 0, 10, 20],
'bbox_label': 1,
'polygon': [0, 0, 0, 20, 10, 20, 10, 0],
'text': 'tmp3',
'ignore': True
}, {
'bbox': [10, 10, 110, 120],
'bbox_label': 2,
'polygon': [10, 10, 10, 120, 110, 120, 110, 10],
'text': 'tmp4',
'ignore': True
}]
}
def test_load_polygon(self):
transform = LoadOCRAnnotations(
with_bbox=False, with_label=False, with_polygon=True)
results = transform(copy.deepcopy(self.results))
self.assertIn('gt_polygons', results)
self.assertIsInstance(results['gt_polygons'], list)
self.assertEqual(len(results['gt_polygons']), 4)
for gt_polygon in results['gt_polygons']:
self.assertIsInstance(gt_polygon, np.ndarray)
self.assertEqual(gt_polygon.dtype, np.float32)
self.assertIn('gt_ignored', results)
self.assertEqual(results['gt_ignored'].dtype, np.bool_)
self.assertTrue((results['gt_ignored'],
np.array([False, False, True, True], dtype=np.bool_)))
def test_load_text(self):
transform = LoadOCRAnnotations(
with_bbox=False, with_label=False, with_text=True)
results = transform(copy.deepcopy(self.results))
self.assertIn('gt_texts', results)
self.assertListEqual(results['gt_texts'],
['tmp1', 'tmp2', 'tmp3', 'tmp4'])
def test_repr(self):
transform = LoadOCRAnnotations(
with_bbox=True, with_label=True, with_polygon=True, with_text=True)
self.assertEqual(
repr(transform),
('LoadOCRAnnotations(with_bbox=True, with_label=True, '
'with_polygon=True, with_text=True, '
"imdecode_backend='cv2', file_client_args={'backend': 'disk'})"))
class TestLoadKIEAnnotations(TestCase):
def setUp(self):
self.results = {
'bboxes': np.random.rand(2, 4).astype(np.float32),
'bbox_labels': np.random.randint(0, 10, (2, )),
'edge_labels': np.random.randint(0, 10, (2, 2)),
'texts': ['text1', 'text2'],
'ori_shape': (288, 512)
}
self.results = {
'img_shape': (288, 512),
'ori_shape': (288, 512),
'instances': [{
'bbox': [0, 0, 10, 20],
'bbox_label': 1,
'edge_label': 1,
'text': 'tmp1',
}, {
'bbox': [10, 10, 110, 120],
'bbox_label': 2,
'edge_label': 1,
'text': 'tmp2',
}]
}
self.load = LoadKIEAnnotations()
def test_transform(self):
results = self.load(copy.deepcopy(self.results))
self.assertIn('gt_bboxes', results)
self.assertIsInstance(results['gt_bboxes'], np.ndarray)
self.assertEqual(results['gt_bboxes'].shape, (2, 4))
self.assertEqual(results['gt_bboxes'].dtype, np.float32)
self.assertIn('gt_bboxes_labels', results)
self.assertIsInstance(results['gt_bboxes_labels'], np.ndarray)
self.assertEqual(results['gt_bboxes_labels'].shape, (2, ))
self.assertEqual(results['gt_bboxes_labels'].dtype, np.int64)
self.assertIn('gt_edges_labels', results)
self.assertIsInstance(results['gt_edges_labels'], np.ndarray)
self.assertEqual(results['gt_edges_labels'].shape, (2, 2))
self.assertEqual(results['gt_edges_labels'].dtype, np.int64)
self.assertIn('ori_shape', results)
self.assertEqual(results['ori_shape'], (288, 512))
load = LoadKIEAnnotations(key_node_idx=1, value_node_idx=2)
results = load(copy.deepcopy(self.results))
self.assertEqual(results['gt_edges_labels'][0, 1], 1)
self.assertEqual(results['gt_edges_labels'][1, 0], -1)
def test_repr(self):
self.assertEqual(
repr(self.load),
'LoadKIEAnnotations(with_bbox=True, with_label=True, '
'with_text=True)')