(self)
| 15 | cls.data_prefix = osp.join(osp.dirname(__file__), '../data') |
| 16 | |
| 17 | def test_load_img(self): |
| 18 | results = dict( |
| 19 | img_prefix=self.data_prefix, img_info=dict(filename='color.jpg')) |
| 20 | transform = LoadImageFromFile() |
| 21 | results = transform(copy.deepcopy(results)) |
| 22 | assert results['filename'] == osp.join(self.data_prefix, 'color.jpg') |
| 23 | assert results['ori_filename'] == 'color.jpg' |
| 24 | assert results['img'].shape == (288, 512, 3) |
| 25 | assert results['img'].dtype == np.uint8 |
| 26 | assert results['img_shape'] == (288, 512, 3) |
| 27 | assert results['ori_shape'] == (288, 512, 3) |
| 28 | assert results['pad_shape'] == (288, 512, 3) |
| 29 | assert results['scale_factor'] == 1.0 |
| 30 | np.testing.assert_equal(results['img_norm_cfg']['mean'], |
| 31 | np.zeros(3, dtype=np.float32)) |
| 32 | assert repr(transform) == transform.__class__.__name__ + \ |
| 33 | "(to_float32=False,color_type='color',imdecode_backend='cv2')" |
| 34 | |
| 35 | # no img_prefix |
| 36 | results = dict( |
| 37 | img_prefix=None, img_info=dict(filename='tests/data/color.jpg')) |
| 38 | transform = LoadImageFromFile() |
| 39 | results = transform(copy.deepcopy(results)) |
| 40 | assert results['filename'] == 'tests/data/color.jpg' |
| 41 | assert results['ori_filename'] == 'tests/data/color.jpg' |
| 42 | assert results['img'].shape == (288, 512, 3) |
| 43 | |
| 44 | # to_float32 |
| 45 | transform = LoadImageFromFile(to_float32=True) |
| 46 | results = transform(copy.deepcopy(results)) |
| 47 | assert results['img'].dtype == np.float32 |
| 48 | |
| 49 | # gray image |
| 50 | results = dict( |
| 51 | img_prefix=self.data_prefix, img_info=dict(filename='gray.jpg')) |
| 52 | transform = LoadImageFromFile() |
| 53 | results = transform(copy.deepcopy(results)) |
| 54 | assert results['img'].shape == (288, 512, 3) |
| 55 | assert results['img'].dtype == np.uint8 |
| 56 | |
| 57 | transform = LoadImageFromFile(color_type='unchanged') |
| 58 | results = transform(copy.deepcopy(results)) |
| 59 | assert results['img'].shape == (288, 512) |
| 60 | assert results['img'].dtype == np.uint8 |
| 61 | np.testing.assert_equal(results['img_norm_cfg']['mean'], |
| 62 | np.zeros(1, dtype=np.float32)) |
| 63 | |
| 64 | def test_load_seg(self): |
| 65 | results = dict( |
nothing calls this directly
no test coverage detected