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- # Copyright (c) OpenMMLab. All rights reserved.
- import numpy as np
- from mmdet.datasets import CocoDataset
- from mmdet.visualization import get_palette, jitter_color, palette_val
- def test_palette():
- assert palette_val([(1, 2, 3)])[0] == (1 / 255, 2 / 255, 3 / 255)
- # test list
- palette = [(1, 0, 0), (0, 1, 0), (0, 0, 1)]
- palette_ = get_palette(palette, 3)
- for color, color_ in zip(palette, palette_):
- assert color == color_
- # test tuple
- palette = get_palette((1, 2, 3), 3)
- assert len(palette) == 3
- for color in palette:
- assert color == (1, 2, 3)
- # test color str
- palette = get_palette('red', 3)
- assert len(palette) == 3
- for color in palette:
- assert color == (255, 0, 0)
- # test dataset str
- palette = get_palette('coco', len(CocoDataset.METAINFO['classes']))
- assert len(palette) == len(CocoDataset.METAINFO['classes'])
- assert palette[0] == (220, 20, 60)
- # TODO: Awaiting refactoring
- # palette = get_palette('coco', len(CocoPanopticDataset.METAINFO['CLASSES'])) # noqa
- # assert len(palette) == len(CocoPanopticDataset.METAINFO['CLASSES'])
- # assert palette[-1] == (250, 141, 255)
- # palette = get_palette('voc', len(VOCDataset.METAINFO['CLASSES']))
- # assert len(palette) == len(VOCDataset.METAINFO['CLASSES'])
- # assert palette[0] == (106, 0, 228)
- # palette = get_palette('citys', len(CityscapesDataset.METAINFO['CLASSES'])) # noqa
- # assert len(palette) == len(CityscapesDataset.METAINFO['CLASSES'])
- # assert palette[0] == (220, 20, 60)
- # test random
- palette1 = get_palette('random', 3)
- palette2 = get_palette(None, 3)
- for color1, color2 in zip(palette1, palette2):
- assert isinstance(color1, tuple)
- assert isinstance(color2, tuple)
- assert color1 == color2
- def test_jitter_color():
- color = tuple(np.random.randint(0, 255, 3, np.uint8))
- jittered_color = jitter_color(color)
- for c in jittered_color:
- assert 0 <= c <= 255
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