Skip to content

GitLab

Switch branch/tag
Find file Normal viewHistoryPermalink
test_photometric.py 3.16 KB
Newer Older
Kai Chen's avatar
Refactor unittests (#241)  
Kai Chen committed
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77 
# Copyright (c) Open-MMLab. All rights reserved.
import os.path as osp

import cv2
import numpy as np
from numpy.testing import assert_array_equal

import mmcv


class TestPhotometric:

    @classmethod
    def setup_class(cls):
        # the test img resolution is 400x300
        cls.img_path = osp.join(osp.dirname(__file__), '../data/color.jpg')
        cls.img = cv2.imread(cls.img_path)
        cls.mean = np.array([123.675, 116.28, 103.53], dtype=np.float32)
        cls.std = np.array([58.395, 57.12, 57.375], dtype=np.float32)

    def test_imnormalize(self):
        rgb_img = self.img[:, :, ::-1]
        baseline = (rgb_img - self.mean) / self.std
        img = mmcv.imnormalize(self.img, self.mean, self.std)
        assert np.allclose(img, baseline)
        assert id(img) != id(self.img)
        img = mmcv.imnormalize(rgb_img, self.mean, self.std, to_rgb=False)
        assert np.allclose(img, baseline)
        assert id(img) != id(rgb_img)

    def test_imnormalize_(self):
        img_for_normalize = np.float32(self.img)
        rgb_img_for_normalize = np.float32(self.img[:, :, ::-1])
        baseline = (rgb_img_for_normalize - self.mean) / self.std
        img = mmcv.imnormalize_(img_for_normalize, self.mean, self.std)
        assert np.allclose(img_for_normalize, baseline)
        assert id(img) == id(img_for_normalize)
        img = mmcv.imnormalize_(
            rgb_img_for_normalize, self.mean, self.std, to_rgb=False)
        assert np.allclose(img, baseline)
        assert id(img) == id(rgb_img_for_normalize)

    def test_imdenormalize(self):
        norm_img = (self.img[:, :, ::-1] - self.mean) / self.std
        rgb_baseline = (norm_img * self.std + self.mean)
        bgr_baseline = rgb_baseline[:, :, ::-1]
        img = mmcv.imdenormalize(norm_img, self.mean, self.std)
        assert np.allclose(img, bgr_baseline)
        img = mmcv.imdenormalize(norm_img, self.mean, self.std, to_bgr=False)
        assert np.allclose(img, rgb_baseline)

    def test_iminvert(self):
        img = np.array([[0, 128, 255], [1, 127, 254], [2, 129, 253]],
                       dtype=np.uint8)
        img_r = np.array([[255, 127, 0], [254, 128, 1], [253, 126, 2]],
                         dtype=np.uint8)
        assert_array_equal(mmcv.iminvert(img), img_r)

    def test_solarize(self):
        img = np.array([[0, 128, 255], [1, 127, 254], [2, 129, 253]],
                       dtype=np.uint8)
        img_r = np.array([[0, 127, 0], [1, 127, 1], [2, 126, 2]],
                         dtype=np.uint8)
        assert_array_equal(mmcv.solarize(img), img_r)
        img_r = np.array([[0, 127, 0], [1, 128, 1], [2, 126, 2]],
                         dtype=np.uint8)
        assert_array_equal(mmcv.solarize(img, 100), img_r)

    def test_posterize(self):
        img = np.array([[0, 128, 255], [1, 127, 254], [2, 129, 253]],
                       dtype=np.uint8)
        img_r = np.array([[0, 128, 128], [0, 0, 128], [0, 128, 128]],
                         dtype=np.uint8)
        assert_array_equal(mmcv.posterize(img, 1), img_r)
        img_r = np.array([[0, 128, 224], [0, 96, 224], [0, 128, 224]],
                         dtype=np.uint8)
        assert_array_equal(mmcv.posterize(img, 3), img_r)