Coverage for /scratch/builds/bob/bob.ip.binseg/miniconda/conda-bld/bob.ip.binseg_1673966692152/_test_env_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_p/lib/python3.10/site-packages/bob/ip/common/test/test_iostar.py: 51%

1#!/usr/bin/env python 

2# coding=utf-8 

3 

4 

5"""Tests for IOSTAR""" 

6 

7import os 

8 

9import numpy 

10import pytest 

11 

12from ...binseg.data.iostar import dataset 

13from .utils import count_bw 

14 

15 

16def test_protocol_consistency(): 

17 

18 subset = dataset.subsets("vessel") 

19 assert len(subset) == 2 

20 

21 assert "train" in subset 

22 assert len(subset["train"]) == 20 

23 for s in subset["train"]: 

24 assert s.key.startswith(os.path.join("image", "STAR ")) 

25 

26 assert "test" in subset 

27 assert len(subset["test"]) == 10 

28 for s in subset["test"]: 

29 assert s.key.startswith(os.path.join("image", "STAR ")) 

30 

31 subset = dataset.subsets("optic-disc") 

32 assert len(subset) == 2 

33 

34 assert "train" in subset 

35 assert len(subset["train"]) == 20 

36 for s in subset["train"]: 

37 assert s.key.startswith(os.path.join("image", "STAR ")) 

38 

39 assert "test" in subset 

40 assert len(subset["test"]) == 10 

41 for s in subset["test"]: 

42 assert s.key.startswith(os.path.join("image", "STAR ")) 

43 

44 

45@pytest.mark.skip_if_rc_var_not_set("bob.ip.binseg.iostar.datadir") 

46def test_loading(): 

47 

48 image_size = (1024, 1024) 

49 

50 def _check_sample(s, bw_threshold_label, bw_threshold_mask): 

51 

52 data = s.data 

53 assert isinstance(data, dict) 

54 assert len(data) == 3 

55 

56 assert "data" in data 

57 assert data["data"].size == image_size 

58 assert data["data"].mode == "RGB" 

59 

60 assert "label" in data 

61 assert data["label"].size == image_size 

62 assert data["label"].mode == "1" 

63 b, w = count_bw(data["label"]) 

64 assert (b + w) == numpy.prod(image_size), ( 

65 f"Counts of black + white ({b}+{w}) do not add up to total " 

66 f"image size ({numpy.prod(image_size)}) at '{s.key}':label" 

67 ) 

68 assert (w / b) < bw_threshold_label, ( 

69 f"The proportion between black and white pixels " 

70 f"({w}/{b}={w/b:.2f}) is larger than the allowed threshold " 

71 f"of {bw_threshold_label} at '{s.key}':label - this could " 

72 f"indicate a loading problem!" 

73 ) 

74 

75 assert "mask" in data 

76 assert data["mask"].size == image_size 

77 assert data["mask"].mode == "1" 

78 bm, wm = count_bw(data["mask"]) 

79 assert (bm + wm) == numpy.prod(image_size), ( 

80 f"Counts of black + white ({bm}+{wm}) do not add up to total " 

81 f"image size ({numpy.prod(image_size)}) at '{s.key}':mask" 

82 ) 

83 assert (wm / bm) > bw_threshold_mask, ( 

84 f"The proportion between black and white pixels in masks " 

85 f"({wm}/{bm}={wm/bm:.2f}) is smaller than the allowed " 

86 f"threshold of {bw_threshold_mask} at '{s.key}':label - " 

87 f"this could indicate a loading problem!" 

88 ) 

89 

90 # to visualize images, uncomment the folowing code 

91 # it should display an image with a faded background representing the 

92 # original data, blended with green labels and blue area indicating the 

93 # parts to be masked out. 

94 # from ..data.utils import overlayed_image 

95 # display = overlayed_image(data["data"], data["label"], data["mask"]) 

96 # display.show() 

97 # import ipdb; ipdb.set_trace() 

98 

99 return w / b, wm / bm 

100 

101 limit = None # use this to limit testing to first images only 

102 subset = dataset.subsets("vessel") 

103 proportions = [ 

104 _check_sample(s, 0.11, 3.19) for s in subset["train"][:limit] 

105 ] 

106 # print(f"max label proportions = {max(k[0] for k in proportions)}") 

107 # print(f"min mask proportions = {min(k[1] for k in proportions)}") 

108 proportions = [_check_sample(s, 0.10, 3.27) for s in subset["test"][:limit]] 

109 # print(f"max label proportions = {max(k[0] for k in proportions)}") 

110 # print(f"min mask proportions = {min(k[1] for k in proportions)}") 

111 

112 subset = dataset.subsets("optic-disc") 

113 proportions = [ 

114 _check_sample(s, 0.023, 3.19) for s in subset["train"][:limit] 

115 ] 

116 # print(f"max label proportions = {max(k[0] for k in proportions)}") 

117 # print(f"min mask proportions = {min(k[1] for k in proportions)}") 

118 proportions = [ 

119 _check_sample(s, 0.033, 3.27) for s in subset["test"][:limit] 

120 ] 

121 # print(f"max label proportions = {max(k[0] for k in proportions)}") 

122 # print(f"min mask proportions = {min(k[1] for k in proportions)}") 

123 del proportions # only to satisfy flake8 

124 

125 

126@pytest.mark.skip_if_rc_var_not_set("bob.ip.binseg.iostar.datadir") 

127def test_check(): 

128 assert dataset.check() == 0