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_drive.py: 48%

1#!/usr/bin/env python 

2# coding=utf-8 

3 

4 

5"""Tests for DRIVE""" 

6 

7import os 

8 

9import numpy 

10import pytest 

11 

12from ...binseg.data.drive import dataset 

13from .utils import count_bw 

14 

15 

16def test_protocol_consistency(): 

17 

18 subset = dataset.subsets("default") 

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("training", "images")) 

25 

26 assert "test" in subset 

27 assert len(subset["test"]) == 20 

28 for s in subset["test"]: 

29 assert s.key.startswith(os.path.join("test", "images")) 

30 

31 subset = dataset.subsets("second-annotator") 

32 assert len(subset) == 1 

33 

34 assert "test" in subset 

35 assert len(subset["test"]) == 20 

36 for s in subset["test"]: 

37 assert s.key.startswith(os.path.join("test", "images")) 

38 

39 

40@pytest.mark.skip_if_rc_var_not_set("bob.ip.binseg.drive.datadir") 

41def test_loading(): 

42 

43 image_size = (565, 584) 

44 

45 def _check_sample(s, bw_threshold_label, bw_threshold_mask): 

46 

47 data = s.data 

48 assert isinstance(data, dict) 

49 assert len(data) == 3 

50 

51 assert "data" in data 

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

53 assert data["data"].mode == "RGB" 

54 

55 assert "label" in data 

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

57 assert data["label"].mode == "1" 

58 b, w = count_bw(data["label"]) 

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

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

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

62 ) 

63 assert (w / b) < bw_threshold_label, ( 

64 f"The proportion between black and white pixels in labels " 

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

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

67 f"indicate a loading problem!" 

68 ) 

69 

70 assert "mask" in data 

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

72 assert data["mask"].mode == "1" 

73 bm, wm = count_bw(data["mask"]) 

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

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

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

77 ) 

78 assert (wm / bm) > bw_threshold_mask, ( 

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

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

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

82 f"this could indicate a loading problem!" 

83 ) 

84 

85 # to visualize images, uncomment the folowing code 

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

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

88 # parts to be masked out. 

89 # from ..data.utils import overlayed_image 

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

91 # display.show() 

92 # import ipdb; ipdb.set_trace() 

93 

94 return w / b, wm / bm 

95 

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

97 subset = dataset.subsets("default") 

98 proportions = [ 

99 _check_sample(s, 0.14, 2.14) for s in subset["train"][:limit] 

100 ] 

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

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

103 proportions = [_check_sample(s, 0.12, 2.12) for s in subset["test"]][:limit] 

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

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

106 

107 subset = dataset.subsets("second-annotator") 

108 proportions = [_check_sample(s, 0.12, 2.12) 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 del proportions # only to satisfy flake8 

112 

113 

114@pytest.mark.skip_if_rc_var_not_set("bob.ip.binseg.drive.datadir") 

115def test_check(): 

116 assert dataset.check() == 0