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1# MIT License 

2 

3# Copyright (c) 2024 Quentin Gabot 

4 

5# Permission is hereby granted, free of charge, to any person obtaining a copy 

6# of this software and associated documentation files (the "Software"), to deal 

7# in the Software without restriction, including without limitation the rights 

8# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 

9# copies of the Software, and to permit persons to whom the Software is 

10# furnished to do so, subject to the following conditions: 

11 

12# The above copyright notice and this permission notice shall be included in 

13# all copies or substantial portions of the Software. 

14 

15# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 

16# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 

17# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 

18# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 

19# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 

20# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 

21# SOFTWARE. 

22 

23# Standard imports 

24import pathlib 

25from typing import Tuple, Any 

26 

27# External imports 

28import numpy as np 

29from torch.utils.data import Dataset 

30from PIL import Image 

31 

32# Local imports 

33from .alos2 import ALOSDataset 

34 

35 

36class PolSFDataset(Dataset): 

37 r""" 

38 The Polarimetric SAR dataset with the labels provided by 

39 https://ietr-lab.univ-rennes1.fr/polsarpro-bio/san-francisco/ 

40 

41 We expect the data to be already downloaded and available on your drive. 

42 

43 Arguments: 

44 root: the top root dir where the data are expected 

45 transform : the transform applied the cropped image 

46 patch_size: the dimensions of the patches to consider (rows, cols) 

47 patch_stride: the shift between two consecutive patches, default:patch_size 

48 

49 Note: 

50 An example usage : 

51 

52 .. code-block:: python 

53 

54 import torchcvnn 

55 from torchcvnn.datasets import PolSFDataset 

56 

57 def transform_patches(patches): 

58 # We keep all the patches and get the spectrum 

59 # from it 

60 # If you wish, you could filter out some polarizations 

61 # PolSF provides the four HH, HV, VH, VV 

62 patches = [np.abs(patchi) for _, patchi in patches.items()] 

63 return np.stack(patches) 

64 

65 dataset = PolSFDataset(rootdir, patch_size=((512, 512)), transform=transform_patches 

66 X, y = dataset[0] 

67 

68 Displayed below are example patches with patch sizes :math:`512 \times 512` 

69 with the labels overlayed 

70 

71 .. figure:: ../assets/datasets/polsf.png 

72 :alt: Patches from the PolSF dataset 

73 :width: 100% 

74 :align: center 

75 

76 """ 

77 

78 """ 

79 Class names 

80 """ 

81 classes = [ 

82 "0 - unlabel", 

83 "1 - Montain", 

84 "2 - Water", 

85 "3 - Vegetation", 

86 "4 - High-Density Urban", 

87 "5 - Low-Density Urban", 

88 "6 - Developd", 

89 ] 

90 

91 def __init__( 

92 self, 

93 root: str, 

94 transform=None, 

95 patch_size: tuple = (128, 128), 

96 patch_stride: tuple = None, 

97 ): 

98 self.root = root 

99 

100 # alos2_url = "https://ietr-lab.univ-rennes1.fr/polsarpro-bio/san-francisco/dataset/SAN_FRANCISCO_ALOS2.zip" 

101 # labels_url = "https://raw.githubusercontent.com/liuxuvip/PolSF/master/SF-ALOS2/SF-ALOS2-label2d.png" 

102 

103 crop_coordinates = ((2832, 736), (7888, 3520)) 

104 root = pathlib.Path(root) / "VOL-ALOS2044980750-150324-HBQR1.1__A" 

105 self.alos_dataset = ALOSDataset( 

106 root, transform, crop_coordinates, patch_size, patch_stride 

107 ) 

108 if isinstance(root, str): 

109 root = pathlib.Path(root) 

110 self.labels = np.array(Image.open(root.parent / "SF-ALOS2-label2d.png"))[ 

111 ::-1, : 

112 ].copy() # copy necessary as otherwise torch.from_numpy does not support 

113 # negative stride 

114 

115 def __len__(self) -> int: 

116 """ 

117 Returns the total number of patches in the while image. 

118 

119 Returns: 

120 the total number of patches in the dataset 

121 """ 

122 return len(self.alos_dataset) 

123 

124 def __getitem__(self, idx) -> Tuple[Any, Any]: 

125 """ 

126 Returns the indexes patch. 

127 

128 Arguments: 

129 idx (int): Index 

130 

131 Returns: 

132 tuple: (patch, labels) where patch contains the 4 complex valued polarization HH, HV, VH, VV and labels contains the aligned semantic labels 

133 """ 

134 alos_patch = self.alos_dataset[idx] 

135 

136 row_stride, col_stride = self.alos_dataset.patch_stride 

137 start_row = (idx // self.alos_dataset.nsamples_per_cols) * row_stride 

138 

139 start_col = (idx % self.alos_dataset.nsamples_per_cols) * col_stride 

140 num_rows, num_cols = self.alos_dataset.patch_size 

141 labels = self.labels[ 

142 start_row : (start_row + num_rows), start_col : (start_col + num_cols) 

143 ] 

144 

145 return alos_patch, labels