Source code for torchgeo.transforms.indices
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
"""TorchGeo indices transforms.
For more information about indices see the following references:
- https://www.indexdatabase.de/db/i.php
- https://github.com/davemlz/awesome-spectral-indices
"""
from typing import Dict
import torch
from torch import Tensor
from torch.nn.modules import Module
# https://github.com/pytorch/pytorch/issues/60979
# https://github.com/pytorch/pytorch/pull/61045
Module.__module__ = "torch.nn"
_EPSILON = 1e-10
class AppendNormalizedDifferenceIndex(Module):
"""Append normalized difference index as channel to image tensor.
.. versionadded:: 0.2
"""
[docs] def __init__(self, index_a: int, index_b: int) -> None:
"""Initialize a new transform instance.
Args:
index_a: reference band channel index
index_b: difference band channel index
"""
super().__init__()
self.dim = -3
self.index_a = index_a
self.index_b = index_b
def _compute_index(self, band_a: Tensor, band_b: Tensor) -> Tensor:
"""Compute normalized difference index.
Args:
band_a: reference band tensor
band_b: difference band tensor
Returns:
the index
"""
return (band_a - band_b) / ((band_a + band_b) + _EPSILON)
[docs] def forward(self, sample: Dict[str, Tensor]) -> Dict[str, Tensor]:
"""Compute and append normalized difference index to image.
Args:
sample: a sample or batch dict
Returns:
the transformed sample
"""
if "image" in sample:
index = self._compute_index(
band_a=sample["image"][..., self.index_a, :, :],
band_b=sample["image"][..., self.index_b, :, :],
)
index = index.unsqueeze(self.dim)
sample["image"] = torch.cat([sample["image"], index], dim=self.dim)
return sample
class AppendNBR(AppendNormalizedDifferenceIndex):
"""Normalized Burn Ratio (NBR).
If you use this index in your research, please cite the following paper:
* https://www.sciencebase.gov/catalog/item/4f4e4b20e4b07f02db6abb36
.. versionadded:: 0.2.0
"""
[docs] def __init__(self, index_nir: int, index_swir: int) -> None:
"""Initialize a new transform instance.
Args:
index_nir: index of the Near Infrared (NIR) band in the image
index_swir: index of the Short-wave Infrared (SWIR) band in the image
"""
super().__init__(index_a=index_nir, index_b=index_swir)
class AppendNDBI(AppendNormalizedDifferenceIndex):
"""Normalized Difference Built-up Index (NDBI).
If you use this index in your research, please cite the following paper:
* https://doi.org/10.1080/01431160304987
"""
[docs] def __init__(self, index_swir: int, index_nir: int) -> None:
"""Initialize a new transform instance.
Args:
index_swir: index of the Short-wave Infrared (SWIR) band in the image
index_nir: index of the Near Infrared (NIR) band in the image
"""
super().__init__(index_a=index_swir, index_b=index_nir)
class AppendNDSI(AppendNormalizedDifferenceIndex):
"""Normalized Difference Snow Index (NDSI).
If you use this index in your research, please cite the following paper:
* https://doi.org/10.1109/IGARSS.1994.399618
"""
[docs] def __init__(self, index_green: int, index_swir: int) -> None:
"""Initialize a new transform instance.
Args:
index_green: index of the Green band in the image
index_swir: index of the Short-wave Infrared (SWIR) band in the image
"""
super().__init__(index_a=index_green, index_b=index_swir)
class AppendNDVI(AppendNormalizedDifferenceIndex):
"""Normalized Difference Vegetation Index (NDVI).
If you use this index in your research, please cite the following paper:
* https://doi.org/10.1016/0034-4257(79)90013-0
"""
[docs] def __init__(self, index_red: int, index_nir: int) -> None:
"""Initialize a new transform instance.
Args:
index_red: index of the Red band in the image
index_nir: index of the Near Infrared (NIR) band in the image
"""
super().__init__(index_a=index_red, index_b=index_nir)
class AppendNDWI(AppendNormalizedDifferenceIndex):
"""Normalized Difference Water Index (NDWI).
If you use this index in your research, please cite the following paper:
* https://doi.org/10.1080/01431169608948714
"""
[docs] def __init__(self, index_green: int, index_nir: int) -> None:
"""Initialize a new transform instance.
Args:
index_green: index of the Green band in the image
index_nir: index of the Near Infrared (NIR) band in the image
"""
super().__init__(index_a=index_green, index_b=index_nir)
