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+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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+#
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+# Licensed under the Apache License, Version 2.0 (the "License");
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+# you may not use this file except in compliance with the License.
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+# You may obtain a copy of the License at
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+#
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+# http://www.apache.org/licenses/LICENSE-2.0
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+#
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+# Unless required by applicable law or agreed to in writing, software
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+# distributed under the License is distributed on an "AS IS" BASIS,
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+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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+# See the License for the specific language governing permissions and
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+# limitations under the License.
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+
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+# Refer to https://github.com/awesome-spectral-indices/awesome-spectral-indices .
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+# See LICENSE (https://github.com/awesome-spectral-indices/awesome-spectral-indices/blob/main/LICENSE).
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+
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+import abc
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+
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+__all__ = [
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+ 'ARI', 'ARI2', 'ARVI', 'AWEInsh', 'AWEIsh', 'BAI', 'BI', 'BLFEI', 'BNDVI',
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+ 'BWDRVI', 'BaI', 'CIG', 'CSI', 'CSIT', 'DBI', 'DBSI', 'DVI', 'EBBI', 'EMBI',
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+ 'EVI', 'EVI2', 'FCVI', 'GARI', 'GBNDVI', 'GLI', 'GNDVI', 'GRVI', 'IPVI',
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+ 'LSWI', 'MBI', 'MGRVI', 'MNDVI', 'MNDWI', 'MNLI', 'MSI', 'NBLI', 'NDSI',
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+ 'NDVI', 'NDWI', 'NDYI', 'NIRv', 'PSRI', 'RI', 'SAVI', 'SWI', 'TDVI', 'UI',
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+ 'VIG', 'WI1', 'WI2', 'WRI'
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+]
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+
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+EPS = 1e-32
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+
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+# | Band name | Description |
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+# |-----------|-------------|
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+# | b | Blue |
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+# | g | Green |
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+# | r | Red |
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+# | re1 | Red Edge 1 |
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+# | re2 | Red Edge 2 |
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+# | re3 | Red Edge 3 |
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+# | n | NIR |
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+# | n2 | NIR 2 |
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+# | s1 | SWIR 1 |
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+# | s2 | SWIR 2 |
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+# | t1 | Thermal 1 |
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+# | t2 | Thermal 2 |
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+
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+
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+class RSIndex(metaclass=abc.ABCMeta):
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+ def __init__(self, band_indices):
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+ super(RSIndex, self).__init__()
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+ self.band_indices = band_indices
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+
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+ @abc.abstractmethod
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+ def _compute(self, *args, **kwargs):
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+ pass
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+
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+ def __call__(self, image):
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+ bands = self.select_bands(image)
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+ return self._compute(**bands)
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+
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+ def select_bands(self, image, to_float32=True):
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+ bands = {}
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+ for name, idx in self.band_indices.items():
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+ if idx == 0:
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+ raise ValueError("Band index starts from 1.")
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+ bands[name] = image[..., idx - 1]
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+ if to_float32:
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+ bands[name] = bands[name].astype('float32')
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+ return bands
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+
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+
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+def compute_normalized_difference_index(band1, band2):
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+ return (band1 - band2) / (band1 + band2 + EPS)
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+
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+
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+class ARI(RSIndex):
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+ def _compute(self, g, re1):
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+ index = 1 / (g + EPS)
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+ index -= 1 / (re1 + EPS)
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+ return index
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+
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+
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+class ARI2(RSIndex):
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+ def _compute(self, g, re1, n):
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+ index = 1 / (g + EPS)
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+ index -= 1 / (re1 + EPS)
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+ index = index * n
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+ return index
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+
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+
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+class ARVI(RSIndex):
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+ def __init__(self, band_indices, c0):
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+ super(ARVI, self).__init__(band_indices)
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+ self.c0 = c0
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+
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+ def _compute(self, b, r, n):
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+ return compute_normalized_difference_index(n, r - self.c0 * (r - b))
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+
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+
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+class AWEInsh(RSIndex):
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+ def _compute(self, g, n, s1, s2):
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+ index = 4.0 * (g - s1)
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+ index -= 0.25 * n
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+ index += 2.75 * s2
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+ return index
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+
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+
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+class AWEIsh(RSIndex):
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+ def _compute(self, b, g, n, s1, s2):
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+ index = 2.5 * g
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+ index += b
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+ index -= 1.5 * (n + s1)
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+ index -= 0.25 * s2
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+ return index
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+
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+
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+class BAI(RSIndex):
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+ def _compute(self, r, n):
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+ index = (0.1 - r)**2.0
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+ index += (0.06 - n)**2.0
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+ return 1.0 / (index + EPS)
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+
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+
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+class BI(RSIndex):
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+ def _compute(self, b, r, n, s1):
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+ return compute_normalized_difference_index(s1 + r, n + b)
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+
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+
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+class BLFEI(RSIndex):
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+ def _compute(self, g, r, s1, s2):
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+ return compute_normalized_difference_index((g + r + s2) / 3.0, s1)
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+
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+
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+class BNDVI(RSIndex):
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+ def _compute(self, b, n):
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+ return compute_normalized_difference_index(n, b)
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+
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+
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+class BWDRVI(RSIndex):
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+ def __init__(self, band_indices, c0):
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+ super(BWDRVI, self).__init__(band_indices)
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+ self.c0 = c0
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+
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+ def _compute(self, b, n):
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+ return compute_normalized_difference_index(self.c0 * n, b)
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+
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+
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+class BaI(RSIndex):
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+ def _compute(self, r, n, s1):
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+ index = r + s1
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+ index -= n
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+ return index
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+
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+
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+class CIG(RSIndex):
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+ def _compute(self, g, n):
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+ index = n / (g + EPS)
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+ index -= 1.0
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+ return index
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+
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+
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+class CSI(RSIndex):
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+ def _compute(self, n, s2):
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+ return n / (s2 + EPS)
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+
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+
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+class CSIT(RSIndex):
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+ def _compute(self, n, s2, t1):
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+ return n / ((s2 * t1) / 10000.0 + EPS)
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+
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+
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+class DBI(RSIndex):
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+ def _compute(self, b, r, n, t1):
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+ index = (b - t1) / (b + t1 + EPS)
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+ index -= (n - r) / (n + r + EPS)
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+ return index
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+
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+
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+class DBSI(RSIndex):
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+ def _compute(self, g, r, n, s1):
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+ index = (s1 - g) / (s1 + g + EPS)
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+ index -= (n - r) / (n + r + EPS)
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+ return index
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+
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+
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+class DVI(RSIndex):
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+ def _compute(self, r, n):
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+ return n - r
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+
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+
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+class EBBI(RSIndex):
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+ def _compute(self, n, s1, t1):
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+ num = s1 - n
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+ denom = (10.0 * ((s1 + t1)**0.5))
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+ return num / (denom + EPS)
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+
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+
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+class EMBI(RSIndex):
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+ def _compute(self, g, n, s1, s2):
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+ item1 = compute_normalized_difference_index(s1, s2 + n)
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+ item1 += 0.5
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+ item2 = compute_normalized_difference_index(g, s1)
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+ return (item1 - item2 - 0.5) / (item1 + item2 + 1.5 + EPS)
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+
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+
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+class EVI(RSIndex):
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+ def __init__(self, band_indices, c0=2.5, c1=6, c2=7.5, c3=1):
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+ super(EVI, self).__init__(band_indices)
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+ self.c0 = c0
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+ self.c1 = c1
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+ self.c2 = c2
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+ self.c3 = c3
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+
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+ def _compute(self, b, r, n):
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+ num = self.c0 * (n - r)
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+ denom = n + self.c1 * r - self.c2 * b + self.c3
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+ return num / (denom + EPS)
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+
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+
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+class EVI2(RSIndex):
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+ def __init__(self, band_indices, c0, c1):
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+ super(EVI2, self).__init__(band_indices)
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+ self.c0 = c0
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+ self.c1 = c1
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+
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+ def _compute(self, n, r):
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+ num = self.c0 * (n - r)
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+ denom = n + 2.4 * r + self.c1
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+ return num / (denom + EPS)
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+
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+
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+class FCVI(RSIndex):
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+ def _compute(self, b, g, r, n):
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+ return n - ((r + g + b) / 3.0)
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+
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+
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+class GARI(RSIndex):
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+ def _compute(self, b, g, r, n):
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+ num = n - (g - (b - r))
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+ denom = n - (g + (b - r))
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+ return num / (denom + EPS)
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+
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+
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+class GBNDVI(RSIndex):
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+ def _compute(self, b, g, n):
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+ return compute_normalized_difference_index(n, g + b)
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+
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+
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+class GLI(RSIndex):
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+ def _compute(self, b, g, r):
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+ return compute_normalized_difference_index(2.0 * g, r + b)
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+
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+
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+class GNDVI(RSIndex):
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+ def _compute(self, g, n):
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+ return compute_normalized_difference_index(n, g)
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+
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+
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+class GRVI(RSIndex):
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+ def _compute(self, g, n):
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+ return n / (g + EPS)
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+
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+
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+class IPVI(RSIndex):
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+ def _compute(self, r, n):
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+ return n / (n + r + EPS)
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+
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+
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+class LSWI(RSIndex):
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+ def _compute(self, n, s1):
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+ return compute_normalized_difference_index(n, s1)
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+
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+
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+class MBI(RSIndex):
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+ def _compute(self, n, s1, s2):
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+ index = compute_normalized_difference_index(s1, s2 + n)
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+ index += 0.5
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+ return index
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+
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+
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+class MGRVI(RSIndex):
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+ def _compute(self, g, r):
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+ return compute_normalized_difference_index(g**2.0, r**2.0)
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+
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+
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+class MNDVI(RSIndex):
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+ def _compute(self, n, s2):
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+ return compute_normalized_difference_index(n, s2)
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+
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+
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+class MNDWI(RSIndex):
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+ def _compute(self, g, s1):
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+ return compute_normalized_difference_index(g, s1)
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+
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+
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+class MNLI(RSIndex):
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+ def __init__(self, band_indices, c0):
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+ super(MNLI, self).__init__(band_indices)
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+ self.c0 = c0
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+
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+ def _compute(self, r, n):
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+ num = (1 + self.c0) * ((n**2) - r)
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+ denom = ((n**2) + r + self.c0)
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+ return num / (denom + EPS)
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+
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+
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+class MSI(RSIndex):
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+ def _compute(self, n, s1):
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+ return s1 / (n + EPS)
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+
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+
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+class NBLI(RSIndex):
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+ def _compute(self, r, t1):
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+ return compute_normalized_difference_index(r, t1)
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+
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+
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+class NDSI(RSIndex):
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+ def _compute(self, g, s1):
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+ return compute_normalized_difference_index(g, s1)
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+
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+
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+class NDVI(RSIndex):
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+ def _compute(self, r, n):
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+ return compute_normalized_difference_index(n, r)
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+
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+
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+class NDWI(RSIndex):
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+ def _compute(self, g, n):
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+ return compute_normalized_difference_index(g, n)
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+
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+
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+class NDYI(RSIndex):
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+ def _compute(self, b, g):
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+ return compute_normalized_difference_index(g, b)
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+
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+
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+class NIRv(RSIndex):
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+ def _compute(self, r, n):
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+ return compute_normalized_difference_index(n, r) * n
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+
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+
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+class PSRI(RSIndex):
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+ def _compute(self, b, r, re2):
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+ return (r - b) / (re2 + EPS)
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+
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+
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+class RI(RSIndex):
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+ def _compute(self, g, r):
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+ return compute_normalized_difference_index(r, g)
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+
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+
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+class SAVI(RSIndex):
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+ def __init__(self, band_indices, c0):
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+ super(SAVI, self).__init__(band_indices)
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+ self.c0 = c0
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+
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+ def _compute(self, r, n):
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+ num = (1.0 + self.c0) * (n - r)
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+ denom = n + r + self.c0
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+ return num / (denom + EPS)
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+
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+
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+class SWI(RSIndex):
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+ def _compute(self, g, n, s1):
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+ num = g * (n - s1)
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+ denom = (g + n) * (n + s1)
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+ return num / (denom + EPS)
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+
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+
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+class TDVI(RSIndex):
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+ def _compute(self, r, n):
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+ num = 1.5 * (n - r)
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+ denom = (n**2.0 + r + 0.5)**0.5
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+ return num / (denom + EPS)
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+
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+
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+class UI(RSIndex):
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+ def _compute(self, n, s2):
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+ return compute_normalized_difference_index(s2, n)
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+
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+
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+class VIG(RSIndex):
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+ def _compute(self, g, r):
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+ return compute_normalized_difference_index(g, r)
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+
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+
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+class WI1(RSIndex):
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+ def _compute(self, g, s2):
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+ return compute_normalized_difference_index(g, s2)
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+
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+
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+class WI2(RSIndex):
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+ def _compute(self, b, s2):
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+ return compute_normalized_difference_index(b, s2)
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+
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+
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+class WRI(RSIndex):
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+ def _compute(self, g, r, n, s1):
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+ return (g + r) / (n + s1 + EPS)
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Lin Manhui