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Fix sphinx/build_docs warnings for digital_image_processing
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digital_image_processing/filters/local_binary_pattern.py

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@@ -32,8 +32,7 @@ def local_binary_value(image: np.ndarray, x_coordinate: int, y_coordinate: int)
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:param image: the image to be processed
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:param x_coordinate: x coordinate of the pixel
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:param y_coordinate: the y coordinate of the pixel
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:return: The decimal value of the binary value of the pixels
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around the center pixel.
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:return: The decimal value of the binary value of the pixels around the center pixel.
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"""
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center = image[x_coordinate][y_coordinate]
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powers = [1, 2, 4, 8, 16, 32, 64, 128]

digital_image_processing/index_calculation.py

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@@ -11,7 +11,7 @@
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class IndexCalculation:
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"""
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# Class Summary
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This algorithm consists in calculating vegetation indices, these
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This algorithm consists in calculating vegetation indices, these
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indices can be used for precision agriculture for example (or remote
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sensing). There are functions to define the data and to calculate the
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implemented indices.
@@ -181,6 +181,7 @@ def arv12(self):
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"""
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Atmospherically Resistant Vegetation Index 2
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https://www.indexdatabase.de/db/i-single.php?id=396
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:return: index
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-0.18+1.17*(self.nir-self.red)/(self.nir+self.red)
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"""
@@ -225,7 +226,7 @@ def ndvi(self):
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def bndvi(self):
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"""
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Normalized Difference self.nir/self.blue self.blue-normalized difference
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Normalized Difference self.nir/self.blue self.blue-normalized difference
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vegetation index
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https://www.indexdatabase.de/db/i-single.php?id=135
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:return: index
@@ -474,7 +475,7 @@ def norm_r(self):
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def ngrdi(self):
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"""
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Normalized Difference self.green/self.red Normalized self.green self.red
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Normalized Difference self.green/self.red Normalized self.green self.red
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difference index, Visible Atmospherically Resistant Indices self.green
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(VIself.green)
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https://www.indexdatabase.de/db/i-single.php?id=390

digital_image_processing/morphological_operations/dilation_operation.py

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Original file line numberDiff line numberDiff line change
@@ -23,6 +23,7 @@ def rgb_to_gray(rgb: np.ndarray) -> np.ndarray:
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def gray_to_binary(gray: np.ndarray) -> np.ndarray:
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"""
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Return binary image from gray image
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>>> gray_to_binary(np.array([[127, 255, 0]]))
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array([[False, True, False]])
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>>> gray_to_binary(np.array([[0]]))

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