kopia lustrzana https://github.com/OpenDroneMap/ODM
96 wiersze
3.5 KiB
Python
96 wiersze
3.5 KiB
Python
#!/usr/bin/python
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# -*- coding: utf-8 -*-
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import rasterio, os, sys
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import numpy as np
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class bcolors:
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OKBLUE = '\033[94m'
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OKGREEN = '\033[92m'
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WARNING = '\033[93m'
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FAIL = '\033[91m'
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ENDC = '\033[0m'
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BOLD = '\033[1m'
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UNDERLINE = '\033[4m'
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try:
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file = sys.argv[1]
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typ = sys.argv[2]
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(fileRoot, fileExt) = os.path.splitext(file)
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outFileName = fileRoot + "_" + typ + fileExt
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if typ not in ['vari', 'tgi', 'ngrdi']:
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raise IndexError
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except (TypeError, IndexError, NameError):
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print bcolors.FAIL + 'Arguments messed up. Check arguments order and index name' + bcolors.ENDC
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print 'Usage: ./vegind.py orto index'
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print ' orto - filepath to RGB orthophoto'
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print ' index - Vegetation Index'
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print bcolors.OKGREEN + 'Available indexes: vari, ngrdi, tgi' + bcolors.ENDC
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sys.exit()
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def calcNgrdi(red, green):
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"""
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Normalized green red difference index
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Tucker,C.J.,1979.
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Red and photographic infrared linear combinations for monitoring vegetation.
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Remote Sensing of Environment 8, 127–150
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:param red: red visible channel
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:param green: green visible channel
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:return: ngrdi index array
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"""
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mask = np.not_equal(np.add(red,green), 0.0)
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return np.choose(mask, (-9999.0, np.true_divide(
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np.subtract(green,red),
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np.add(red,green))))
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def calcVari(red,green,blue):
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"""
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Calculates Visible Atmospheric Resistant Index
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Gitelson, A.A., Kaufman, Y.J., Stark, R., Rundquist, D., 2002.
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Novel algorithms for remote estimation of vegetation fraction.
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Remote Sensing of Environment 80, 76–87.
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:param red: red visible channel
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:param green: green visible channel
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:param blue: blue visible channel
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:return: vari index array, that will be saved to tiff
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"""
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mask = np.not_equal(np.subtract(np.add(green,red),blue), 0.0)
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return np.choose(mask, (-9999.0, np.true_divide(np.subtract(green,red),np.subtract(np.add(green,red),blue))))
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def calcTgi(red,green,blue):
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"""
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Calculates Triangular Greenness Index
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Hunt, E. Raymond Jr.; Doraiswamy, Paul C.; McMurtrey, James E.; Daughtry, Craig S.T.; Perry, Eileen M.; and Akhmedov, Bakhyt,
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A visible band index for remote sensing leaf chlorophyll content at the canopy scale (2013).
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Publications from USDA-ARS / UNL Faculty. Paper 1156.
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http://digitalcommons.unl.edu/usdaarsfacpub/1156
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:param red: red channel
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:param green: green channel
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:param blue: blue channel
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:return: tgi index array, that will be saved to tiff
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"""
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mask = np.not_equal(green-red+blue-255.0, 0.0)
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return np.choose(mask, (-9999.0, np.subtract(green, np.multiply(0.39,red), np.multiply(0.61, blue))))
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try:
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with rasterio.Env():
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ds = rasterio.open(file)
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profile = ds.profile
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profile.update(dtype=rasterio.float32, count=1, nodata=-9999)
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red = np.float32(ds.read(1))
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green = np.float32(ds.read(2))
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blue = np.float32(ds.read(3))
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np.seterr(divide='ignore', invalid='ignore')
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if typ == 'ngrdi':
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indeks = calcNgrdi(red,green)
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elif typ == 'vari':
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indeks = calcVari(red, green, blue)
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elif typ == 'tgi':
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indeks = calcTgi(red, green, blue)
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with rasterio.open(outFileName, 'w', **profile) as dst:
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dst.write(indeks.astype(rasterio.float32), 1)
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except rasterio.errors.RasterioIOError:
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print bcolors.FAIL + 'Orthophoto file not found or access denied' + bcolors.ENDC
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sys.exit()
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