import numpy as np
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# Originally based on work by Frank and Even
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# Modified by Piero Toffanin for speed and lower memory usage
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# The code here is re-licensed under AGPLv3, but is based on MIT
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#******************************************************************************
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# Copyright (c) 2009, Frank Warmerdam
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# Copyright (c) 2010, Even Rouault <even dot rouault at mines-paris dot org>
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#
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# Permission is hereby granted, free of charge, to any person obtaining a
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# copy of this software and associated documentation files (the "Software"),
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# to deal in the Software without restriction, including without limitation
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# the rights to use, copy, modify, merge, publish, distribute, sublicense,
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# and/or sell copies of the Software, and to permit persons to whom the
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# Software is furnished to do so, subject to the following conditions:
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#
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# The above copyright notice and this permission notice shall be included
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# in all copies or substantial portions of the Software.
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#
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# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
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# OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
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# THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
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# DEALINGS IN THE SOFTWARE.
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#******************************************************************************
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# =============================================================================
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# rgb_to_hs()
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#
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# rgb comes in as [r,g,b] with values in the range [0,255]. The returned
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# hsv values will be with hue and saturation in the range [0,1]
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#
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def rgb_to_hs( r, g, b ):
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maxc = np.maximum(r,np.maximum(g,b))
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minc = np.minimum(r,np.minimum(g,b))
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# compute the difference, but reset zeros to ones to avoid divide by zeros later.
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maxc_minus_minc = maxc-minc
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s = np.divide(maxc_minus_minc, np.maximum(maxc, 1), dtype=np.float32)
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maxc_minus_minc[minc==maxc] = 1
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rc = np.divide((maxc-r), maxc_minus_minc, dtype=np.float32)
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gc = np.divide((maxc-g), maxc_minus_minc, dtype=np.float32)
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bc = np.divide((maxc-b), maxc_minus_minc, dtype=np.float32)
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maxc_minus_minc = None
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h = np.zeros((r.shape[0],r.shape[1]), dtype=np.float32)
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np.copyto(h, 4.0+gc-rc, where=(maxc == b))
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np.copyto(h, 2.0+rc-bc, where=(maxc==g))
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rc = None
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np.copyto(h, bc-gc, where=(maxc==r))
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np.divide(h, 6.0, out=h)
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np.mod(h, 1.0, out=h)
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return h, s
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# =============================================================================
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# hsv_to_rgb()
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#
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# hsv comes in as [h,s,v] with hue and saturation in the range [0,1],
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# but value in the range [0,255].
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def hsv_to_rgb( h, s, v ):
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np.multiply(h, 6.0, out=h)
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i = h.astype(np.uint8)
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np.subtract(h, i, out=h)
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q = v*(1.0 - s*h)
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t = v*(1.0 - s*(1.0-h))
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h = None
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p = v*(1.0 - s)
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r = np.zeros_like(v, dtype=np.uint8)
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g = np.zeros_like(v, dtype=np.uint8)
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b = np.zeros_like(v, dtype=np.uint8)
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idx = i==0
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np.copyto(r, v, where=idx, casting='unsafe')
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np.copyto(g, t, where=idx, casting='unsafe')
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np.copyto(b, p, where=idx, casting='unsafe')
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idx = i==1
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np.copyto(r, q, where=idx, casting='unsafe')
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np.copyto(g, v, where=idx, casting='unsafe')
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np.copyto(b, p, where=idx, casting='unsafe')
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idx = i==2
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np.copyto(r, p, where=idx, casting='unsafe')
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np.copyto(g, v, where=idx, casting='unsafe')
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np.copyto(b, t, where=idx, casting='unsafe')
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idx = i==3
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np.copyto(r, p, where=idx, casting='unsafe')
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np.copyto(g, q, where=idx, casting='unsafe')
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np.copyto(b, v, where=idx, casting='unsafe')
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idx = i==4
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np.copyto(r, t, where=idx, casting='unsafe')
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np.copyto(g, p, where=idx, casting='unsafe')
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np.copyto(b, v, where=idx, casting='unsafe')
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idx = i==5
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np.copyto(r, v, where=idx, casting='unsafe')
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np.copyto(g, p, where=idx, casting='unsafe')
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np.copyto(b, q, where=idx, casting='unsafe')
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return np.asarray([r,g,b])
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def hsv_blend(rgb, intensity):
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h, s = rgb_to_hs(rgb[0], rgb[1], rgb[2])
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#replace v with hillshade
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#convert back to RGB
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return hsv_to_rgb(h, s, intensity)
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