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smooth.py
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"""
***********************************************************************************************************************
BSD 3-Clause Clear License
Redistribution and use in source and binary forms, with or without
modification, are permitted (subject to the limitations in the disclaimer
below) provided that the following conditions are met:
* Redistributions of source code must retain the above copyright notice,
this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
* Neither the name of the copyright holder nor the names of its
contributors may be used to endorse or promote products derived from this
software without specific prior written permission.
NO EXPRESS OR IMPLIED LICENSES TO ANY PARTY'S PATENT RIGHTS ARE GRANTED BY
THIS LICENSE. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND
CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A
PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
POSSIBILITY OF SUCH DAMAGE.
Copyright (c) 2017-Demetris Marnerides, All rights reserved.
***********************************************************************************************************************
"""
"""
This is from the scipy smoothing demo
http://scipy-cookbook.readthedocs.io/items/SignalSmooth.html
window_len must be odd
"""
import numpy as np
def smooth(x, window_len=25, window='blackman'):
if x.ndim != 1:
raise ValueError("smooth only accepts 1 dimension arrays.")
if x.size < window_len:
raise ValueError("Input vector needs to be bigger than window size.")
if window_len<3:
return x
if not window in ['flat', 'hanning', 'hamming', 'bartlett', 'blackman']:
raise ValueError("Window is on of 'flat', 'hanning', 'hamming', 'bartlett', 'blackman'")
s=np.r_[x[window_len-1:0:-1],x,x[-2:-window_len-1:-1]]
if window == 'flat': #moving average
w=np.ones(window_len,'d')
else:
w=eval('np.'+window+'(window_len)')
y=np.convolve(w/w.sum(),s,mode='valid')
return y
# For smoothing the luminance precentile curves of video frames
def smoothen_luminance(predictions, percs):
percs = np.array(percs, dtype='float32').transpose()
smooth_percs = []
for i, perc in enumerate(percs):
smooth_percs.append(smooth(perc))
# smooth_low, smooth_high = smooth(np.array(low)), smooth(np.array(high))
ret = []
smooth_percs = np.array(smooth_percs).transpose()
percs = percs.transpose()
for i, pred in enumerate(predictions):
smooth_pred = np.interp(pred, percs[i], smooth_percs[i]).astype('float32')
ret.append(smooth_pred.clip(0,1))
return ret