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# Copyright 2014 The Android Open Source Project
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os.path
import its.caps
import its.device
import its.image
import its.objects
import matplotlib
from matplotlib import pylab
import numpy as np
NAME = os.path.basename(__file__).split('.')[0]
LOCKED = 3
LUMA_LOCKED_TOL = 0.05
THRESH_CONVERGE_FOR_EV = 8 # AE must converge within this num
YUV_FULL_SCALE = 255.0
YUV_SAT_MIN = 250.0
YUV_SAT_TOL = 3.0
def main():
"""Tests that EV compensation is applied."""
with its.device.ItsSession() as cam:
props = cam.get_camera_properties()
its.caps.skip_unless(its.caps.ev_compensation(props) and
its.caps.ae_lock(props))
debug = its.caps.debug_mode()
mono_camera = its.caps.mono_camera(props)
largest_yuv = its.objects.get_largest_yuv_format(props)
if debug:
fmt = largest_yuv
else:
match_ar = (largest_yuv['width'], largest_yuv['height'])
fmt = its.objects.get_smallest_yuv_format(props, match_ar=match_ar)
ev_per_step = its.objects.rational_to_float(
props['android.control.aeCompensationStep'])
steps_per_ev = int(1.0 / ev_per_step)
evs = range(-2 * steps_per_ev, 2 * steps_per_ev + 1, steps_per_ev)
lumas = []
# Converge 3A, and lock AE once converged. skip AF trigger as
# dark/bright scene could make AF convergence fail and this test
# doesn't care the image sharpness.
cam.do_3a(ev_comp=0, lock_ae=True, do_af=False, mono_camera=mono_camera)
for ev in evs:
# Capture a single shot with the same EV comp and locked AE.
req = its.objects.auto_capture_request()
req['android.control.aeExposureCompensation'] = ev
req['android.control.aeLock'] = True
caps = cam.do_capture([req]*THRESH_CONVERGE_FOR_EV, fmt)
luma_locked = []
for i, cap in enumerate(caps):
if cap['metadata']['android.control.aeState'] == LOCKED:
y = its.image.convert_capture_to_planes(cap)[0]
tile = its.image.get_image_patch(y, 0.45, 0.45, 0.1, 0.1)
luma = its.image.compute_image_means(tile)[0]
luma_locked.append(luma)
if i == THRESH_CONVERGE_FOR_EV-1:
lumas.append(luma)
print 'lumas in AE locked captures: ', luma_locked
msg = 'AE locked lumas: %s, RTOL: %.2f' % (
str(luma_locked), LUMA_LOCKED_TOL)
assert np.isclose(min(luma_locked), max(luma_locked),
rtol=LUMA_LOCKED_TOL), msg
assert caps[THRESH_CONVERGE_FOR_EV-1]['metadata']['android.control.aeState'] == LOCKED
pylab.plot(evs, lumas, '-ro')
pylab.title(NAME)
pylab.xlabel('EV Compensation')
pylab.ylabel('Mean Luma (Normalized)')
matplotlib.pyplot.savefig('%s_plot_means.png' % (NAME))
# Trim extra saturated images
while (lumas[-2] >= YUV_SAT_MIN/YUV_FULL_SCALE and
lumas[-1] >= YUV_SAT_MIN/YUV_FULL_SCALE and
len(lumas) > 2):
lumas.pop(-1)
print 'Removed saturated image.'
# Only allow positive EVs to give saturated image
assert len(lumas) > 2, '3 or more unsaturated images needed'
min_luma_diffs = min(np.diff(lumas))
print 'Min of the luma value difference between adjacent ev comp: ',
print min_luma_diffs
# All luma brightness should be increasing with increasing ev comp.
assert min_luma_diffs > 0, 'Luma is not increasing!'
if __name__ == '__main__':
main()