# 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()