# 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 its.image import its.caps import its.device import its.objects import os.path import pylab import matplotlib import matplotlib.pyplot import numpy def main(): """Tests that EV compensation is applied. """ NAME = os.path.basename(__file__).split(".")[0] 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)) 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 = [] for ev in evs: # Re-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=ev, lock_ae=True, do_af=False) # 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 cap = cam.do_capture(req) y = its.image.convert_capture_to_planes(cap)[0] tile = its.image.get_image_patch(y, 0.45,0.45,0.1,0.1) lumas.append(its.image.compute_image_means(tile)[0]) pylab.plot(evs, lumas, 'r') matplotlib.pyplot.savefig("%s_plot_means.png" % (NAME)) # trim trailing 1.0s (for saturated image) while lumas and lumas[-1] == 1.0: lumas.pop(-1) # Only allow positive EVs to give saturated image assert(len(lumas) > 2) luma_diffs = numpy.diff(lumas) min_luma_diffs = min(luma_diffs) print "Min of the luma value difference between adjacent ev comp: ", \ min_luma_diffs # All luma brightness should be increasing with increasing ev comp. assert(min_luma_diffs > 0) if __name__ == '__main__': main()