# Copyright 2013 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 its.target import pylab import os.path import matplotlib import matplotlib.pyplot def main(): """Test that the android.sensor.sensitivity parameter is applied. """ NAME = os.path.basename(__file__).split(".")[0] NUM_STEPS = 5 sensitivities = None r_means = [] g_means = [] b_means = [] with its.device.ItsSession() as cam: props = cam.get_camera_properties() its.caps.skip_unless(its.caps.compute_target_exposure(props) and its.caps.per_frame_control(props)) expt,_ = its.target.get_target_exposure_combos(cam)["midSensitivity"] sens_range = props['android.sensor.info.sensitivityRange'] sens_step = (sens_range[1] - sens_range[0]) / float(NUM_STEPS-1) sensitivities = [sens_range[0] + i * sens_step for i in range(NUM_STEPS)] for s in sensitivities: req = its.objects.manual_capture_request(s, expt) cap = cam.do_capture(req) img = its.image.convert_capture_to_rgb_image(cap) its.image.write_image( img, "%s_iso=%04d.jpg" % (NAME, s)) tile = its.image.get_image_patch(img, 0.45, 0.45, 0.1, 0.1) rgb_means = its.image.compute_image_means(tile) r_means.append(rgb_means[0]) g_means.append(rgb_means[1]) b_means.append(rgb_means[2]) # Draw a plot. pylab.plot(sensitivities, r_means, 'r') pylab.plot(sensitivities, g_means, 'g') pylab.plot(sensitivities, b_means, 'b') pylab.ylim([0,1]) matplotlib.pyplot.savefig("%s_plot_means.png" % (NAME)) # Test for pass/fail: check that each shot is brighter than the previous. for means in [r_means, g_means, b_means]: for i in range(len(means)-1): assert(means[i+1] > means[i]) if __name__ == '__main__': main()