| # 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.device |
| import its.objects |
| import pylab |
| import os.path |
| import matplotlib |
| import matplotlib.pyplot |
| |
| def main(): |
| """Test that the android.sensor.exposureTime parameter is applied. |
| """ |
| NAME = os.path.basename(__file__).split(".")[0] |
| |
| # Pass/fail thresholds. |
| THRESHOLD_MAX_MIN_DIFF = 0.3 |
| THRESHOLD_MAX_MIN_RATIO = 2.0 |
| |
| req = { |
| "android.control.mode": 0, |
| "android.control.aeMode": 0, |
| "android.control.awbMode": 0, |
| "android.control.afMode": 0, |
| "android.sensor.frameDuration": 0, |
| "android.sensor.sensitivity": 200 |
| } |
| |
| exposures = range(1,101,20) # ms |
| r_means = [] |
| g_means = [] |
| b_means = [] |
| |
| with its.device.ItsSession() as cam: |
| for e in exposures: |
| req["android.sensor.exposureTime"] = e*1000*1000 |
| fname, w, h, cap_md = cam.do_capture(req) |
| img = its.image.load_yuv420_to_rgb_image(fname, w, h) |
| its.image.write_image( |
| img, "%s_time=%03dms.jpg" % (NAME, e)) |
| 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(exposures, r_means, 'r') |
| pylab.plot(exposures, g_means, 'g') |
| pylab.plot(exposures, b_means, 'b') |
| pylab.ylim([0,1]) |
| matplotlib.pyplot.savefig("%s_plot_means.png" % (NAME)) |
| |
| # Test for pass/fail: just check that that images get brighter by an amount |
| # that is more than could be expected by random noise. Don't assume the |
| # curve has any specific shape or gradient. This test is just checking that |
| # the sensitivity parameter actually does something. Note the intensity |
| # may be clamped to 0 or 1 for part of the ramp, so only test that the |
| # brightness difference between the first and last samples are above a |
| # given threshold. |
| for means in [r_means, g_means, b_means]: |
| for i in range(len(means)-1): |
| assert(means[i] <= means[i+1]) |
| assert(means[-1] - means[0] > THRESHOLD_MAX_MIN_DIFF) |
| assert(means[-1] / means[0] > THRESHOLD_MAX_MIN_RATIO) |
| |
| if __name__ == '__main__': |
| main() |
| |