test_param_exposure_time.py revision 67b689684c4600930ccfa9cc7cec8d7a75b6ed7a 
1# Copyright 2013 The Android Open Source Project
2#
3# Licensed under the Apache License, Version 2.0 (the "License");
4# you may not use this file except in compliance with the License.
5# You may obtain a copy of the License at
6#
7#      http://www.apache.org/licenses/LICENSE-2.0
8#
9# Unless required by applicable law or agreed to in writing, software
10# distributed under the License is distributed on an "AS IS" BASIS,
11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12# See the License for the specific language governing permissions and
13# limitations under the License.
14
15import its.image
16import its.device
17import its.objects
18import pylab
19import os.path
20import matplotlib
21import matplotlib.pyplot
22
23def main():
24    """Test that the android.sensor.exposureTime parameter is applied.
25    """
26    NAME = os.path.basename(__file__).split(".")[0]
27
28    # Pass/fail thresholds.
29    THRESHOLD_MAX_MIN_DIFF = 0.3
30    THRESHOLD_MAX_MIN_RATIO = 2.0
31
32    req = its.objects.capture_request( {
33        "android.control.mode": 0,
34        "android.control.aeMode": 0,
35        "android.control.awbMode": 0,
36        "android.control.afMode": 0,
37        "android.sensor.frameDuration": 0,
38        "android.sensor.sensitivity": 200
39        })
40
41    exposures = range(1,101,20) # ms
42    r_means = []
43    g_means = []
44    b_means = []
45
46    with its.device.ItsSession() as cam:
47        for e in exposures:
48            req["captureRequest"]["android.sensor.exposureTime"] = e*1000*1000
49            fname, w, h, cap_md = cam.do_capture(req)
50            img = its.image.load_yuv420_to_rgb_image(fname, w, h)
51            its.image.write_image(
52                    img, "%s_time=%03dms.jpg" % (NAME, e))
53            tile = its.image.get_image_patch(img, 0.45, 0.45, 0.1, 0.1)
54            rgb_means = its.image.compute_image_means(tile)
55            r_means.append(rgb_means[0])
56            g_means.append(rgb_means[1])
57            b_means.append(rgb_means[2])
58
59    # Draw a plot.
60    pylab.plot(exposures, r_means, 'r')
61    pylab.plot(exposures, g_means, 'g')
62    pylab.plot(exposures, b_means, 'b')
63    pylab.ylim([0,1])
64    matplotlib.pyplot.savefig("%s_plot_means.png" % (NAME))
65
66    # Test for pass/fail: just check that that images get brighter by an amount
67    # that is more than could be expected by random noise. Don't assume the
68    # curve has any specific shape or gradient. This test is just checking that
69    # the sensitivity parameter actually does something. Note the intensity
70    # may be clamped to 0 or 1 for part of the ramp, so only test that the
71    # brightness difference between the first and last samples are above a
72    # given threshold.
73    for means in [r_means, g_means, b_means]:
74        for i in range(len(means)-1):
75            assert(means[i] <= means[i+1])
76        assert(means[-1] - means[0] > THRESHOLD_MAX_MIN_DIFF)
77        assert(means[-1] / means[0] > THRESHOLD_MAX_MIN_RATIO)
78
79if __name__ == '__main__':
80    main()
81
82