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.caps
17import its.device
18import its.objects
19import its.target
20from matplotlib import pylab
21import os.path
22import matplotlib
23import matplotlib.pyplot
24
25def main():
26    """Test that the android.sensor.sensitivity parameter is applied.
27    """
28    NAME = os.path.basename(__file__).split(".")[0]
29
30    NUM_STEPS = 5
31
32    sensitivities = None
33    r_means = []
34    g_means = []
35    b_means = []
36
37    with its.device.ItsSession() as cam:
38        props = cam.get_camera_properties()
39        its.caps.skip_unless(its.caps.compute_target_exposure(props) and
40                             its.caps.per_frame_control(props))
41
42        debug = its.caps.debug_mode()
43        largest_yuv = its.objects.get_largest_yuv_format(props)
44        if debug:
45            fmt = largest_yuv
46        else:
47            match_ar = (largest_yuv['width'], largest_yuv['height'])
48            fmt = its.objects.get_smallest_yuv_format(props, match_ar=match_ar)
49
50        expt,_ = its.target.get_target_exposure_combos(cam)["midSensitivity"]
51        sens_range = props['android.sensor.info.sensitivityRange']
52        sens_step = (sens_range[1] - sens_range[0]) / float(NUM_STEPS-1)
53        sensitivities = [sens_range[0] + i * sens_step for i in range(NUM_STEPS)]
54
55        for s in sensitivities:
56            req = its.objects.manual_capture_request(s, expt)
57            cap = cam.do_capture(req, fmt)
58            img = its.image.convert_capture_to_rgb_image(cap)
59            its.image.write_image(
60                    img, "%s_iso=%04d.jpg" % (NAME, s))
61            tile = its.image.get_image_patch(img, 0.45, 0.45, 0.1, 0.1)
62            rgb_means = its.image.compute_image_means(tile)
63            r_means.append(rgb_means[0])
64            g_means.append(rgb_means[1])
65            b_means.append(rgb_means[2])
66
67    # Draw a plot.
68    pylab.plot(sensitivities, r_means, 'r')
69    pylab.plot(sensitivities, g_means, 'g')
70    pylab.plot(sensitivities, b_means, 'b')
71    pylab.ylim([0,1])
72    matplotlib.pyplot.savefig("%s_plot_means.png" % (NAME))
73
74    # Test for pass/fail: check that each shot is brighter than the previous.
75    for means in [r_means, g_means, b_means]:
76        for i in range(len(means)-1):
77            assert(means[i+1] > means[i])
78
79if __name__ == '__main__':
80    main()
81
82