1# Copyright 2014 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.caps
18import its.objects
19import os.path
20import pylab
21import matplotlib
22import matplotlib.pyplot
23import numpy
24
25def main():
26    """Tests that EV compensation is applied.
27    """
28    NAME = os.path.basename(__file__).split(".")[0]
29
30    MAX_LUMA_DELTA_THRESH = 0.02
31
32    with its.device.ItsSession() as cam:
33        props = cam.get_camera_properties()
34        its.caps.skip_unless(its.caps.manual_sensor(props) and
35                             its.caps.manual_post_proc(props) and
36                             its.caps.per_frame_control(props) and
37                             its.caps.ev_compensation(props))
38
39        ev_compensation_range = props['android.control.aeCompensationRange']
40        range_min = ev_compensation_range[0]
41        range_max = ev_compensation_range[1]
42        ev_per_step = its.objects.rational_to_float(
43                props['android.control.aeCompensationStep'])
44        steps_per_ev = int(round(1.0 / ev_per_step))
45        ev_steps = range(range_min, range_max + 1, steps_per_ev)
46        imid = len(ev_steps) / 2
47        ev_shifts = [pow(2, step * ev_per_step) for step in ev_steps]
48        lumas = []
49        for ev in ev_steps:
50            # Re-converge 3A, and lock AE once converged. skip AF trigger as
51            # dark/bright scene could make AF convergence fail and this test
52            # doesn't care the image sharpness.
53            cam.do_3a(ev_comp=ev, lock_ae=True, do_af=False)
54
55            # Capture a single shot with the same EV comp and locked AE.
56            req = its.objects.auto_capture_request()
57            req['android.control.aeExposureCompensation'] = ev
58            req["android.control.aeLock"] = True
59            # Use linear tone curve to avoid brightness being impacted
60            # by tone curves.
61            req["android.tonemap.mode"] = 0
62            req["android.tonemap.curveRed"] = [0.0,0.0, 1.0,1.0]
63            req["android.tonemap.curveGreen"] = [0.0,0.0, 1.0,1.0]
64            req["android.tonemap.curveBlue"] = [0.0,0.0, 1.0,1.0]
65            cap = cam.do_capture(req)
66            y = its.image.convert_capture_to_planes(cap)[0]
67            tile = its.image.get_image_patch(y, 0.45,0.45,0.1,0.1)
68            lumas.append(its.image.compute_image_means(tile)[0])
69
70        print "ev_step_size_in_stops", ev_per_step
71        shift_mid = ev_shifts[imid]
72        luma_normal = lumas[imid] / shift_mid
73        expected_lumas = [luma_normal * ev_shift for ev_shift in ev_shifts]
74
75        pylab.plot(ev_steps, lumas, 'r')
76        pylab.plot(ev_steps, expected_lumas, 'b')
77        matplotlib.pyplot.savefig("%s_plot_means.png" % (NAME))
78
79        luma_diffs = [expected_lumas[i] - lumas[i] for i in range(len(ev_steps))]
80        max_diff = max(abs(i) for i in luma_diffs)
81        avg_diff = abs(numpy.array(luma_diffs)).mean()
82        print "Max delta between modeled and measured lumas:", max_diff
83        print "Avg delta between modeled and measured lumas:", avg_diff
84        assert(max_diff < MAX_LUMA_DELTA_THRESH)
85
86if __name__ == '__main__':
87    main()
88