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 os.path
16import its.caps
17import its.device
18import its.image
19import its.objects
20
21BURST_LEN = 8
22COLORS = ['R', 'G', 'B']
23FPS_MAX_DIFF = 2.0
24NAME = os.path.basename(__file__).split('.')[0]
25SPREAD_THRESH_MANUAL_SENSOR = 0.01
26SPREAD_THRESH = 0.03
27VALUE_THRESH = 0.1
28
29
30def main():
31    """Test 3A lock + YUV burst (using auto settings).
32
33    This is a test that is designed to pass even on limited devices that
34    don't have MANUAL_SENSOR or PER_FRAME_CONTROLS. The test checks
35    YUV image consistency while the frame rate check is in CTS.
36    """
37
38    with its.device.ItsSession() as cam:
39        props = cam.get_camera_properties()
40        its.caps.skip_unless(its.caps.ae_lock(props) and
41                             its.caps.awb_lock(props))
42        mono_camera = its.caps.mono_camera(props)
43
44        # Converge 3A prior to capture.
45        cam.do_3a(do_af=True, lock_ae=True, lock_awb=True,
46                  mono_camera=mono_camera)
47
48        fmt = its.objects.get_largest_yuv_format(props)
49
50        # After 3A has converged, lock AE+AWB for the duration of the test.
51        print 'Locking AE & AWB'
52        req = its.objects.fastest_auto_capture_request(props)
53        req['android.control.awbLock'] = True
54        req['android.control.aeLock'] = True
55
56        # Capture bursts of YUV shots.
57        # Get the mean values of a center patch for each.
58        r_means = []
59        g_means = []
60        b_means = []
61        caps = cam.do_capture([req]*BURST_LEN, fmt)
62        for i, cap in enumerate(caps):
63            img = its.image.convert_capture_to_rgb_image(cap)
64            its.image.write_image(img, '%s_frame%d.jpg'%(NAME, i))
65            tile = its.image.get_image_patch(img, 0.45, 0.45, 0.1, 0.1)
66            means = its.image.compute_image_means(tile)
67            r_means.append(means[0])
68            g_means.append(means[1])
69            b_means.append(means[2])
70
71        # Assert center patch brightness & similarity
72        for i, means in enumerate([r_means, g_means, b_means]):
73            plane = COLORS[i]
74            min_means = min(means)
75            spread = max(means) - min_means
76            print '%s patch mean spread %.5f. means = [' % (plane, spread),
77            for j in range(BURST_LEN):
78                print '%.5f' % means[j],
79            print ']'
80            e_msg = 'Image too dark!  %s: %.5f, THRESH: %.2f' % (
81                    plane, min_means, VALUE_THRESH)
82            assert min_means > VALUE_THRESH, e_msg
83            threshold = SPREAD_THRESH_MANUAL_SENSOR \
84                    if its.caps.manual_sensor(props) else SPREAD_THRESH
85            e_msg = '%s center patch spread: %.5f, THRESH: %.2f' % (
86                    plane, spread, threshold)
87            assert spread < threshold, e_msg
88
89if __name__ == '__main__':
90    main()
91
92