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.device
16import its.caps
17import its.objects
18import its.image
19import os.path
20import pylab
21import matplotlib
22import matplotlib.pyplot
23
24def main():
25    """Capture a set of raw images with increasing gains and measure the noise.
26
27    Capture raw-only, in a burst.
28    """
29    NAME = os.path.basename(__file__).split(".")[0]
30
31    # Each shot must be 1% noisier (by the variance metric) than the previous
32    # one.
33    VAR_THRESH = 1.01
34
35    NUM_STEPS = 5
36
37    with its.device.ItsSession() as cam:
38
39        props = cam.get_camera_properties()
40        its.caps.skip_unless(its.caps.raw16(props) and
41                             its.caps.manual_sensor(props) and
42                             its.caps.read_3a(props) and
43                             its.caps.per_frame_control(props))
44
45        # Expose for the scene with min sensitivity
46        sens_min, sens_max = props['android.sensor.info.sensitivityRange']
47        sens_step = (sens_max - sens_min) / NUM_STEPS
48        s_ae,e_ae,_,_,_  = cam.do_3a(get_results=True)
49        s_e_prod = s_ae * e_ae
50
51        reqs = []
52        settings = []
53        for s in range(sens_min, sens_max, sens_step):
54            e = int(s_e_prod / float(s))
55            req = its.objects.manual_capture_request(s, e)
56            reqs.append(req)
57            settings.append((s,e))
58
59        caps = cam.do_capture(reqs, cam.CAP_RAW)
60
61        variances = []
62        for i,cap in enumerate(caps):
63            (s,e) = settings[i]
64
65            # Measure the variance. Each shot should be noisier than the
66            # previous shot (as the gain is increasing).
67            plane = its.image.convert_capture_to_planes(cap, props)[1]
68            tile = its.image.get_image_patch(plane, 0.45,0.45,0.1,0.1)
69            var = its.image.compute_image_variances(tile)[0]
70            variances.append(var)
71
72            img = its.image.convert_capture_to_rgb_image(cap, props=props)
73            its.image.write_image(img, "%s_s=%05d_var=%f.jpg" % (NAME,s,var))
74            print "s=%d, e=%d, var=%e"%(s,e,var)
75
76        pylab.plot(range(len(variances)), variances)
77        matplotlib.pyplot.savefig("%s_variances.png" % (NAME))
78
79        # Test that each shot is noisier than the previous one.
80        for i in range(len(variances) - 1):
81            assert(variances[i] < variances[i+1] / VAR_THRESH)
82
83if __name__ == '__main__':
84    main()
85
86