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
20import matplotlib
21import matplotlib.pyplot
22import numpy
23import os.path
24from matplotlib import pylab
25
26NR_MODES = [0, 1, 2, 3, 4]  # NR modes 0, 1, 2, 3, 4 with high gain
27
28
29def main():
30    """Test that the android.noiseReduction.mode param is applied when set.
31
32    Capture images with the camera dimly lit. Uses a high analog gain to
33    ensure the captured image is noisy.
34
35    Captures three images, for NR off, "fast", and "high quality".
36    Also captures an image with low gain and NR off, and uses the variance
37    of this as the baseline.
38    """
39    NAME = os.path.basename(__file__).split(".")[0]
40
41    NUM_SAMPLES_PER_MODE = 4
42    SNR_TOLERANCE = 3 # unit in db
43    # List of SNRs for R,G,B.
44    snrs = [[], [], []]
45
46    # Reference (baseline) SNR for each of R,G,B.
47    ref_snr = []
48
49    nr_modes_reported = []
50
51    with its.device.ItsSession() as cam:
52        props = cam.get_camera_properties()
53        its.caps.skip_unless(its.caps.compute_target_exposure(props) and
54                             its.caps.per_frame_control(props) and
55                             its.caps.noise_reduction_mode(props, 0))
56
57        # NR mode 0 with low gain
58        e, s = its.target.get_target_exposure_combos(cam)["minSensitivity"]
59        req = its.objects.manual_capture_request(s, e)
60        req["android.noiseReduction.mode"] = 0
61        cap = cam.do_capture(req)
62        rgb_image = its.image.convert_capture_to_rgb_image(cap)
63        its.image.write_image(
64                rgb_image,
65                "%s_low_gain.jpg" % (NAME))
66        rgb_tile = its.image.get_image_patch(rgb_image, 0.45, 0.45, 0.1, 0.1)
67        ref_snr = its.image.compute_image_snrs(rgb_tile)
68        print "Ref SNRs:", ref_snr
69
70        e, s = its.target.get_target_exposure_combos(cam)["maxSensitivity"]
71
72        for mode in NR_MODES:
73            # Skip unavailable modes
74            if not its.caps.noise_reduction_mode(props, mode):
75                nr_modes_reported.append(mode)
76                for channel in range(3):
77                    snrs[channel].append(0)
78                continue
79
80            rgb_snr_list = []
81            # Capture several images to account for per frame noise variations
82            for n in range(NUM_SAMPLES_PER_MODE):
83                req = its.objects.manual_capture_request(s, e)
84                req["android.noiseReduction.mode"] = mode
85                cap = cam.do_capture(req)
86                rgb_image = its.image.convert_capture_to_rgb_image(cap)
87                if n == 0:
88                    nr_modes_reported.append(
89                            cap["metadata"]["android.noiseReduction.mode"])
90                    its.image.write_image(
91                            rgb_image,
92                            "%s_high_gain_nr=%d.jpg" % (NAME, mode))
93                rgb_tile = its.image.get_image_patch(
94                        rgb_image, 0.45, 0.45, 0.1, 0.1)
95                rgb_snrs = its.image.compute_image_snrs(rgb_tile)
96                rgb_snr_list.append(rgb_snrs)
97
98            r_snrs = [rgb[0] for rgb in rgb_snr_list]
99            g_snrs = [rgb[1] for rgb in rgb_snr_list]
100            b_snrs = [rgb[2] for rgb in rgb_snr_list]
101            rgb_snrs = [numpy.mean(r_snrs), numpy.mean(g_snrs), numpy.mean(b_snrs)]
102            print "NR mode", mode, "SNRs:"
103            print "    R SNR:", rgb_snrs[0],\
104                    "Min:", min(r_snrs), "Max:", max(r_snrs)
105            print "    G SNR:", rgb_snrs[1],\
106                    "Min:", min(g_snrs), "Max:", max(g_snrs)
107            print "    B SNR:", rgb_snrs[2],\
108                    "Min:", min(b_snrs), "Max:", max(b_snrs)
109
110            for chan in range(3):
111                snrs[chan].append(rgb_snrs[chan])
112
113    # Draw a plot.
114    for j in range(3):
115        pylab.plot(NR_MODES, snrs[j], "-"+"rgb"[j]+"o")
116    pylab.xlabel("Noise Reduction Mode")
117    pylab.ylabel("SNR (dB)")
118    pylab.xticks(NR_MODES)
119    matplotlib.pyplot.savefig("%s_plot_SNRs.png" % (NAME))
120
121    assert nr_modes_reported == NR_MODES
122
123    for j in range(3):
124        # Larger SNR is better
125        # Verify OFF(0) is not better than FAST(1)
126        assert(snrs[j][0] <
127               snrs[j][1] + SNR_TOLERANCE)
128        # Verify FAST(1) is not better than HQ(2)
129        assert(snrs[j][1] <
130               snrs[j][2] + SNR_TOLERANCE)
131        # Verify HQ(2) is better than OFF(0)
132        assert(snrs[j][0] < snrs[j][2])
133        if its.caps.noise_reduction_mode(props, 3):
134            # Verify OFF(0) is not better than MINIMAL(3)
135            assert(snrs[j][0] <
136                   snrs[j][3] + SNR_TOLERANCE)
137            # Verify MINIMAL(3) is not better than HQ(2)
138            assert(snrs[j][3] <
139                   snrs[j][2] + SNR_TOLERANCE)
140            if its.caps.noise_reduction_mode(props, 4):
141                # Verify ZSL(4) is close to MINIMAL(3)
142                assert(numpy.isclose(snrs[j][4], snrs[j][3],
143                                     atol=SNR_TOLERANCE))
144        elif its.caps.noise_reduction_mode(props, 4):
145            # Verify ZSL(4) is close to OFF(0)
146            assert(numpy.isclose(snrs[j][4], snrs[j][0],
147                                 atol=SNR_TOLERANCE))
148
149if __name__ == '__main__':
150    main()
151
152