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.caps
17import its.device
18import its.objects
19import its.target
20import os.path
21import numpy
22
23def main():
24    """Test that crop regions work.
25    """
26    NAME = os.path.basename(__file__).split(".")[0]
27
28    # A list of 5 regions, specified in normalized (x,y,w,h) coords.
29    # The regions correspond to: TL, TR, BL, BR, CENT
30    REGIONS = [(0.0, 0.0, 0.5, 0.5),
31               (0.5, 0.0, 0.5, 0.5),
32               (0.0, 0.5, 0.5, 0.5),
33               (0.5, 0.5, 0.5, 0.5),
34               (0.25, 0.25, 0.5, 0.5)]
35
36    with its.device.ItsSession() as cam:
37        props = cam.get_camera_properties()
38        its.caps.skip_unless(its.caps.compute_target_exposure(props) and
39                             its.caps.freeform_crop(props) and
40                             its.caps.per_frame_control(props))
41
42        a = props['android.sensor.info.activeArraySize']
43        ax, ay = a["left"], a["top"]
44        aw, ah = a["right"] - a["left"], a["bottom"] - a["top"]
45        e, s = its.target.get_target_exposure_combos(cam)["minSensitivity"]
46        print "Active sensor region (%d,%d %dx%d)" % (ax, ay, aw, ah)
47
48        # Uses a 2x digital zoom.
49        assert(its.objects.get_max_digital_zoom(props) >= 2)
50
51        # Capture a full frame.
52        req = its.objects.manual_capture_request(s,e)
53        cap_full = cam.do_capture(req)
54        img_full = its.image.convert_capture_to_rgb_image(cap_full)
55        its.image.write_image(img_full, "%s_full.jpg" % (NAME))
56        wfull, hfull = cap_full["width"], cap_full["height"]
57
58        # Capture a burst of crop region frames.
59        # Note that each region is 1/2x1/2 of the full frame, and is digitally
60        # zoomed into the full size output image, so must be downscaled (below)
61        # by 2x when compared to a tile of the full image.
62        reqs = []
63        for x,y,w,h in REGIONS:
64            req = its.objects.manual_capture_request(s,e)
65            req["android.scaler.cropRegion"] = {
66                    "top": int(ah * y),
67                    "left": int(aw * x),
68                    "right": int(aw * (x + w)),
69                    "bottom": int(ah * (y + h))}
70            reqs.append(req)
71        caps_regions = cam.do_capture(reqs)
72        match_failed = False
73        for i,cap in enumerate(caps_regions):
74            a = cap["metadata"]["android.scaler.cropRegion"]
75            ax, ay = a["left"], a["top"]
76            aw, ah = a["right"] - a["left"], a["bottom"] - a["top"]
77
78            # Match this crop image against each of the five regions of
79            # the full image, to find the best match (which should be
80            # the region that corresponds to this crop image).
81            img_crop = its.image.convert_capture_to_rgb_image(cap)
82            img_crop = its.image.downscale_image(img_crop, 2)
83            its.image.write_image(img_crop, "%s_crop%d.jpg" % (NAME, i))
84            min_diff = None
85            min_diff_region = None
86            for j,(x,y,w,h) in enumerate(REGIONS):
87                tile_full = its.image.get_image_patch(img_full, x,y,w,h)
88                wtest = min(tile_full.shape[1], aw)
89                htest = min(tile_full.shape[0], ah)
90                tile_full = tile_full[0:htest:, 0:wtest:, ::]
91                tile_crop = img_crop[0:htest:, 0:wtest:, ::]
92                its.image.write_image(tile_full, "%s_fullregion%d.jpg"%(NAME,j))
93                diff = numpy.fabs(tile_full - tile_crop).mean()
94                if min_diff is None or diff < min_diff:
95                    min_diff = diff
96                    min_diff_region = j
97            if i != min_diff_region:
98                match_failed = True
99            print "Crop image %d (%d,%d %dx%d) best match with region %d"%(
100                    i, ax, ay, aw, ah, min_diff_region)
101
102        assert(not match_failed)
103
104if __name__ == '__main__':
105    main()
106
107