1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
|
# Copyright 2014 The Android Open Source Project
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import its.image
import its.device
import its.objects
import its.target
import pylab
import os.path
import matplotlib
import matplotlib.pyplot
import copy
import numpy
def main():
"""Test that crop regions work.
"""
NAME = os.path.basename(__file__).split(".")[0]
# A list of 5 regions, specified in normalized (x,y,w,h) coords.
# The regions correspond to: TL, TR, BL, BR, CENT
REGIONS = [(0.0, 0.0, 0.5, 0.5),
(0.5, 0.0, 0.5, 0.5),
(0.0, 0.5, 0.5, 0.5),
(0.5, 0.5, 0.5, 0.5),
(0.25, 0.25, 0.5, 0.5)]
with its.device.ItsSession() as cam:
props = cam.get_camera_properties()
a = props['android.sensor.info.activeArraySize']
ax, ay = a["left"], a["top"]
aw, ah = a["right"] - a["left"], a["bottom"] - a["top"]
e, s = its.target.get_target_exposure_combos(cam)["minSensitivity"]
print "Active sensor region (%d,%d %dx%d)" % (ax, ay, aw, ah)
# Uses a 2x digital zoom.
assert(props['android.scaler.availableMaxDigitalZoom'] >= 2)
# Capture a full frame.
req = its.objects.manual_capture_request(s,e)
cap_full = cam.do_capture(req)
img_full = its.image.convert_capture_to_rgb_image(cap_full)
its.image.write_image(img_full, "%s_full.jpg" % (NAME))
wfull, hfull = cap_full["width"], cap_full["height"]
# Capture a burst of crop region frames.
# Note that each region is 1/2x1/2 of the full frame, and is digitally
# zoomed into the full size output image, so must be downscaled (below)
# by 2x when compared to a tile of the full image.
reqs = []
for x,y,w,h in REGIONS:
req = its.objects.manual_capture_request(s,e)
req["android.scaler.cropRegion"] = {
"top": int(ah * y),
"left": int(aw * x),
"right": int(aw * (x + w)),
"bottom": int(ah * (y + h))}
reqs.append(req)
caps_regions = cam.do_capture(reqs)
match_failed = False
for i,cap in enumerate(caps_regions):
a = cap["metadata"]["android.scaler.cropRegion"]
ax, ay = a["left"], a["top"]
aw, ah = a["right"] - a["left"], a["bottom"] - a["top"]
# Match this crop image against each of the five regions of
# the full image, to find the best match (which should be
# the region that corresponds to this crop image).
img_crop = its.image.convert_capture_to_rgb_image(cap)
img_crop = its.image.downscale_image(img_crop, 2)
its.image.write_image(img_crop, "%s_crop%d.jpg" % (NAME, i))
min_diff = None
min_diff_region = None
for j,(x,y,w,h) in enumerate(REGIONS):
tile_full = its.image.get_image_patch(img_full, x,y,w,h)
wtest = min(tile_full.shape[1], aw)
htest = min(tile_full.shape[0], ah)
tile_full = tile_full[0:htest:, 0:wtest:, ::]
tile_crop = img_crop[0:htest:, 0:wtest:, ::]
its.image.write_image(tile_full, "%s_fullregion%d.jpg"%(NAME,j))
diff = numpy.fabs(tile_full - tile_crop).mean()
if min_diff is None or diff < min_diff:
min_diff = diff
min_diff_region = j
if i != min_diff_region:
match_failed = True
print "Crop image %d (%d,%d %dx%d) best match with region %d"%(
i, ax, ay, aw, ah, min_diff_region)
assert(not match_failed)
if __name__ == '__main__':
main()
|
