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# Copyright 2013 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
def main():
"""Test that settings latch on the right frame.
Takes a bunch of shots using back-to-back requests, varying the capture
request parameters between shots. Checks that the images that come back
have the expexted properties.
"""
NAME = os.path.basename(__file__).split(".")[0]
with its.device.ItsSession() as cam:
props = cam.get_camera_properties()
_,fmt = its.objects.get_fastest_manual_capture_settings(props)
e, s = its.target.get_target_exposure_combos(cam)["midExposureTime"]
e = e / 2.0
r_means = []
g_means = []
b_means = []
reqs = [
its.objects.manual_capture_request(s, e, True),
its.objects.manual_capture_request(s, e, True),
its.objects.manual_capture_request(s*2,e, True),
its.objects.manual_capture_request(s*2,e, True),
its.objects.manual_capture_request(s, e, True),
its.objects.manual_capture_request(s, e, True),
its.objects.manual_capture_request(s, e*2, True),
its.objects.manual_capture_request(s, e, True),
its.objects.manual_capture_request(s*2,e, True),
its.objects.manual_capture_request(s, e, True),
its.objects.manual_capture_request(s, e*2, True),
its.objects.manual_capture_request(s, e, True),
its.objects.manual_capture_request(s, e*2, True),
its.objects.manual_capture_request(s, e*2, True),
]
caps = cam.do_capture(reqs, fmt)
for i,cap in enumerate(caps):
img = its.image.convert_capture_to_rgb_image(cap)
its.image.write_image(img, "%s_i=%02d.jpg" % (NAME, i))
tile = its.image.get_image_patch(img, 0.45, 0.45, 0.1, 0.1)
rgb_means = its.image.compute_image_means(tile)
r_means.append(rgb_means[0])
g_means.append(rgb_means[1])
b_means.append(rgb_means[2])
# Draw a plot.
idxs = range(len(r_means))
pylab.plot(idxs, r_means, 'r')
pylab.plot(idxs, g_means, 'g')
pylab.plot(idxs, b_means, 'b')
pylab.ylim([0,1])
matplotlib.pyplot.savefig("%s_plot_means.png" % (NAME))
g_avg = sum(g_means) / len(g_means)
g_ratios = [g / g_avg for g in g_means]
g_hilo = [g>1.0 for g in g_ratios]
assert(g_hilo == [False, False, True, True, False, False, True,
False, True, False, True, False, True, True])
if __name__ == '__main__':
main()
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