blob: 18ca506e388526fcbd05d418be171881b836f5f5 [file] [log] [blame]
# 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.caps
import its.device
import its.objects
import os.path
import numpy
def main():
"""Test a sequence of shots with different tonemap curves.
"""
NAME = os.path.basename(__file__).split(".")[0]
# There should be 3 identical frames followed by a different set of
# 3 identical frames.
MAX_SAME_DELTA = 0.01
MIN_DIFF_DELTA = 0.10
with its.device.ItsSession() as cam:
props = cam.get_camera_properties()
its.caps.skip_unless(its.caps.manual_sensor(props) and
its.caps.manual_post_proc(props) and
its.caps.per_frame_control(props))
sens, exp_time, _,_,_ = cam.do_3a(do_af=False,get_results=True)
means = []
# Capture 3 manual shots with a linear tonemap.
req = its.objects.manual_capture_request(sens, exp_time, True)
for i in [0,1,2]:
cap = cam.do_capture(req)
img = its.image.convert_capture_to_rgb_image(cap)
its.image.write_image(img, "%s_i=%d.jpg" % (NAME, i))
tile = its.image.get_image_patch(img, 0.45, 0.45, 0.1, 0.1)
means.append(tile.mean(0).mean(0))
# Capture 3 manual shots with the default tonemap.
req = its.objects.manual_capture_request(sens, exp_time, False)
for i in [3,4,5]:
cap = cam.do_capture(req)
img = its.image.convert_capture_to_rgb_image(cap)
its.image.write_image(img, "%s_i=%d.jpg" % (NAME, i))
tile = its.image.get_image_patch(img, 0.45, 0.45, 0.1, 0.1)
means.append(tile.mean(0).mean(0))
# Compute the delta between each consecutive frame pair.
deltas = [numpy.max(numpy.fabs(means[i+1]-means[i])) \
for i in range(len(means)-1)]
print "Deltas between consecutive frames:", deltas
assert(all([abs(deltas[i]) < MAX_SAME_DELTA for i in [0,1,3,4]]))
assert(abs(deltas[2]) > MIN_DIFF_DELTA)
if __name__ == '__main__':
main()