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# 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.dng
import its.objects
import numpy
import os.path
def main():
"""Test that the DNG tags are internally self-consistent.
"""
NAME = os.path.basename(__file__).split(".")[0]
with its.device.ItsSession() as cam:
props = cam.get_camera_properties()
# Assumes that illuminant 1 is D65, and illuminant 2 is standard A.
# TODO: Generalize DNG tags check for any provided illuminants.
illum_code = [21, 17] # D65, A
illum_str = ['D65', 'A']
ref_str = ['android.sensor.referenceIlluminant%d'%(i) for i in [1,2]]
cm_str = ['android.sensor.colorTransform%d'%(i) for i in [1,2]]
fm_str = ['android.sensor.forwardMatrix%d'%(i) for i in [1,2]]
cal_str = ['android.sensor.calibrationTransform%d'%(i) for i in [1,2]]
dng_illum = [its.dng.D65, its.dng.A]
for i in [0,1]:
assert(props[ref_str[i]] == illum_code[i])
raw_input("\n[Point camera at grey card under %s and press ENTER]"%(
illum_str[i]))
cam.do_3a(do_af=False)
cap = cam.do_capture(its.objects.auto_capture_request())
gains = cap["metadata"]["android.colorCorrection.gains"]
ccm = its.objects.rational_to_float(
cap["metadata"]["android.colorCorrection.transform"])
cal = its.objects.rational_to_float(props[cal_str[i]])
print "HAL reported gains:\n", numpy.array(gains)
print "HAL reported ccm:\n", numpy.array(ccm).reshape(3,3)
print "HAL reported cal:\n", numpy.array(cal).reshape(3,3)
# Dump the image.
img = its.image.convert_capture_to_rgb_image(cap)
its.image.write_image(img, "%s_%s.jpg" % (NAME, illum_str[i]))
# Compute the matrices that are expected under this illuminant from
# the HAL-reported WB gains, CCM, and calibration matrix.
cm, fm = its.dng.compute_cm_fm(dng_illum[i], gains, ccm, cal)
asn = its.dng.compute_asn(dng_illum[i], cal, cm)
print "Expected ColorMatrix:\n", cm
print "Expected ForwardMatrix:\n", fm
print "Expected AsShotNeutral:\n", asn
# Get the matrices that are reported by the HAL for this
# illuminant.
cm_ref = numpy.array(its.objects.rational_to_float(
props[cm_str[i]])).reshape(3,3)
fm_ref = numpy.array(its.objects.rational_to_float(
props[fm_str[i]])).reshape(3,3)
asn_ref = numpy.array(its.objects.rational_to_float(
cap['metadata']['android.sensor.neutralColorPoint']))
print "Reported ColorMatrix:\n", cm_ref
print "Reported ForwardMatrix:\n", fm_ref
print "Reported AsShotNeutral:\n", asn_ref
# The color matrix may be scaled (between the reported and
# expected values).
cm_scale = cm.mean(1).mean(0) / cm_ref.mean(1).mean(0)
print "ColorMatrix scale factor:", cm_scale
# Compute the deltas between reported and expected.
print "Ratios in ColorMatrix:\n", cm / cm_ref
print "Deltas in ColorMatrix (after normalizing):\n", cm/cm_scale - cm_ref
print "Deltas in ForwardMatrix:\n", fm - fm_ref
print "Deltas in AsShotNeutral:\n", asn - asn_ref
# TODO: Add pass/fail test on DNG matrices.
if __name__ == '__main__':
main()
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