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106 lines
3.8 KiB
106 lines
3.8 KiB
# Copyright 2013 The Android Open Source Project
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import its.image
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import its.device
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import its.objects
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from matplotlib import pylab
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import os.path
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import matplotlib
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import matplotlib.pyplot
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def main():
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"""Test that BLC and LSC look reasonable.
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"""
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NAME = os.path.basename(__file__).split(".")[0]
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r_means_center = []
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g_means_center = []
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b_means_center = []
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r_means_corner = []
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g_means_corner = []
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b_means_corner = []
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with its.device.ItsSession() as cam:
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props = cam.get_camera_properties()
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expt_range = props['android.sensor.info.exposureTimeRange']
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# Get AE+AWB lock first, so the auto values in the capture result are
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# populated properly.
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r = [[0,0,1,1,1]]
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ae_sen,ae_exp,awb_gains,awb_transform,_ \
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= cam.do_3a(r,r,r,do_af=False,get_results=True)
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print "AE:", ae_sen, ae_exp / 1000000.0
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print "AWB:", awb_gains, awb_transform
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# Set analog gain (sensitivity) to 800
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ae_exp = ae_exp * ae_sen / 800
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ae_sen = 800
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# Capture range of exposures from 1/100x to 4x of AE estimate.
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exposures = [ae_exp*x/100.0 for x in [1]+range(10,401,40)]
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exposures = [e for e in exposures
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if e >= expt_range[0] and e <= expt_range[1]]
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# Convert the transform back to rational.
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awb_transform_rat = its.objects.float_to_rational(awb_transform)
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# Linear tonemap
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tmap = sum([[i/63.0,i/63.0] for i in range(64)], [])
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reqs = []
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for e in exposures:
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req = its.objects.manual_capture_request(ae_sen,e)
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req["android.tonemap.mode"] = 0
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req["android.tonemap.curve"] = {
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"red": tmap, "green": tmap, "blue": tmap}
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req["android.colorCorrection.transform"] = awb_transform_rat
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req["android.colorCorrection.gains"] = awb_gains
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reqs.append(req)
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caps = cam.do_capture(reqs)
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for i,cap in enumerate(caps):
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img = its.image.convert_capture_to_rgb_image(cap)
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its.image.write_image(img, "%s_i=%d.jpg"%(NAME, i))
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tile_center = its.image.get_image_patch(img, 0.45, 0.45, 0.1, 0.1)
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rgb_means = its.image.compute_image_means(tile_center)
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r_means_center.append(rgb_means[0])
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g_means_center.append(rgb_means[1])
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b_means_center.append(rgb_means[2])
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tile_corner = its.image.get_image_patch(img, 0.0, 0.0, 0.1, 0.1)
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rgb_means = its.image.compute_image_means(tile_corner)
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r_means_corner.append(rgb_means[0])
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g_means_corner.append(rgb_means[1])
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b_means_corner.append(rgb_means[2])
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fig = matplotlib.pyplot.figure()
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pylab.plot(exposures, r_means_center, 'r')
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pylab.plot(exposures, g_means_center, 'g')
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pylab.plot(exposures, b_means_center, 'b')
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pylab.ylim([0,1])
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matplotlib.pyplot.savefig("%s_plot_means_center.png" % (NAME))
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fig = matplotlib.pyplot.figure()
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pylab.plot(exposures, r_means_corner, 'r')
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pylab.plot(exposures, g_means_corner, 'g')
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pylab.plot(exposures, b_means_corner, 'b')
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pylab.ylim([0,1])
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matplotlib.pyplot.savefig("%s_plot_means_corner.png" % (NAME))
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if __name__ == '__main__':
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main()
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