diff options
Diffstat (limited to 'apps/CameraITS/tests/scene1/test_auto_vs_manual.py')
| -rw-r--r-- | apps/CameraITS/tests/scene1/test_auto_vs_manual.py | 95 |
1 files changed, 0 insertions, 95 deletions
diff --git a/apps/CameraITS/tests/scene1/test_auto_vs_manual.py b/apps/CameraITS/tests/scene1/test_auto_vs_manual.py deleted file mode 100644 index a9d5ce4..0000000 --- a/apps/CameraITS/tests/scene1/test_auto_vs_manual.py +++ /dev/null @@ -1,95 +0,0 @@ -# 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 math - -def main(): - """Capture auto and manual shots that should look the same. - - Manual shots taken with just manual WB, and also with manual WB+tonemap. - - In all cases, the general color/look of the shots should be the same, - however there can be variations in brightness/contrast due to different - "auto" ISP blocks that may be disabled in the manual flows. - """ - NAME = os.path.basename(__file__).split(".")[0] - - with its.device.ItsSession() as cam: - props = cam.get_camera_properties() - if (not its.caps.manual_sensor(props) or - not its.caps.manual_post_proc(props)): - print "Test skipped" - return - - # Converge 3A and get the estimates. - sens, exp, gains, xform, focus = cam.do_3a(get_results=True) - xform_rat = its.objects.float_to_rational(xform) - print "AE sensitivity %d, exposure %dms" % (sens, exp/1000000.0) - print "AWB gains", gains - print "AWB transform", xform - print "AF distance", focus - - # Auto capture. - req = its.objects.auto_capture_request() - cap_auto = cam.do_capture(req) - img_auto = its.image.convert_capture_to_rgb_image(cap_auto) - its.image.write_image(img_auto, "%s_auto.jpg" % (NAME)) - xform_a = its.objects.rational_to_float( - cap_auto["metadata"]["android.colorCorrection.transform"]) - gains_a = cap_auto["metadata"]["android.colorCorrection.gains"] - print "Auto gains:", gains_a - print "Auto transform:", xform_a - - # Manual capture 1: WB - req = its.objects.manual_capture_request(sens, exp) - req["android.colorCorrection.transform"] = xform_rat - req["android.colorCorrection.gains"] = gains - cap_man1 = cam.do_capture(req) - img_man1 = its.image.convert_capture_to_rgb_image(cap_man1) - its.image.write_image(img_man1, "%s_manual_wb.jpg" % (NAME)) - xform_m1 = its.objects.rational_to_float( - cap_man1["metadata"]["android.colorCorrection.transform"]) - gains_m1 = cap_man1["metadata"]["android.colorCorrection.gains"] - print "Manual wb gains:", gains_m1 - print "Manual wb transform:", xform_m1 - - # Manual capture 2: WB + tonemap - gamma = sum([[i/63.0,math.pow(i/63.0,1/2.2)] for i in xrange(64)],[]) - req["android.tonemap.mode"] = 0 - req["android.tonemap.curveRed"] = gamma - req["android.tonemap.curveGreen"] = gamma - req["android.tonemap.curveBlue"] = gamma - cap_man2 = cam.do_capture(req) - img_man2 = its.image.convert_capture_to_rgb_image(cap_man2) - its.image.write_image(img_man2, "%s_manual_wb_tm.jpg" % (NAME)) - xform_m2 = its.objects.rational_to_float( - cap_man2["metadata"]["android.colorCorrection.transform"]) - gains_m2 = cap_man2["metadata"]["android.colorCorrection.gains"] - print "Manual wb+tm gains:", gains_m2 - print "Manual wb+tm transform:", xform_m2 - - # Check that the WB gains and transform reported in each capture - # result match with the original AWB estimate from do_3a. - for g,x in [(gains_a,xform_a),(gains_m1,xform_m1),(gains_m2,xform_m2)]: - assert(all([abs(xform[i] - x[i]) < 0.05 for i in range(9)])) - assert(all([abs(gains[i] - g[i]) < 0.05 for i in range(4)])) - -if __name__ == '__main__': - main() - |