1# Copyright 2014 The Android Open Source Project 2# 3# Licensed under the Apache License, Version 2.0 (the "License"); 4# you may not use this file except in compliance with the License. 5# You may obtain a copy of the License at 6# 7# http://www.apache.org/licenses/LICENSE-2.0 8# 9# Unless required by applicable law or agreed to in writing, software 10# distributed under the License is distributed on an "AS IS" BASIS, 11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12# See the License for the specific language governing permissions and 13# limitations under the License. 14 15import its.image 16import its.caps 17import its.device 18import its.objects 19import os.path 20import math 21 22def main(): 23 """Capture auto and manual shots that should look the same. 24 25 Manual shots taken with just manual WB, and also with manual WB+tonemap. 26 27 In all cases, the general color/look of the shots should be the same, 28 however there can be variations in brightness/contrast due to different 29 "auto" ISP blocks that may be disabled in the manual flows. 30 """ 31 NAME = os.path.basename(__file__).split(".")[0] 32 33 with its.device.ItsSession() as cam: 34 props = cam.get_camera_properties() 35 its.caps.skip_unless(its.caps.manual_sensor(props) and 36 its.caps.manual_post_proc(props) and 37 its.caps.per_frame_control(props)) 38 39 # Converge 3A and get the estimates. 40 debug = its.caps.debug_mode() 41 if debug: 42 fmt = its.objects.get_largest_yuv_format(props) 43 else: 44 fmt = its.objects.get_smallest_yuv_format(props) 45 sens, exp, gains, xform, focus = cam.do_3a(get_results=True) 46 xform_rat = its.objects.float_to_rational(xform) 47 print "AE sensitivity %d, exposure %dms" % (sens, exp/1000000.0) 48 print "AWB gains", gains 49 print "AWB transform", xform 50 print "AF distance", focus 51 52 # Auto capture. 53 req = its.objects.auto_capture_request() 54 cap_auto = cam.do_capture(req, fmt) 55 img_auto = its.image.convert_capture_to_rgb_image(cap_auto) 56 its.image.write_image(img_auto, "%s_auto.jpg" % (NAME)) 57 xform_a = its.objects.rational_to_float( 58 cap_auto["metadata"]["android.colorCorrection.transform"]) 59 gains_a = cap_auto["metadata"]["android.colorCorrection.gains"] 60 print "Auto gains:", gains_a 61 print "Auto transform:", xform_a 62 63 # Manual capture 1: WB 64 req = its.objects.manual_capture_request(sens, exp, focus) 65 req["android.colorCorrection.transform"] = xform_rat 66 req["android.colorCorrection.gains"] = gains 67 cap_man1 = cam.do_capture(req, fmt) 68 img_man1 = its.image.convert_capture_to_rgb_image(cap_man1) 69 its.image.write_image(img_man1, "%s_manual_wb.jpg" % (NAME)) 70 xform_m1 = its.objects.rational_to_float( 71 cap_man1["metadata"]["android.colorCorrection.transform"]) 72 gains_m1 = cap_man1["metadata"]["android.colorCorrection.gains"] 73 print "Manual wb gains:", gains_m1 74 print "Manual wb transform:", xform_m1 75 76 # Manual capture 2: WB + tonemap 77 gamma = sum([[i/63.0,math.pow(i/63.0,1/2.2)] for i in xrange(64)],[]) 78 req["android.tonemap.mode"] = 0 79 req["android.tonemap.curveRed"] = gamma 80 req["android.tonemap.curveGreen"] = gamma 81 req["android.tonemap.curveBlue"] = gamma 82 cap_man2 = cam.do_capture(req, fmt) 83 img_man2 = its.image.convert_capture_to_rgb_image(cap_man2) 84 its.image.write_image(img_man2, "%s_manual_wb_tm.jpg" % (NAME)) 85 xform_m2 = its.objects.rational_to_float( 86 cap_man2["metadata"]["android.colorCorrection.transform"]) 87 gains_m2 = cap_man2["metadata"]["android.colorCorrection.gains"] 88 print "Manual wb+tm gains:", gains_m2 89 print "Manual wb+tm transform:", xform_m2 90 91 # Check that the WB gains and transform reported in each capture 92 # result match with the original AWB estimate from do_3a. 93 for g,x in [(gains_a,xform_a),(gains_m1,xform_m1),(gains_m2,xform_m2)]: 94 assert(all([abs(xform[i] - x[i]) < 0.05 for i in range(9)])) 95 assert(all([abs(gains[i] - g[i]) < 0.05 for i in range(4)])) 96 97if __name__ == '__main__': 98 main() 99 100