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 15 import its.image 16 import its.caps 17 import its.device 18 import its.objects 19 import os.path 20 import math 21 22 def 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 sens, exp, gains, xform, focus = cam.do_3a(get_results=True) 41 xform_rat = its.objects.float_to_rational(xform) 42 print "AE sensitivity %d, exposure %dms" % (sens, exp/1000000.0) 43 print "AWB gains", gains 44 print "AWB transform", xform 45 print "AF distance", focus 46 47 # Auto capture. 48 req = its.objects.auto_capture_request() 49 cap_auto = cam.do_capture(req) 50 img_auto = its.image.convert_capture_to_rgb_image(cap_auto) 51 its.image.write_image(img_auto, "%s_auto.jpg" % (NAME)) 52 xform_a = its.objects.rational_to_float( 53 cap_auto["metadata"]["android.colorCorrection.transform"]) 54 gains_a = cap_auto["metadata"]["android.colorCorrection.gains"] 55 print "Auto gains:", gains_a 56 print "Auto transform:", xform_a 57 58 # Manual capture 1: WB 59 req = its.objects.manual_capture_request(sens, exp) 60 req["android.colorCorrection.transform"] = xform_rat 61 req["android.colorCorrection.gains"] = gains 62 cap_man1 = cam.do_capture(req) 63 img_man1 = its.image.convert_capture_to_rgb_image(cap_man1) 64 its.image.write_image(img_man1, "%s_manual_wb.jpg" % (NAME)) 65 xform_m1 = its.objects.rational_to_float( 66 cap_man1["metadata"]["android.colorCorrection.transform"]) 67 gains_m1 = cap_man1["metadata"]["android.colorCorrection.gains"] 68 print "Manual wb gains:", gains_m1 69 print "Manual wb transform:", xform_m1 70 71 # Manual capture 2: WB + tonemap 72 gamma = sum([[i/63.0,math.pow(i/63.0,1/2.2)] for i in xrange(64)],[]) 73 req["android.tonemap.mode"] = 0 74 req["android.tonemap.curveRed"] = gamma 75 req["android.tonemap.curveGreen"] = gamma 76 req["android.tonemap.curveBlue"] = gamma 77 cap_man2 = cam.do_capture(req) 78 img_man2 = its.image.convert_capture_to_rgb_image(cap_man2) 79 its.image.write_image(img_man2, "%s_manual_wb_tm.jpg" % (NAME)) 80 xform_m2 = its.objects.rational_to_float( 81 cap_man2["metadata"]["android.colorCorrection.transform"]) 82 gains_m2 = cap_man2["metadata"]["android.colorCorrection.gains"] 83 print "Manual wb+tm gains:", gains_m2 84 print "Manual wb+tm transform:", xform_m2 85 86 # Check that the WB gains and transform reported in each capture 87 # result match with the original AWB estimate from do_3a. 88 for g,x in [(gains_a,xform_a),(gains_m1,xform_m1),(gains_m2,xform_m2)]: 89 assert(all([abs(xform[i] - x[i]) < 0.05 for i in range(9)])) 90 assert(all([abs(gains[i] - g[i]) < 0.05 for i in range(4)])) 91 92 if __name__ == '__main__': 93 main() 94 95
