1# Copyright 2016 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.device 16import its.caps 17import its.image 18import its.objects 19import its.target 20import os.path 21from matplotlib import pylab 22import matplotlib 23import matplotlib.pyplot 24 25def main(): 26 """Capture a set of raw/yuv images with different 27 sensitivity/post Raw sensitivity boost combination 28 and check if the output pixel mean matches request settings 29 """ 30 NAME = os.path.basename(__file__).split(".")[0] 31 32 # Each raw image 33 RATIO_THRESHOLD = 0.1 34 # Waive the check if raw pixel value is below this level (signal too small 35 # that small black level error converts to huge error in percentage) 36 RAW_PIXEL_VAL_THRESHOLD = 0.03 37 38 with its.device.ItsSession() as cam: 39 props = cam.get_camera_properties() 40 its.caps.skip_unless(its.caps.raw_output(props) and 41 its.caps.post_raw_sensitivity_boost(props) and 42 its.caps.compute_target_exposure(props) and 43 its.caps.per_frame_control(props) and 44 not its.caps.mono_camera(props)) 45 46 w,h = its.objects.get_available_output_sizes( 47 "yuv", props, (1920, 1080))[0] 48 49 if its.caps.raw16(props): 50 raw_format = 'raw' 51 elif its.caps.raw10(props): 52 raw_format = 'raw10' 53 elif its.caps.raw12(props): 54 raw_format = 'raw12' 55 else: # should not reach here 56 raise its.error.Error('Cannot find available RAW output format') 57 58 out_surfaces = [{"format": raw_format}, 59 {"format": "yuv", "width": w, "height": h}] 60 61 sens_min, sens_max = props['android.sensor.info.sensitivityRange'] 62 sens_boost_min, sens_boost_max = \ 63 props['android.control.postRawSensitivityBoostRange'] 64 65 66 e_target, s_target = \ 67 its.target.get_target_exposure_combos(cam)["midSensitivity"] 68 69 reqs = [] 70 settings = [] 71 s_boost = sens_boost_min 72 while s_boost <= sens_boost_max: 73 s_raw = int(round(s_target * 100.0 / s_boost)) 74 if s_raw < sens_min or s_raw > sens_max: 75 break 76 req = its.objects.manual_capture_request(s_raw, e_target) 77 req['android.control.postRawSensitivityBoost'] = s_boost 78 reqs.append(req) 79 settings.append((s_raw, s_boost)) 80 if s_boost == sens_boost_max: 81 break 82 s_boost *= 2 83 # Always try to test maximum sensitivity boost value 84 if s_boost > sens_boost_max: 85 s_boost = sens_boost_max 86 87 caps = cam.do_capture(reqs, out_surfaces) 88 89 raw_rgb_means = [] 90 yuv_rgb_means = [] 91 raw_caps, yuv_caps = caps 92 if not isinstance(raw_caps, list): 93 raw_caps = [raw_caps] 94 if not isinstance(yuv_caps, list): 95 yuv_caps = [yuv_caps] 96 for i in xrange(len(reqs)): 97 (s, s_boost) = settings[i] 98 raw_cap = raw_caps[i] 99 yuv_cap = yuv_caps[i] 100 raw_rgb = its.image.convert_capture_to_rgb_image(raw_cap, props=props) 101 yuv_rgb = its.image.convert_capture_to_rgb_image(yuv_cap) 102 raw_tile = its.image.get_image_patch(raw_rgb, 0.45,0.45,0.1,0.1) 103 yuv_tile = its.image.get_image_patch(yuv_rgb, 0.45,0.45,0.1,0.1) 104 raw_rgb_means.append(its.image.compute_image_means(raw_tile)) 105 yuv_rgb_means.append(its.image.compute_image_means(yuv_tile)) 106 its.image.write_image(raw_tile, 107 "%s_raw_s=%04d_boost=%04d.jpg" % (NAME,s,s_boost)) 108 its.image.write_image(yuv_tile, 109 "%s_yuv_s=%04d_boost=%04d.jpg" % (NAME,s,s_boost)) 110 print "s=%d, s_boost=%d: raw_means %s, yuv_means %s"%( 111 s,s_boost,raw_rgb_means[-1], yuv_rgb_means[-1]) 112 113 xs = range(len(reqs)) 114 pylab.plot(xs, [rgb[0] for rgb in raw_rgb_means], 'r') 115 pylab.plot(xs, [rgb[1] for rgb in raw_rgb_means], 'g') 116 pylab.plot(xs, [rgb[2] for rgb in raw_rgb_means], 'b') 117 pylab.ylim([0,1]) 118 matplotlib.pyplot.savefig("%s_raw_plot_means.png" % (NAME)) 119 pylab.clf() 120 pylab.plot(xs, [rgb[0] for rgb in yuv_rgb_means], 'r') 121 pylab.plot(xs, [rgb[1] for rgb in yuv_rgb_means], 'g') 122 pylab.plot(xs, [rgb[2] for rgb in yuv_rgb_means], 'b') 123 pylab.ylim([0,1]) 124 matplotlib.pyplot.savefig("%s_yuv_plot_means.png" % (NAME)) 125 126 rgb_str = ["R", "G", "B"] 127 # Test that raw means is about 2x brighter than next step 128 for step in range(1, len(reqs)): 129 (s_prev, s_boost_prev) = settings[step - 1] 130 (s, s_boost) = settings[step] 131 expect_raw_ratio = s_prev / float(s) 132 raw_thres_min = expect_raw_ratio * (1 - RATIO_THRESHOLD) 133 raw_thres_max = expect_raw_ratio * (1 + RATIO_THRESHOLD) 134 for rgb in range(3): 135 ratio = raw_rgb_means[step - 1][rgb] / raw_rgb_means[step][rgb] 136 print ("Step (%d,%d) %s channel: %f, %f, ratio %f," + 137 " threshold_min %f, threshold_max %f") % ( 138 step-1, step, rgb_str[rgb], 139 raw_rgb_means[step - 1][rgb], 140 raw_rgb_means[step][rgb], 141 ratio, raw_thres_min, raw_thres_max) 142 if (raw_rgb_means[step][rgb] <= RAW_PIXEL_VAL_THRESHOLD): 143 continue 144 assert(raw_thres_min < ratio < raw_thres_max) 145 146 # Test that each yuv step is about the same bright as their mean 147 yuv_thres_min = 1 - RATIO_THRESHOLD 148 yuv_thres_max = 1 + RATIO_THRESHOLD 149 for rgb in range(3): 150 vals = [val[rgb] for val in yuv_rgb_means] 151 for step in range(len(reqs)): 152 if (raw_rgb_means[step][rgb] <= RAW_PIXEL_VAL_THRESHOLD): 153 vals = vals[:step] 154 mean = sum(vals) / len(vals) 155 print "%s channel vals %s mean %f"%(rgb_str[rgb], vals, mean) 156 for step in range(len(vals)): 157 ratio = vals[step] / mean 158 assert(yuv_thres_min < ratio < yuv_thres_max) 159 160if __name__ == '__main__': 161 main() 162