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.device 17import its.caps 18import its.objects 19import os.path 20from matplotlib import pylab 21import matplotlib 22import matplotlib.pyplot 23import numpy 24 25#AE must converge within this number of auto requests for EV 26THREASH_CONVERGE_FOR_EV = 8 27 28def main(): 29 """Tests that EV compensation is applied. 30 """ 31 LOCKED = 3 32 33 NAME = os.path.basename(__file__).split(".")[0] 34 35 MAX_LUMA_DELTA_THRESH = 0.05 36 37 with its.device.ItsSession() as cam: 38 props = cam.get_camera_properties() 39 its.caps.skip_unless(its.caps.manual_sensor(props) and 40 its.caps.manual_post_proc(props) and 41 its.caps.per_frame_control(props) and 42 its.caps.ev_compensation(props)) 43 44 mono_camera = its.caps.mono_camera(props) 45 debug = its.caps.debug_mode() 46 largest_yuv = its.objects.get_largest_yuv_format(props) 47 if debug: 48 fmt = largest_yuv 49 else: 50 match_ar = (largest_yuv['width'], largest_yuv['height']) 51 fmt = its.objects.get_smallest_yuv_format(props, match_ar=match_ar) 52 53 ev_compensation_range = props['android.control.aeCompensationRange'] 54 range_min = ev_compensation_range[0] 55 range_max = ev_compensation_range[1] 56 ev_per_step = its.objects.rational_to_float( 57 props['android.control.aeCompensationStep']) 58 steps_per_ev = int(round(1.0 / ev_per_step)) 59 ev_steps = range(range_min, range_max + 1, steps_per_ev) 60 imid = len(ev_steps) / 2 61 ev_shifts = [pow(2, step * ev_per_step) for step in ev_steps] 62 lumas = [] 63 64 # Converge 3A, and lock AE once converged. skip AF trigger as 65 # dark/bright scene could make AF convergence fail and this test 66 # doesn't care the image sharpness. 67 cam.do_3a(ev_comp=0, lock_ae=True, do_af=False, mono_camera=mono_camera) 68 69 for ev in ev_steps: 70 71 # Capture a single shot with the same EV comp and locked AE. 72 req = its.objects.auto_capture_request() 73 req['android.control.aeExposureCompensation'] = ev 74 req['android.control.aeLock'] = True 75 # Use linear tone curve to avoid brightness being impacted 76 # by tone curves. 77 req['android.tonemap.mode'] = 0 78 req['android.tonemap.curve'] = { 79 'red': [0.0,0.0, 1.0,1.0], 80 'green': [0.0,0.0, 1.0,1.0], 81 'blue': [0.0,0.0, 1.0,1.0]} 82 caps = cam.do_capture([req]*THREASH_CONVERGE_FOR_EV, fmt) 83 84 for cap in caps: 85 if (cap['metadata']['android.control.aeState'] == LOCKED): 86 y = its.image.convert_capture_to_planes(cap)[0] 87 tile = its.image.get_image_patch(y, 0.45,0.45,0.1,0.1) 88 lumas.append(its.image.compute_image_means(tile)[0]) 89 break 90 assert(cap['metadata']['android.control.aeState'] == LOCKED) 91 92 print "ev_step_size_in_stops", ev_per_step 93 shift_mid = ev_shifts[imid] 94 luma_normal = lumas[imid] / shift_mid 95 expected_lumas = [min(1.0, luma_normal * ev_shift) for ev_shift in ev_shifts] 96 97 pylab.plot(ev_steps, lumas, 'r') 98 pylab.plot(ev_steps, expected_lumas, 'b') 99 matplotlib.pyplot.savefig("%s_plot_means.png" % (NAME)) 100 101 luma_diffs = [expected_lumas[i] - lumas[i] for i in range(len(ev_steps))] 102 max_diff = max(abs(i) for i in luma_diffs) 103 avg_diff = abs(numpy.array(luma_diffs)).mean() 104 print "Max delta between modeled and measured lumas:", max_diff 105 print "Avg delta between modeled and measured lumas:", avg_diff 106 assert(max_diff < MAX_LUMA_DELTA_THRESH) 107 108if __name__ == '__main__': 109 main() 110