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 20import 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 debug = its.caps.debug_mode() 45 if debug: 46 fmt = its.objects.get_largest_yuv_format(props) 47 else: 48 fmt = its.objects.get_smallest_yuv_format(props) 49 50 ev_compensation_range = props['android.control.aeCompensationRange'] 51 range_min = ev_compensation_range[0] 52 range_max = ev_compensation_range[1] 53 ev_per_step = its.objects.rational_to_float( 54 props['android.control.aeCompensationStep']) 55 steps_per_ev = int(round(1.0 / ev_per_step)) 56 ev_steps = range(range_min, range_max + 1, steps_per_ev) 57 imid = len(ev_steps) / 2 58 ev_shifts = [pow(2, step * ev_per_step) for step in ev_steps] 59 lumas = [] 60 61 # Converge 3A, and lock AE once converged. skip AF trigger as 62 # dark/bright scene could make AF convergence fail and this test 63 # doesn't care the image sharpness. 64 cam.do_3a(ev_comp=0, lock_ae=True, do_af=False) 65 66 for ev in ev_steps: 67 68 # Capture a single shot with the same EV comp and locked AE. 69 req = its.objects.auto_capture_request() 70 req['android.control.aeExposureCompensation'] = ev 71 req["android.control.aeLock"] = True 72 # Use linear tone curve to avoid brightness being impacted 73 # by tone curves. 74 req["android.tonemap.mode"] = 0 75 req["android.tonemap.curveRed"] = [0.0,0.0, 1.0,1.0] 76 req["android.tonemap.curveGreen"] = [0.0,0.0, 1.0,1.0] 77 req["android.tonemap.curveBlue"] = [0.0,0.0, 1.0,1.0] 78 caps = cam.do_capture([req]*THREASH_CONVERGE_FOR_EV, fmt) 79 80 for cap in caps: 81 if (cap['metadata']['android.control.aeState'] == LOCKED): 82 y = its.image.convert_capture_to_planes(cap)[0] 83 tile = its.image.get_image_patch(y, 0.45,0.45,0.1,0.1) 84 lumas.append(its.image.compute_image_means(tile)[0]) 85 break 86 assert(cap['metadata']['android.control.aeState'] == LOCKED) 87 88 print "ev_step_size_in_stops", ev_per_step 89 shift_mid = ev_shifts[imid] 90 luma_normal = lumas[imid] / shift_mid 91 expected_lumas = [min(1.0, luma_normal * ev_shift) for ev_shift in ev_shifts] 92 93 pylab.plot(ev_steps, lumas, 'r') 94 pylab.plot(ev_steps, expected_lumas, 'b') 95 matplotlib.pyplot.savefig("%s_plot_means.png" % (NAME)) 96 97 luma_diffs = [expected_lumas[i] - lumas[i] for i in range(len(ev_steps))] 98 max_diff = max(abs(i) for i in luma_diffs) 99 avg_diff = abs(numpy.array(luma_diffs)).mean() 100 print "Max delta between modeled and measured lumas:", max_diff 101 print "Avg delta between modeled and measured lumas:", avg_diff 102 assert(max_diff < MAX_LUMA_DELTA_THRESH) 103 104if __name__ == '__main__': 105 main() 106