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 os.path 16 import its.caps 17 import its.device 18 import its.image 19 import its.objects 20 import numpy 21 22 MAX_SAME_DELTA = 0.03 # match number in test_burst_sameness_manual 23 MIN_DIFF_DELTA = 0.10 24 NAME = os.path.basename(__file__).split(".")[0] 25 26 27 def main(): 28 """Test a sequence of shots with different tonemap curves. 29 30 There should be 3 identical frames followed by a different set of 31 3 identical frames. 32 """ 33 34 with its.device.ItsSession() as cam: 35 props = cam.get_camera_properties() 36 its.caps.skip_unless(its.caps.manual_sensor(props) and 37 its.caps.manual_post_proc(props) and 38 its.caps.per_frame_control(props) and 39 not its.caps.mono_camera(props)) 40 41 debug = its.caps.debug_mode() 42 largest_yuv = its.objects.get_largest_yuv_format(props) 43 if debug: 44 fmt = largest_yuv 45 else: 46 match_ar = (largest_yuv["width"], largest_yuv["height"]) 47 fmt = its.objects.get_smallest_yuv_format(props, match_ar=match_ar) 48 49 sens, exp_time, _, _, f_dist = cam.do_3a(do_af=True, get_results=True) 50 51 means = [] 52 53 # Capture 3 manual shots with a linear tonemap. 54 req = its.objects.manual_capture_request( 55 sens, exp_time, f_dist, True, props) 56 for i in [0, 1, 2]: 57 cap = cam.do_capture(req, fmt) 58 img = its.image.convert_capture_to_rgb_image(cap) 59 its.image.write_image(img, "%s_i=%d.jpg" % (NAME, i)) 60 tile = its.image.get_image_patch(img, 0.45, 0.45, 0.1, 0.1) 61 means.append(tile.mean(0).mean(0)) 62 63 # Capture 3 manual shots with the default tonemap. 64 req = its.objects.manual_capture_request(sens, exp_time, f_dist, False) 65 for i in [3, 4, 5]: 66 cap = cam.do_capture(req, fmt) 67 img = its.image.convert_capture_to_rgb_image(cap) 68 its.image.write_image(img, "%s_i=%d.jpg" % (NAME, i)) 69 tile = its.image.get_image_patch(img, 0.45, 0.45, 0.1, 0.1) 70 means.append(tile.mean(0).mean(0)) 71 72 # Compute the delta between each consecutive frame pair. 73 deltas = [numpy.max(numpy.fabs(means[i+1]-means[i])) \ 74 for i in range(len(means)-1)] 75 print "Deltas between consecutive frames:", deltas 76 77 msg = "deltas: %s, MAX_SAME_DELTA: %.2f" % ( 78 str(deltas), MAX_SAME_DELTA) 79 assert all([abs(deltas[i]) < MAX_SAME_DELTA for i in [0, 1, 3, 4]]), msg 80 assert abs(deltas[2]) > MIN_DIFF_DELTA, "delta: %.5f, THRESH: %.2f" % ( 81 abs(deltas[2]), MIN_DIFF_DELTA) 82 83 if __name__ == "__main__": 84 main() 85 86
