| # Copyright 2014 The Android Open Source Project |
| # |
| # Licensed under the Apache License, Version 2.0 (the "License"); |
| # you may not use this file except in compliance with the License. |
| # You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an "AS IS" BASIS, |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| |
| import its.image |
| import its.caps |
| import its.device |
| import its.objects |
| import os.path |
| import numpy |
| |
| def main(): |
| """Test a sequence of shots with different tonemap curves. |
| """ |
| NAME = os.path.basename(__file__).split(".")[0] |
| |
| # There should be 3 identical frames followed by a different set of |
| # 3 identical frames. |
| MAX_SAME_DELTA = 0.01 |
| MIN_DIFF_DELTA = 0.10 |
| |
| with its.device.ItsSession() as cam: |
| props = cam.get_camera_properties() |
| its.caps.skip_unless(its.caps.manual_sensor(props) and |
| its.caps.manual_post_proc(props) and |
| its.caps.per_frame_control(props)) |
| |
| sens, exp_time, _,_,_ = cam.do_3a(do_af=False,get_results=True) |
| |
| means = [] |
| |
| # Capture 3 manual shots with a linear tonemap. |
| req = its.objects.manual_capture_request(sens, exp_time, True, props) |
| for i in [0,1,2]: |
| cap = cam.do_capture(req) |
| img = its.image.convert_capture_to_rgb_image(cap) |
| its.image.write_image(img, "%s_i=%d.jpg" % (NAME, i)) |
| tile = its.image.get_image_patch(img, 0.45, 0.45, 0.1, 0.1) |
| means.append(tile.mean(0).mean(0)) |
| |
| # Capture 3 manual shots with the default tonemap. |
| req = its.objects.manual_capture_request(sens, exp_time, False) |
| for i in [3,4,5]: |
| cap = cam.do_capture(req) |
| img = its.image.convert_capture_to_rgb_image(cap) |
| its.image.write_image(img, "%s_i=%d.jpg" % (NAME, i)) |
| tile = its.image.get_image_patch(img, 0.45, 0.45, 0.1, 0.1) |
| means.append(tile.mean(0).mean(0)) |
| |
| # Compute the delta between each consecutive frame pair. |
| deltas = [numpy.max(numpy.fabs(means[i+1]-means[i])) \ |
| for i in range(len(means)-1)] |
| print "Deltas between consecutive frames:", deltas |
| |
| assert(all([abs(deltas[i]) < MAX_SAME_DELTA for i in [0,1,3,4]])) |
| assert(abs(deltas[2]) > MIN_DIFF_DELTA) |
| |
| if __name__ == '__main__': |
| main() |
| |