# Copyright 2016 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. """Verifies android.lens.state when lens is moving.""" import logging import os from mobly import test_runner import numpy as np import its_base_test import camera_properties_utils import capture_request_utils import image_processing_utils import its_session_utils import opencv_processing_utils FRAME_ATOL_MS = 10 MIN_AF_FD_TOL = 1.2 # AF value must < 1.2*min NAME = os.path.splitext(os.path.basename(__file__))[0] NUM_FRAMES_PER_FD = 12 POSITION_RTOL = 0.10 # 10% SHARPNESS_RTOL = 0.10 # 10% START_FRAME = 1 # start on second frame VGA_WIDTH, VGA_HEIGHT = 640, 480 def take_caps_and_determine_sharpness( cam, props, fmt, gain, exp, af_fd, chart, log_path): """Return fd, sharpness, lens state of the output images. Args: cam: An open device session. props: Properties of cam fmt: dict; capture format gain: Sensitivity for the request as defined in android.sensor.sensitivity exp: Exposure time for the request as defined in android.sensor.exposureTime af_fd: Focus distance for the request as defined in android.lens.focusDistance chart: Object that contains chart information log_path: log_path to save the captured image Returns: Object containing reported sharpness of the output image, keyed by the following string: 'sharpness' """ # initialize variables and take data sets data_set = {} white_level = int(props['android.sensor.info.whiteLevel']) min_fd = props['android.lens.info.minimumFocusDistance'] fds = [af_fd] * NUM_FRAMES_PER_FD + [min_fd] * NUM_FRAMES_PER_FD reqs = [] for i, fd in enumerate(fds): reqs.append(capture_request_utils.manual_capture_request(gain, exp)) reqs[i]['android.lens.focusDistance'] = fd caps = cam.do_capture(reqs, fmt) caps = caps[START_FRAME:] for i, cap in enumerate(caps): data = {'fd': fds[i+START_FRAME]} data['loc'] = cap['metadata']['android.lens.focusDistance'] data['lens_moving'] = (cap['metadata']['android.lens.state'] == 1) timestamp = cap['metadata']['android.sensor.timestamp'] * 1E-6 if i == 0: timestamp_init = timestamp timestamp -= timestamp_init data['timestamp'] = timestamp y, _, _ = image_processing_utils.convert_capture_to_planes(cap, props) chart.img = image_processing_utils.normalize_img( image_processing_utils.get_image_patch( y, chart.xnorm, chart.ynorm, chart.wnorm, chart.hnorm)) img_name = '%s_i=%d.jpg' % (os.path.join(log_path, NAME), i) image_processing_utils.write_image(chart.img, img_name) data['sharpness'] = ( white_level * image_processing_utils.compute_image_sharpness(chart.img)) data_set[i] = data return data_set class LensMovementReportingTest(its_base_test.ItsBaseTest): """Test if focus distance is properly reported. Do unit step of focus distance and check sharpness correlates. """ def test_lens_movement_reporting(self): logging.debug('Starting %s', NAME) with its_session_utils.ItsSession( device_id=self.dut.serial, camera_id=self.camera_id, hidden_physical_id=self.hidden_physical_id) as cam: chart_loc_arg = self.chart_loc_arg props = cam.get_camera_properties() props = cam.override_with_hidden_physical_camera_props(props) # Check skip conditions camera_properties_utils.skip_unless( not camera_properties_utils.fixed_focus(props) and camera_properties_utils.read_3a(props) and camera_properties_utils.lens_approx_calibrated(props)) # Calculate camera_fov and load scaled image on tablet. its_session_utils.load_scene( cam, props, self.scene, self.tablet, self.chart_distance) # Initialize chart class and locate chart in scene chart = opencv_processing_utils.Chart( cam, props, self.log_path, chart_loc=chart_loc_arg) # Get proper sensitivity, exposure time, and focus distance with 3A. mono_camera = camera_properties_utils.mono_camera(props) s, e, _, _, af_fd = cam.do_3a(get_results=True, mono_camera=mono_camera) # Get sharpness for each focal distance fmt = {'format': 'yuv', 'width': VGA_WIDTH, 'height': VGA_HEIGHT} d = take_caps_and_determine_sharpness( cam, props, fmt, s, e, af_fd, chart, self.log_path) for k in sorted(d): logging.debug( 'i: %d\tfd: %.3f\tlens location (diopters): %.3f \t' 'sharpness: %.1f \tlens_moving: %r \t' 'timestamp: %.1fms', k, d[k]['fd'], d[k]['loc'], d[k]['sharpness'], d[k]['lens_moving'], d[k]['timestamp']) # Assert frames are consecutive frame_diffs = np.gradient([v['timestamp'] for v in d.values()]) delta_diffs = np.amax(frame_diffs) - np.amin(frame_diffs) if not np.isclose(delta_diffs, 0, atol=FRAME_ATOL_MS): raise AssertionError(f'Timestamp gradient(ms): {delta_diffs:.1f}, ' f'ATOL: {FRAME_ATOL_MS}') # Remove data when lens is moving for k in sorted(d): if d[k]['lens_moving']: del d[k] # Split data into min_fd and af data for processing d_min_fd = {} d_af_fd = {} for k in sorted(d): if d[k]['fd'] == props['android.lens.info.minimumFocusDistance']: d_min_fd[k] = d[k] if d[k]['fd'] == af_fd: d_af_fd[k] = d[k] logging.debug('Assert reported locs are close for af_fd captures') min_loc = min([v['loc'] for v in d_af_fd.values()]) max_loc = max([v['loc'] for v in d_af_fd.values()]) if not np.isclose(min_loc, max_loc, rtol=POSITION_RTOL): raise AssertionError(f'af_fd[loc] min: {min_loc:.3f}, max: ' f'{max_loc:.3f}, RTOL: {POSITION_RTOL}') logging.debug('Assert reported sharpness is close at af_fd') min_sharp = min([v['sharpness'] for v in d_af_fd.values()]) max_sharp = max([v['sharpness'] for v in d_af_fd.values()]) if not np.isclose(min_sharp, max_sharp, rtol=SHARPNESS_RTOL): raise AssertionError(f'af_fd[sharpness] min: {min_sharp:.3f}, ' f'max: {max_sharp:.3f}, RTOL: {SHARPNESS_RTOL}') logging.debug('Assert reported loc is close to assign loc for af_fd') first_key = min(d_af_fd.keys()) # find 1st non-moving frame loc = d_af_fd[first_key]['loc'] fd = d_af_fd[first_key]['fd'] if not np.isclose(loc, fd, rtol=POSITION_RTOL): raise AssertionError(f'af_fd[loc]: {loc:.3f}, af_fd[fd]: {fd:.3f}, ' f'RTOL: {POSITION_RTOL}') logging.debug('Assert reported locs are close for min_fd captures') min_loc = min([v['loc'] for v in d_min_fd.values()]) max_loc = max([v['loc'] for v in d_min_fd.values()]) if not np.isclose(min_loc, max_loc, rtol=POSITION_RTOL): raise AssertionError(f'min_fd[loc] min: {min_loc:.3f}, max: ' f'{max_loc:.3f}, RTOL: {POSITION_RTOL}') logging.debug('Assert reported sharpness is close at min_fd') min_sharp = min([v['sharpness'] for v in d_min_fd.values()]) max_sharp = max([v['sharpness'] for v in d_min_fd.values()]) if not np.isclose(min_sharp, max_sharp, rtol=SHARPNESS_RTOL): raise AssertionError(f'min_fd[sharpness] min: {min_sharp:.3f}, ' f'max: {max_sharp:.3f}, RTOL: {SHARPNESS_RTOL}') logging.debug('Assert reported loc is close to assigned loc for min_fd') last_key = max(d_min_fd.keys()) # find last (non-moving) frame loc = d_min_fd[last_key]['loc'] fd = d_min_fd[last_key]['fd'] if not np.isclose(loc, fd, rtol=POSITION_RTOL): raise AssertionError(f'min_fd[loc]: {loc:.3f}, min_fd[fd]: {fd:.3f}, ' f'RTOL: {POSITION_RTOL}') logging.debug('Assert AF focus distance > minimum focus distance') min_fd = d_min_fd[last_key]['fd'] if af_fd > min_fd * MIN_AF_FD_TOL: raise AssertionError(f'AF focus distance > min focus distance! af: ' f'{af_fd}, min: {min_fd}, TOL: {MIN_AF_FD_TOL}') if __name__ == '__main__': test_runner.main()