# 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. """Verifies sensitivities on RAW images.""" import logging import os.path import matplotlib from matplotlib import pylab from mobly import test_runner import its_base_test import camera_properties_utils import capture_request_utils import image_processing_utils import its_session_utils import opencv_processing_utils GR_PLANE_IDX = 1 # GR plane index in RGGB data IMG_STATS_GRID = 9 # Center 11.11% NAME = os.path.splitext(os.path.basename(__file__))[0] NUM_SENS_STEPS = 5 VAR_THRESH = 1.01 # Each shot must be 1% noisier than previous def define_raw_stats_fmt(props): """Define format with active array width and height.""" aaw = (props['android.sensor.info.preCorrectionActiveArraySize']['right'] - props['android.sensor.info.preCorrectionActiveArraySize']['left']) aah = (props['android.sensor.info.preCorrectionActiveArraySize']['bottom'] - props['android.sensor.info.preCorrectionActiveArraySize']['top']) logging.debug('Active array W,H: %d,%d', aaw, aah) return {'format': 'rawStats', 'gridWidth': aaw // IMG_STATS_GRID, 'gridHeight': aah // IMG_STATS_GRID} class RawSensitivityTest(its_base_test.ItsBaseTest): """Capture a set of raw images with increasing gains and measure the noise.""" def test_raw_sensitivity(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: props = cam.get_camera_properties() props = cam.override_with_hidden_physical_camera_props(props) camera_properties_utils.skip_unless( camera_properties_utils.raw16(props) and camera_properties_utils.manual_sensor(props) and camera_properties_utils.read_3a(props) and camera_properties_utils.per_frame_control(props) and not camera_properties_utils.mono_camera(props)) name_with_log_path = os.path.join(self.log_path, NAME) camera_fov = float(cam.calc_camera_fov(props)) # Load chart for scene its_session_utils.load_scene( cam, props, self.scene, self.tablet, self.chart_distance) # Expose for the scene with min sensitivity sens_min, _ = props['android.sensor.info.sensitivityRange'] # Digital gains might not be visible on RAW data sens_max = props['android.sensor.maxAnalogSensitivity'] sens_step = (sens_max - sens_min) // NUM_SENS_STEPS # Skip AF if TELE camera if camera_fov <= opencv_processing_utils.FOV_THRESH_TELE: s_ae, e_ae, _, _, _ = cam.do_3a(do_af=False, get_results=True) f_dist = 0 else: s_ae, e_ae, _, _, f_dist = cam.do_3a(get_results=True) s_e_prod = s_ae * e_ae sensitivities = list(range(sens_min, sens_max, sens_step)) variances = [] for s in sensitivities: e = int(s_e_prod / float(s)) req = capture_request_utils.manual_capture_request(s, e, f_dist) # Capture in rawStats to reduce test run time fmt = define_raw_stats_fmt(props) cap = cam.do_capture(req, fmt) if self.debug_mode: img = image_processing_utils.convert_capture_to_rgb_image( cap, props=props) image_processing_utils.write_image( img, f'{name_with_log_path}_{s}_{e}ns.jpg', True) # Measure variance _, var_image = image_processing_utils.unpack_rawstats_capture(cap) cfa_idxs = image_processing_utils.get_canonical_cfa_order(props) white_level = float(props['android.sensor.info.whiteLevel']) var = var_image[IMG_STATS_GRID//2, IMG_STATS_GRID//2, cfa_idxs[GR_PLANE_IDX]]/white_level**2 logging.debug('s=%d, e=%d, var=%e', s, e, var) variances.append(var) # Create plot pylab.figure(NAME) pylab.plot(sensitivities, variances, '-ro') pylab.xticks(sensitivities) pylab.xlabel('Sensitivities') pylab.ylabel('Image Center Patch Variance') pylab.ticklabel_format(axis='y', style='sci', scilimits=(-6, -6)) pylab.title(NAME) matplotlib.pyplot.savefig(f'{name_with_log_path}_variances.png') # Test that each shot is noisier than previous for i in range(len(variances) - 1): if variances[i] >= variances[i+1]/VAR_THRESH: raise AssertionError(f'variances [i]: {variances[i]:5f}, [i+1]: ' f'{variances[i+1]:.5f}, THRESH: {VAR_THRESH}') if __name__ == '__main__': test_runner.main()