# Copyright 2013 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.sensor.sensitivity parameter is applied.""" 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 target_exposure_utils COLORS = ['R', 'G', 'B'] NAME = os.path.splitext(os.path.basename(__file__))[0] NUM_STEPS = 5 PATCH_H = 0.1 # center 10% PATCH_W = 0.1 PATCH_X = 0.5 - PATCH_W/2 PATCH_Y = 0.5 - PATCH_H/2 class ParamSensitivityTest(its_base_test.ItsBaseTest): """Test that the android.sensor.sensitivity parameter is applied.""" def test_param_sensitivity(self): logging.debug('Starting %s', NAME) sensitivities = None r_means = [] g_means = [] b_means = [] 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) log_path = self.log_path test_name_with_path = os.path.join(log_path, NAME) # check SKIP conditions camera_properties_utils.skip_unless( camera_properties_utils.compute_target_exposure(props)) # Load chart for scene its_session_utils.load_scene( cam, props, self.scene, self.tablet, self.chart_distance) # Initialize requests sync_latency = camera_properties_utils.sync_latency(props) largest_yuv = capture_request_utils.get_largest_yuv_format(props) match_ar = (largest_yuv['width'], largest_yuv['height']) fmt = capture_request_utils.get_smallest_yuv_format( props, match_ar=match_ar) expt, _ = target_exposure_utils.get_target_exposure_combos( log_path, cam)['midSensitivity'] sens_range = props['android.sensor.info.sensitivityRange'] sens_step = (sens_range[1] - sens_range[0]) / float(NUM_STEPS-1) sensitivities = [ int(sens_range[0] + i * sens_step) for i in range(NUM_STEPS)] for s in sensitivities: logging.debug('Capturing with sensitivity: %d', s) req = capture_request_utils.manual_capture_request(s, expt) cap = its_session_utils.do_capture_with_latency( cam, req, sync_latency, fmt) img = image_processing_utils.convert_capture_to_rgb_image(cap) image_processing_utils.write_image( img, f'{test_name_with_path}_iso={s}.jpg') patch = image_processing_utils.get_image_patch( img, PATCH_X, PATCH_Y, PATCH_W, PATCH_H) rgb_means = image_processing_utils.compute_image_means(patch) r_means.append(rgb_means[0]) g_means.append(rgb_means[1]) b_means.append(rgb_means[2]) logging.debug('R means: %s', str(r_means)) logging.debug('G means: %s', str(g_means)) logging.debug('B means: %s', str(b_means)) # Draw plot pylab.figure(NAME) pylab.plot(sensitivities, r_means, '-ro') pylab.plot(sensitivities, g_means, '-go') pylab.plot(sensitivities, b_means, '-bo') pylab.ylim([0, 1]) pylab.title(NAME) pylab.xlabel('Gain (ISO)') pylab.ylabel('RGB means') matplotlib.pyplot.savefig(f'{test_name_with_path}_plot_means.png') # Test for pass/fail: check that each shot is brighter than previous for i, means in enumerate([r_means, g_means, b_means]): for j in range(len(means)-1): if means[j+1] <= means[j]: raise AssertionError(f'{COLORS[i]} cap {j} means[j+1]: ' f'{means[j+1]:.3f}, means[j]: {means[j]:.3f}') if __name__ == '__main__': test_runner.main()