125 lines
4.9 KiB
Python
125 lines
4.9 KiB
Python
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# Copyright 2014 The Android Open Source Project
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Verifies sensitivities on RAW images."""
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import logging
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import os.path
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import matplotlib
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from matplotlib import pylab
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from mobly import test_runner
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import its_base_test
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import camera_properties_utils
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import capture_request_utils
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import image_processing_utils
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import its_session_utils
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_GR_PLANE_IDX = 1 # GR plane index in RGGB data
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_IMG_STATS_GRID = 9 # Center 11.11%
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_NAME = os.path.splitext(os.path.basename(__file__))[0]
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_NUM_SENS_STEPS = 5
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_VAR_THRESH = 1.01 # Each shot must be 1% noisier than previous
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def define_raw_stats_fmt(props):
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"""Define format with active array width and height."""
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aaw = (props['android.sensor.info.preCorrectionActiveArraySize']['right'] -
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props['android.sensor.info.preCorrectionActiveArraySize']['left'])
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aah = (props['android.sensor.info.preCorrectionActiveArraySize']['bottom'] -
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props['android.sensor.info.preCorrectionActiveArraySize']['top'])
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logging.debug('Active array W,H: %d,%d', aaw, aah)
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return {'format': 'rawStats',
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'gridWidth': aaw // _IMG_STATS_GRID,
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'gridHeight': aah // _IMG_STATS_GRID}
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class RawSensitivityTest(its_base_test.ItsBaseTest):
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"""Capture a set of raw images with increasing gains and measure the noise."""
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def test_raw_sensitivity(self):
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logging.debug('Starting %s', _NAME)
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with its_session_utils.ItsSession(
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device_id=self.dut.serial,
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camera_id=self.camera_id,
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hidden_physical_id=self.hidden_physical_id) as cam:
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props = cam.get_camera_properties()
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props = cam.override_with_hidden_physical_camera_props(props)
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camera_properties_utils.skip_unless(
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camera_properties_utils.raw16(props) and
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camera_properties_utils.manual_sensor(props) and
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camera_properties_utils.read_3a(props) and
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camera_properties_utils.per_frame_control(props) and
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not camera_properties_utils.mono_camera(props))
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name_with_log_path = os.path.join(self.log_path, _NAME)
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# Load chart for scene
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its_session_utils.load_scene(
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cam, props, self.scene, self.tablet,
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its_session_utils.CHART_DISTANCE_NO_SCALING)
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# Expose for the scene with min sensitivity
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sens_min, _ = props['android.sensor.info.sensitivityRange']
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# Digital gains might not be visible on RAW data
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sens_max = props['android.sensor.maxAnalogSensitivity']
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sens_step = (sens_max - sens_min) // _NUM_SENS_STEPS
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# Intentionally blur images for noise measurements
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s_ae, e_ae, _, _, _ = cam.do_3a(do_af=False, get_results=True)
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s_e_prod = s_ae * e_ae
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sensitivities = list(range(sens_min, sens_max, sens_step))
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variances = []
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for s in sensitivities:
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e = int(s_e_prod / float(s))
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req = capture_request_utils.manual_capture_request(s, e, 0)
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# Capture in rawStats to reduce test run time
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fmt = define_raw_stats_fmt(props)
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cap = cam.do_capture(req, fmt)
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if self.debug_mode:
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img = image_processing_utils.convert_capture_to_rgb_image(
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cap, props=props)
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image_processing_utils.write_image(
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img, f'{name_with_log_path}_{s}_{e}ns.jpg', True)
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# Measure variance
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_, var_image = image_processing_utils.unpack_rawstats_capture(cap)
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cfa_idxs = image_processing_utils.get_canonical_cfa_order(props)
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white_level = float(props['android.sensor.info.whiteLevel'])
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var = var_image[_IMG_STATS_GRID//2, _IMG_STATS_GRID//2,
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cfa_idxs[_GR_PLANE_IDX]]/white_level**2
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logging.debug('s=%d, e=%d, var=%e', s, e, var)
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variances.append(var)
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# Create plot
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pylab.figure(_NAME)
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pylab.plot(sensitivities, variances, '-ro')
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pylab.xticks(sensitivities)
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pylab.xlabel('Sensitivities')
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pylab.ylabel('Image Center Patch Variance')
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pylab.ticklabel_format(axis='y', style='sci', scilimits=(-6, -6))
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pylab.title(_NAME)
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matplotlib.pyplot.savefig(f'{name_with_log_path}_variances.png')
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# Test that each shot is noisier than previous
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for i in range(len(variances) - 1):
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if variances[i] >= variances[i+1]/_VAR_THRESH:
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raise AssertionError(f'variances [i]: {variances[i]:5f}, [i+1]: '
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f'{variances[i+1]:.5f}, THRESH: {_VAR_THRESH}')
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if __name__ == '__main__':
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test_runner.main()
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