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# 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
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 (chart_distance=0 for no chart scaling)
its_session_utils.load_scene(
cam, props, self.scene, self.tablet, chart_distance=0)
# 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
# Intentionally blur images for noise measurements
s_ae, e_ae, _, _, _ = cam.do_3a(do_af=False, 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, 0)
# 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()
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