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# Copyright 2019 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 camera will produce full black & full white images."""
import logging
import math
import os.path
import matplotlib
from matplotlib import pylab
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
_ANDROID10_API_LEVEL = 29
CH_FULL_SCALE = 255
CH_THRESH_BLACK = 6
CH_THRESH_WHITE = CH_FULL_SCALE - 6
CH_TOL_WHITE = 2
COLOR_PLANES = ['R', 'G', 'B']
NAME = os.path.splitext(os.path.basename(__file__))[0]
PATCH_H = 0.1
PATCH_W = 0.1
PATCH_X = 0.45
PATCH_Y = 0.45
VGA_WIDTH, VGA_HEIGHT = 640, 480
def do_img_capture(cam, s, e, fmt, latency, cap_name, log_path):
"""Do the image captures with the defined parameters.
Args:
cam: its_session open for camera
s: sensitivity for request
e: exposure in ns for request
fmt: format of request
latency: number of frames for sync latency of request
cap_name: string to define the capture
log_path: path for plot directory
Returns:
means values of center patch from capture
"""
req = capture_request_utils.manual_capture_request(s, e)
cap = its_session_utils.do_capture_with_latency(cam, req, latency, fmt)
img = image_processing_utils.convert_capture_to_rgb_image(cap)
image_processing_utils.write_image(
img, '%s_%s.jpg' % (os.path.join(log_path, NAME), cap_name))
patch = image_processing_utils.get_image_patch(
img, PATCH_X, PATCH_Y, PATCH_W, PATCH_H)
means = image_processing_utils.compute_image_means(patch)
means = [m * CH_FULL_SCALE for m in means]
logging.debug('%s pixel means: %s', cap_name, str(means))
r_exp = cap['metadata']['android.sensor.exposureTime']
r_iso = cap['metadata']['android.sensor.sensitivity']
logging.debug('%s shot write values: sens = %d, exp time = %.4fms',
cap_name, s, (e / 1000000.0))
logging.debug('%s shot read values: sens = %d, exp time = %.4fms',
cap_name, r_iso, (r_exp / 1000000.0))
return means
class BlackWhiteTest(its_base_test.ItsBaseTest):
"""Test that device will prodoce full black + white images.
"""
def test_black_white(self):
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)
# Check SKIP conditions
camera_properties_utils.skip_unless(
camera_properties_utils.manual_sensor(props))
# Load chart for scene
its_session_utils.load_scene(
cam, props, self.scene, self.tablet, self.chart_distance)
# Initialize params for requests
latency = camera_properties_utils.sync_latency(props)
fmt = {'format': 'yuv', 'width': VGA_WIDTH, 'height': VGA_HEIGHT}
expt_range = props['android.sensor.info.exposureTimeRange']
sens_range = props['android.sensor.info.sensitivityRange']
log_path = self.log_path
# Take shot with very low ISO and exp time: expect it to be black
s = sens_range[0]
e = expt_range[0]
black_means = do_img_capture(cam, s, e, fmt, latency, 'black', log_path)
r_means.append(black_means[0])
g_means.append(black_means[1])
b_means.append(black_means[2])
# Take shot with very high ISO and exp time: expect it to be white.
s = sens_range[1]
e = expt_range[1]
white_means = do_img_capture(cam, s, e, fmt, latency, 'white', log_path)
r_means.append(white_means[0])
g_means.append(white_means[1])
b_means.append(white_means[2])
# Draw plot
pylab.title('test_black_white')
pylab.plot([0, 1], r_means, '-ro')
pylab.plot([0, 1], g_means, '-go')
pylab.plot([0, 1], b_means, '-bo')
pylab.xlabel('Capture Number')
pylab.ylabel('Output Values [0:255]')
pylab.ylim([0, 255])
matplotlib.pyplot.savefig('%s_plot_means.png' % (
os.path.join(log_path, NAME)))
# Assert blacks below CH_THRESH_BLACK
for ch, mean in enumerate(black_means):
if mean >= CH_THRESH_BLACK:
raise AssertionError(f'{COLOR_PLANES[ch]} black: {mean:.1f}, '
f'THRESH: {CH_THRESH_BLACK}')
# Assert whites above CH_THRESH_WHITE
for ch, mean in enumerate(white_means):
if mean <= CH_THRESH_WHITE:
raise AssertionError(f'{COLOR_PLANES[ch]} white: {mean:.1f}, '
f'THRESH: {CH_THRESH_WHITE}')
# Assert channels saturate evenly (was test_channel_saturation)
first_api_level = its_session_utils.get_first_api_level(self.dut.serial)
if first_api_level > _ANDROID10_API_LEVEL:
if not math.isclose(
np.amin(white_means), np.amax(white_means), abs_tol=CH_TOL_WHITE):
raise AssertionError('channel saturation not equal! '
f'RGB: {white_means}, ATOL: {CH_TOL_WHITE}')
if __name__ == '__main__':
test_runner.main()