apps/CameraITS/tests/scene1_1/test_locked_burst.py

# 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.

import os.path
import its.caps
import its.device
import its.image
import its.objects

BURST_LEN = 8
COLORS = ['R', 'G', 'B']
FPS_MAX_DIFF = 2.0
NAME = os.path.basename(__file__).split('.')[0]
SPREAD_THRESH_MANUAL_SENSOR = 0.01
SPREAD_THRESH = 0.03
VALUE_THRESH = 0.1


def main():
    """Test 3A lock + YUV burst (using auto settings).

    This is a test that is designed to pass even on limited devices that
    don't have MANUAL_SENSOR or PER_FRAME_CONTROLS. The test checks
    YUV image consistency while the frame rate check is in CTS.
    """

    with its.device.ItsSession() as cam:
        props = cam.get_camera_properties()
        its.caps.skip_unless(its.caps.ae_lock(props) and
                             its.caps.awb_lock(props))
        mono_camera = its.caps.mono_camera(props)

        # Converge 3A prior to capture.
        cam.do_3a(do_af=True, lock_ae=True, lock_awb=True,
                  mono_camera=mono_camera)

        fmt = its.objects.get_largest_yuv_format(props)

        # After 3A has converged, lock AE+AWB for the duration of the test.
        print 'Locking AE & AWB'
        req = its.objects.fastest_auto_capture_request(props)
        req['android.control.awbLock'] = True
        req['android.control.aeLock'] = True

        # Capture bursts of YUV shots.
        # Get the mean values of a center patch for each.
        r_means = []
        g_means = []
        b_means = []
        caps = cam.do_capture([req]*BURST_LEN, fmt)
        for i, cap in enumerate(caps):
            img = its.image.convert_capture_to_rgb_image(cap)
            its.image.write_image(img, '%s_frame%d.jpg'%(NAME, i))
            tile = its.image.get_image_patch(img, 0.45, 0.45, 0.1, 0.1)
            means = its.image.compute_image_means(tile)
            r_means.append(means[0])
            g_means.append(means[1])
            b_means.append(means[2])

        # Assert center patch brightness & similarity
        for i, means in enumerate([r_means, g_means, b_means]):
            plane = COLORS[i]
            min_means = min(means)
            spread = max(means) - min_means
            print '%s patch mean spread %.5f. means = [' % (plane, spread),
            for j in range(BURST_LEN):
                print '%.5f' % means[j],
            print ']'
            e_msg = 'Image too dark!  %s: %.5f, THRESH: %.2f' % (
                    plane, min_means, VALUE_THRESH)
            assert min_means > VALUE_THRESH, e_msg
            threshold = SPREAD_THRESH_MANUAL_SENSOR \
                    if its.caps.manual_sensor(props) else SPREAD_THRESH
            e_msg = '%s center patch spread: %.5f, THRESH: %.2f' % (
                    plane, spread, threshold)
            assert spread < threshold, e_msg

if __name__ == '__main__':
    main()