apps/CameraITS/tests/scene4/test_preview_aspect_ratio_and_crop.py - platform/cts - Git at Google

 # Copyright 2022 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.
 """Validate preview aspect ratio, crop and FoV vs format."""

 import logging
 import os

 from mobly import test_runner

 import its_base_test
 import camera_properties_utils
 import capture_request_utils
 import image_fov_utils
 import image_processing_utils
 import its_session_utils
 import opencv_processing_utils
 import video_processing_utils


 _NAME = os.path.splitext(os.path.basename(__file__))[0]
 _VIDEO_DURATION = 3  # seconds
 _MAX_8BIT_IMGS = 255


 def _collect_data(cam, preview_size):
   """Capture a preview video from the device.

   Captures camera preview frames from the passed device.

   Args:
     cam: camera object
     preview_size: str; preview resolution. ex. '1920x1080'

   Returns:
     recording object as described by cam.do_preview_recording
   """

   recording_obj = cam.do_preview_recording(preview_size, _VIDEO_DURATION, False)
   logging.debug('Recorded output path: %s', recording_obj['recordedOutputPath'])
   logging.debug('Tested quality: %s', recording_obj['quality'])

   return recording_obj


 def _print_failed_test_results(failed_ar, failed_fov, failed_crop):
   """Print failed test results."""
   if failed_ar:
     logging.error('Aspect ratio test summary')
     logging.error('Images failed in the aspect ratio test:')
     logging.error('Aspect ratio value: width / height')
     for fa in failed_ar:
       logging.error('%s', fa)

   if failed_fov:
     logging.error('FoV test summary')
     logging.error('Images failed in the FoV test:')
     for fov in failed_fov:
       logging.error('%s', str(fov))

   if failed_crop:
     logging.error('Crop test summary')
     logging.error('Images failed in the crop test:')
     logging.error('Circle center (H x V) relative to the image center.')
     for fc in failed_crop:
       logging.error('%s', fc)


 class PreviewAspectRatioAndCropTest(its_base_test.ItsBaseTest):
   """Test preview aspect ratio/field of view/cropping for each tested fmt.

     This test checks for:
     1. Aspect ratio: images are not stretched
     2. Crop: center of images is not shifted
     3. FOV: images cropped to keep maximum possible FOV with only 1 dimension
        (horizontal or veritical) cropped.


   The test preview is a black circle on a white background.

   When RAW capture is available, set the height vs. width ratio of the circle in
   the full-frame RAW as ground truth. In an ideal setup such ratio should be
   very close to 1.0, but here we just use the value derived from full resolution
   RAW as ground truth to account for the possibility that the chart is not well
   positioned to be precisely parallel to image sensor plane.
   The test then compares the ground truth ratio with the same ratio measured
   on previews captured using different formats.

   If RAW capture is unavailable, a full resolution JPEG image is used to setup
   ground truth. In this case, the ground truth aspect ratio is defined as 1.0
   and it is the tester's responsibility to make sure the test chart is
   properly positioned so the detected circles indeed have aspect ratio close
   to 1.0 assuming no bugs causing image stretched.

   The aspect ratio test checks the aspect ratio of the detected circle and
   it will fail if the aspect ratio differs too much from the ground truth
   aspect ratio mentioned above.

   The FOV test examines the ratio between the detected circle area and the
   image size. When the aspect ratio of the test image is the same as the
   ground truth image, the ratio should be very close to the ground truth
   value. When the aspect ratio is different, the difference is factored in
   per the expectation of the Camera2 API specification, which mandates the
   FOV reduction from full sensor area must only occur in one dimension:
   horizontally or vertically, and never both. For example, let's say a sensor
   has a 16:10 full sensor FOV. For all 16:10 output images there should be no
   FOV reduction on them. For 16:9 output images the FOV should be vertically
   cropped by 9/10. For 4:3 output images the FOV should be cropped
   horizontally instead and the ratio (r) can be calculated as follows:
       (16 * r) / 10 = 4 / 3 => r = 40 / 48 = 0.8333
   Say the circle is covering x percent of the 16:10 sensor on the full 16:10
   FOV, and assume the circle in the center will never be cut in any output
   sizes (this can be achieved by picking the right size and position of the
   test circle), the from above cropping expectation we can derive on a 16:9
   output image the circle will cover (x / 0.9) percent of the 16:9 image; on
   a 4:3 output image the circle will cover (x / 0.8333) percent of the 4:3
   image.

   The crop test checks that the center of any output image remains aligned
   with center of sensor's active area, no matter what kind of cropping or
   scaling is applied. The test verifies that by checking the relative vector
   from the image center to the center of detected circle remains unchanged.
   The relative part is normalized by the detected circle size to account for
   scaling effect.
   """

   def test_preview_aspect_ratio_and_crop(self):
     log_path = self.log_path
     video_processing_utils.log_ffmpeg_version()

     with its_session_utils.ItsSession(
         device_id=self.dut.serial,
         camera_id=self.camera_id,
         hidden_physical_id=self.hidden_physical_id) as cam:
       failed_ar = []  # Streams failed the aspect ratio test
       failed_crop = []  # Streams failed the crop test
       failed_fov = []  # Streams that fail FoV test
       props = cam.get_camera_properties()
       fls_logical = props['android.lens.info.availableFocalLengths']
       logging.debug('logical available focal lengths: %s', str(fls_logical))
       props = cam.override_with_hidden_physical_camera_props(props)
       fls_physical = props['android.lens.info.availableFocalLengths']
       logging.debug('physical available focal lengths: %s', str(fls_physical))
       name_with_log_path = f'{os.path.join(self.log_path, _NAME)}'

       # Check SKIP conditions
       first_api_level = its_session_utils.get_first_api_level(self.dut.serial)
       camera_properties_utils.skip_unless(
           first_api_level >= its_session_utils.ANDROID14_API_LEVEL)

       # Load scene
       its_session_utils.load_scene(cam, props, self.scene,
                                    self.tablet, self.chart_distance)
       # Raise error if not FRONT or REAR facing camera
       camera_properties_utils.check_front_or_rear_camera(props)

       # List of preview resolutions to test
       supported_preview_sizes = cam.get_supported_preview_sizes(self.camera_id)
       for size in video_processing_utils.LOW_RESOLUTION_SIZES:
         if size in supported_preview_sizes:
           supported_preview_sizes.remove(size)
       logging.debug('Supported preview resolutions: %s',
                     supported_preview_sizes)
       raw_avlb = camera_properties_utils.raw16(props)
       full_or_better = camera_properties_utils.full_or_better(props)

       # Converge 3A
       cam.do_3a()
       req = capture_request_utils.auto_capture_request()
       if raw_avlb and (fls_physical == fls_logical):
         logging.debug('RAW')
         raw_bool = True
       else:
         logging.debug('JPEG')
         raw_bool = False
       ref_fov, cc_ct_gt, aspect_ratio_gt = image_fov_utils.find_fov_reference(
           cam, req, props, raw_bool, name_with_log_path)

       run_crop_test = full_or_better and raw_avlb

       # Check if we support testing this preview size
       for preview_size in supported_preview_sizes:
         logging.debug('Testing preview recording for size: %s', preview_size)
         # recording preview
         preview_rec_obj = _collect_data(cam, preview_size)

         # Grab the recording from DUT
         self.dut.adb.pull([preview_rec_obj['recordedOutputPath'], log_path])
         preview_file_name = (
             preview_rec_obj['recordedOutputPath'].split('/')[-1])
         logging.debug('preview_file_name: %s', preview_file_name)
         preview_size = preview_rec_obj['videoSize']
         width = int(preview_size.split('x')[0])
         height = int(preview_size.split('x')[-1])

         # Extract last key frame as numpy image
         last_key_frame = (
             video_processing_utils.extract_last_key_frame_from_recording(
                 self.log_path, preview_file_name)
         )

         # Check FoV
         ref_img_name = (f'{name_with_log_path}_{preview_size}_circle.png')
         circle = opencv_processing_utils.find_circle(
             last_key_frame, ref_img_name, image_fov_utils.CIRCLE_MIN_AREA,
             image_fov_utils.CIRCLE_COLOR)

         opencv_processing_utils.append_circle_center_to_img(
             circle, last_key_frame, ref_img_name)

         max_img_value = _MAX_8BIT_IMGS

         # Check pass/fail for fov coverage for all fmts in AR_CHECKED
         img_name_stem = f'{name_with_log_path}_{preview_size}'
         fov_chk_msg = image_fov_utils.check_fov(
             circle, ref_fov, width, height)
         if fov_chk_msg:
           img_name = f'{img_name_stem}_fov.png'
           fov_chk_preview_msg = f'Preview Size: {preview_size} {fov_chk_msg}'
           failed_fov.append(fov_chk_preview_msg)
           image_processing_utils.write_image(
               last_key_frame/max_img_value, img_name, True)

         # Check pass/fail for aspect ratio
         ar_chk_msg = image_fov_utils.check_ar(
             circle, aspect_ratio_gt, width, height,
             f'{preview_size}')
         if ar_chk_msg:
           img_name = f'{img_name_stem}_ar.png'
           failed_ar.append(ar_chk_msg)
           image_processing_utils.write_image(
               last_key_frame/max_img_value, img_name, True)

         # Check pass/fail for crop
         if run_crop_test:
           # Normalize the circle size to 1/4 of the image size, so that
           # circle size won't affect the crop test result
           crop_thresh_factor = ((min(ref_fov['w'], ref_fov['h']) / 4.0) /
                                 max(ref_fov['circle_w'],
                                     ref_fov['circle_h']))
           crop_chk_msg = image_fov_utils.check_crop(
               circle, cc_ct_gt, width, height,
               f'{preview_size}', crop_thresh_factor)
           if crop_chk_msg:
             crop_img_name = f'{img_name_stem}_crop.png'
             failed_crop.append(crop_chk_msg)
             image_processing_utils.write_image(last_key_frame/max_img_value,
                                                crop_img_name, True)
         else:
           logging.debug('Crop test skipped')

     # Print any failed test results
     _print_failed_test_results(failed_ar, failed_fov, failed_crop)

     e_msg = ''
     if failed_ar:
       e_msg = 'Aspect ratio '
     if failed_fov:
       e_msg += 'FoV '
     if failed_crop:
       e_msg += 'Crop '
     if e_msg:
       raise AssertionError(f'{e_msg}check failed.')

 if __name__ == '__main__':
   test_runner.main()
	# Copyright 2022 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.
	"""Validate preview aspect ratio, crop and FoV vs format."""

	import logging
	import os

	from mobly import test_runner

	import its_base_test
	import camera_properties_utils
	import capture_request_utils
	import image_fov_utils
	import image_processing_utils
	import its_session_utils
	import opencv_processing_utils
	import video_processing_utils


	_NAME = os.path.splitext(os.path.basename(__file__))[0]
	_VIDEO_DURATION = 3 # seconds
	_MAX_8BIT_IMGS = 255


	def _collect_data(cam, preview_size):
	"""Capture a preview video from the device.

	Captures camera preview frames from the passed device.

	Args:
	cam: camera object
	preview_size: str; preview resolution. ex. '1920x1080'

	Returns:
	recording object as described by cam.do_preview_recording
	"""

	recording_obj = cam.do_preview_recording(preview_size, _VIDEO_DURATION, False)
	logging.debug('Recorded output path: %s', recording_obj['recordedOutputPath'])
	logging.debug('Tested quality: %s', recording_obj['quality'])

	return recording_obj


	def _print_failed_test_results(failed_ar, failed_fov, failed_crop):
	"""Print failed test results."""
	if failed_ar:
	logging.error('Aspect ratio test summary')
	logging.error('Images failed in the aspect ratio test:')
	logging.error('Aspect ratio value: width / height')
	for fa in failed_ar:
	logging.error('%s', fa)

	if failed_fov:
	logging.error('FoV test summary')
	logging.error('Images failed in the FoV test:')
	for fov in failed_fov:
	logging.error('%s', str(fov))

	if failed_crop:
	logging.error('Crop test summary')
	logging.error('Images failed in the crop test:')
	logging.error('Circle center (H x V) relative to the image center.')
	for fc in failed_crop:
	logging.error('%s', fc)


	class PreviewAspectRatioAndCropTest(its_base_test.ItsBaseTest):
	"""Test preview aspect ratio/field of view/cropping for each tested fmt.

	This test checks for:
	1. Aspect ratio: images are not stretched
	2. Crop: center of images is not shifted
	3. FOV: images cropped to keep maximum possible FOV with only 1 dimension
	(horizontal or veritical) cropped.



	The test preview is a black circle on a white background.

	When RAW capture is available, set the height vs. width ratio of the circle in
	the full-frame RAW as ground truth. In an ideal setup such ratio should be
	very close to 1.0, but here we just use the value derived from full resolution
	RAW as ground truth to account for the possibility that the chart is not well
	positioned to be precisely parallel to image sensor plane.
	The test then compares the ground truth ratio with the same ratio measured
	on previews captured using different formats.

	If RAW capture is unavailable, a full resolution JPEG image is used to setup
	ground truth. In this case, the ground truth aspect ratio is defined as 1.0
	and it is the tester's responsibility to make sure the test chart is
	properly positioned so the detected circles indeed have aspect ratio close
	to 1.0 assuming no bugs causing image stretched.

	The aspect ratio test checks the aspect ratio of the detected circle and
	it will fail if the aspect ratio differs too much from the ground truth
	aspect ratio mentioned above.

	The FOV test examines the ratio between the detected circle area and the
	image size. When the aspect ratio of the test image is the same as the
	ground truth image, the ratio should be very close to the ground truth
	value. When the aspect ratio is different, the difference is factored in
	per the expectation of the Camera2 API specification, which mandates the
	FOV reduction from full sensor area must only occur in one dimension:
	horizontally or vertically, and never both. For example, let's say a sensor
	has a 16:10 full sensor FOV. For all 16:10 output images there should be no
	FOV reduction on them. For 16:9 output images the FOV should be vertically
	cropped by 9/10. For 4:3 output images the FOV should be cropped
	horizontally instead and the ratio (r) can be calculated as follows:
	(16 * r) / 10 = 4 / 3 => r = 40 / 48 = 0.8333
	Say the circle is covering x percent of the 16:10 sensor on the full 16:10
	FOV, and assume the circle in the center will never be cut in any output
	sizes (this can be achieved by picking the right size and position of the
	test circle), the from above cropping expectation we can derive on a 16:9
	output image the circle will cover (x / 0.9) percent of the 16:9 image; on
	a 4:3 output image the circle will cover (x / 0.8333) percent of the 4:3
	image.

	The crop test checks that the center of any output image remains aligned
	with center of sensor's active area, no matter what kind of cropping or
	scaling is applied. The test verifies that by checking the relative vector
	from the image center to the center of detected circle remains unchanged.
	The relative part is normalized by the detected circle size to account for
	scaling effect.
	"""

	def test_preview_aspect_ratio_and_crop(self):
	log_path = self.log_path
	video_processing_utils.log_ffmpeg_version()

	with its_session_utils.ItsSession(
	device_id=self.dut.serial,
	camera_id=self.camera_id,
	hidden_physical_id=self.hidden_physical_id) as cam:
	failed_ar = [] # Streams failed the aspect ratio test
	failed_crop = [] # Streams failed the crop test
	failed_fov = [] # Streams that fail FoV test
	props = cam.get_camera_properties()
	fls_logical = props['android.lens.info.availableFocalLengths']
	logging.debug('logical available focal lengths: %s', str(fls_logical))
	props = cam.override_with_hidden_physical_camera_props(props)
	fls_physical = props['android.lens.info.availableFocalLengths']
	logging.debug('physical available focal lengths: %s', str(fls_physical))
	name_with_log_path = f'{os.path.join(self.log_path, _NAME)}'

	# Check SKIP conditions
	first_api_level = its_session_utils.get_first_api_level(self.dut.serial)
	camera_properties_utils.skip_unless(
	first_api_level >= its_session_utils.ANDROID14_API_LEVEL)

	# Load scene
	its_session_utils.load_scene(cam, props, self.scene,
	self.tablet, self.chart_distance)
	# Raise error if not FRONT or REAR facing camera
	camera_properties_utils.check_front_or_rear_camera(props)

	# List of preview resolutions to test
	supported_preview_sizes = cam.get_supported_preview_sizes(self.camera_id)
	for size in video_processing_utils.LOW_RESOLUTION_SIZES:
	if size in supported_preview_sizes:
	supported_preview_sizes.remove(size)
	logging.debug('Supported preview resolutions: %s',
	supported_preview_sizes)
	raw_avlb = camera_properties_utils.raw16(props)
	full_or_better = camera_properties_utils.full_or_better(props)

	# Converge 3A
	cam.do_3a()
	req = capture_request_utils.auto_capture_request()
	if raw_avlb and (fls_physical == fls_logical):
	logging.debug('RAW')
	raw_bool = True
	else:
	logging.debug('JPEG')
	raw_bool = False
	ref_fov, cc_ct_gt, aspect_ratio_gt = image_fov_utils.find_fov_reference(
	cam, req, props, raw_bool, name_with_log_path)

	run_crop_test = full_or_better and raw_avlb

	# Check if we support testing this preview size
	for preview_size in supported_preview_sizes:
	logging.debug('Testing preview recording for size: %s', preview_size)
	# recording preview
	preview_rec_obj = _collect_data(cam, preview_size)

	# Grab the recording from DUT
	self.dut.adb.pull([preview_rec_obj['recordedOutputPath'], log_path])
	preview_file_name = (
	preview_rec_obj['recordedOutputPath'].split('/')[-1])
	logging.debug('preview_file_name: %s', preview_file_name)
	preview_size = preview_rec_obj['videoSize']
	width = int(preview_size.split('x')[0])
	height = int(preview_size.split('x')[-1])

	# Extract last key frame as numpy image
	last_key_frame = (
	video_processing_utils.extract_last_key_frame_from_recording(
	self.log_path, preview_file_name)
	)

	# Check FoV
	ref_img_name = (f'{name_with_log_path}_{preview_size}_circle.png')
	circle = opencv_processing_utils.find_circle(
	last_key_frame, ref_img_name, image_fov_utils.CIRCLE_MIN_AREA,
	image_fov_utils.CIRCLE_COLOR)

	opencv_processing_utils.append_circle_center_to_img(
	circle, last_key_frame, ref_img_name)

	max_img_value = _MAX_8BIT_IMGS

	# Check pass/fail for fov coverage for all fmts in AR_CHECKED
	img_name_stem = f'{name_with_log_path}_{preview_size}'
	fov_chk_msg = image_fov_utils.check_fov(
	circle, ref_fov, width, height)
	if fov_chk_msg:
	img_name = f'{img_name_stem}_fov.png'
	fov_chk_preview_msg = f'Preview Size: {preview_size} {fov_chk_msg}'
	failed_fov.append(fov_chk_preview_msg)
	image_processing_utils.write_image(
	last_key_frame/max_img_value, img_name, True)

	# Check pass/fail for aspect ratio
	ar_chk_msg = image_fov_utils.check_ar(
	circle, aspect_ratio_gt, width, height,
	f'{preview_size}')
	if ar_chk_msg:
	img_name = f'{img_name_stem}_ar.png'
	failed_ar.append(ar_chk_msg)
	image_processing_utils.write_image(
	last_key_frame/max_img_value, img_name, True)

	# Check pass/fail for crop
	if run_crop_test:
	# Normalize the circle size to 1/4 of the image size, so that
	# circle size won't affect the crop test result
	crop_thresh_factor = ((min(ref_fov['w'], ref_fov['h']) / 4.0) /
	max(ref_fov['circle_w'],
	ref_fov['circle_h']))
	crop_chk_msg = image_fov_utils.check_crop(
	circle, cc_ct_gt, width, height,
	f'{preview_size}', crop_thresh_factor)
	if crop_chk_msg:
	crop_img_name = f'{img_name_stem}_crop.png'
	failed_crop.append(crop_chk_msg)
	image_processing_utils.write_image(last_key_frame/max_img_value,
	crop_img_name, True)
	else:
	logging.debug('Crop test skipped')

	# Print any failed test results
	_print_failed_test_results(failed_ar, failed_fov, failed_crop)

	e_msg = ''
	if failed_ar:
	e_msg = 'Aspect ratio '
	if failed_fov:
	e_msg += 'FoV '
	if failed_crop:
	e_msg += 'Crop '
	if e_msg:
	raise AssertionError(f'{e_msg}check failed.')

	if __name__ == '__main__':
	test_runner.main()