119 lines
4.2 KiB
Python
119 lines
4.2 KiB
Python
# Copyright 2013 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 converted YUV images & device JPEG images look the same."""
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import logging
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import os.path
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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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import target_exposure_utils
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_NAME = os.path.splitext(os.path.basename(__file__))[0]
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_PATCH_H = 0.1 # center 10%
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_PATCH_W = 0.1
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_PATCH_X = 0.5 - _PATCH_W/2
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_PATCH_Y = 0.5 - _PATCH_H/2
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_THRESHOLD_MAX_RMS_DIFF = 0.01
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def compute_img_means_and_save(img, fmt_name, log_path):
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"""Extract center patch, compute means, and save image.
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Args:
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img: image array
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fmt_name: text to identify image
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log_path: location to save image
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Returns:
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means of image patch
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"""
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name_with_log_path = os.path.join(log_path, _NAME)
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image_processing_utils.write_image(
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img, f'{name_with_log_path}_fmt={fmt_name}.jpg')
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patch = image_processing_utils.get_image_patch(
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img, _PATCH_X, _PATCH_Y, _PATCH_W, _PATCH_H)
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rgb_means = image_processing_utils.compute_image_means(patch)
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logging.debug('%s rgb_means: %s', fmt_name, str(rgb_means))
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return rgb_means
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class JpegTest(its_base_test.ItsBaseTest):
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"""Test that converted YUV images and device JPEG images look the same."""
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def test_jpeg(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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log_path = self.log_path
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sync_latency = camera_properties_utils.sync_latency(props)
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# Check SKIP conditions
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camera_properties_utils.skip_unless(
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camera_properties_utils.linear_tonemap(props))
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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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# Initialize common request parameters
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if camera_properties_utils.compute_target_exposure(props):
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e, s = target_exposure_utils.get_target_exposure_combos(
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log_path, cam)['midExposureTime']
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req = capture_request_utils.manual_capture_request(
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s, e, 0.0, True, props)
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else:
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cam.do_3a(do_af=False)
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req = capture_request_utils.auto_capture_request(
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linear_tonemap=True, props=props, do_af=False)
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# YUV
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size = capture_request_utils.get_available_output_sizes('yuv', props)[0]
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out_surface = {'width': size[0], 'height': size[1], 'format': 'yuv'}
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cap = its_session_utils.do_capture_with_latency(
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cam, req, sync_latency, out_surface)
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img = image_processing_utils.convert_capture_to_rgb_image(cap)
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rgb_means_yuv = compute_img_means_and_save(img, 'yuv', log_path)
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# JPEG
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size = capture_request_utils.get_available_output_sizes('jpg', props)[0]
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out_surface = {'width': size[0], 'height': size[1], 'format': 'jpg'}
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cap = its_session_utils.do_capture_with_latency(
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cam, req, sync_latency, out_surface)
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img = image_processing_utils.decompress_jpeg_to_rgb_image(cap['data'])
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rgb_means_jpg = compute_img_means_and_save(img, 'jpg', log_path)
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# Assert images are similar
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rms_diff = image_processing_utils.compute_image_rms_difference_1d(
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rgb_means_yuv, rgb_means_jpg)
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logging.debug('RMS difference: %.3f', rms_diff)
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if rms_diff >= _THRESHOLD_MAX_RMS_DIFF:
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raise AssertionError(
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f'RMS diff: {rms_diff:.3f}, spec: {_THRESHOLD_MAX_RMS_DIFF}')
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if __name__ == '__main__':
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test_runner.main()
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