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