def test_run_strred_fextractor_blackframes(self):
print 'test on running STRRED feature extractor on flat frames...'
ref_path = VmafConfig.test_resource_path("yuv", "flat_1920_1080_0.yuv")
dis_path = VmafConfig.test_resource_path("yuv", "flat_1920_1080_10.yuv")
asset = Asset(dataset="test", content_id=0, asset_id=0,
workdir_root=VmafConfig.workdir_path(),
ref_path=ref_path,
dis_path=dis_path,
asset_dict={'width':576, 'height':324})
asset_original = Asset(dataset="test", content_id=0, asset_id=1,
workdir_root=VmafConfig.workdir_path(),
ref_path=ref_path,
dis_path=ref_path,
asset_dict={'width':576, 'height':324})
from vmaf.core.result_store import FileSystemResultStore
result_store = FileSystemResultStore(logger=None)
self.fextractor = StrredFeatureExtractor(
[asset, asset_original],
None, fifo_mode=True,
result_store=result_store
)
print ' running for the first time with fresh calculation...'
self.fextractor.run(parallelize=True)
result0, result1 = self.fextractor.results
import os
self.assertTrue(os.path.exists(result_store._get_result_file_path(result0)))
self.assertTrue(os.path.exists(result_store._get_result_file_path(result1)))
print ' running for the second time with stored results...'
self.fextractor.run(parallelize=True)
results = self.fextractor.results
# ignore NaN
for result in results:
result.set_score_aggregate_method(ListStats.nonemean)
self.assertAlmostEqual(results[0]['STRRED_feature_srred_score'], 1220.5679849999999, places=4)
self.assertAlmostEqual(results[0]['STRRED_feature_trred_score'], 50983.3097155, places=4)
self.assertAlmostEqual(results[0]['STRRED_feature_strred_score'], 62228595.6081, places=4)
self.assertAlmostEqual(results[1]['STRRED_feature_srred_score'], 0.0, places=4)
self.assertAlmostEqual(results[1]['STRRED_feature_trred_score'], 0.0, places=4)
self.assertAlmostEqual(results[1]['STRRED_feature_strred_score'], 0.0, places=4)
def test_run_strred_fextractor_blackframes(self):
print 'test on running STRRED feature extractor on flat frames...'
ref_path = VmafConfig.test_resource_path("yuv", "flat_1920_1080_0.yuv")
dis_path = VmafConfig.test_resource_path("yuv", "flat_1920_1080_10.yuv")
asset = Asset(dataset="test", content_id=0, asset_id=0,
workdir_root=VmafConfig.workdir_path(),
ref_path=ref_path,
dis_path=dis_path,
asset_dict={'width':576, 'height':324})
asset_original = Asset(dataset="test", content_id=0, asset_id=1,
workdir_root=VmafConfig.workdir_path(),
ref_path=ref_path,
dis_path=ref_path,
asset_dict={'width':576, 'height':324})
from vmaf.core.result_store import FileSystemResultStore
result_store = FileSystemResultStore(logger=None)
self.fextractor = StrredFeatureExtractor(
[asset, asset_original],
None, fifo_mode=True,
result_store=result_store
)
print ' running for the first time with fresh calculation...'
self.fextractor.run(parallelize=True)
result0, result1 = self.fextractor.results
import os
self.assertTrue(os.path.exists(result_store._get_result_file_path(result0)))
self.assertTrue(os.path.exists(result_store._get_result_file_path(result1)))
print ' running for the second time with stored results...'
self.fextractor.run(parallelize=True)
results = self.fextractor.results
# ignore NaN
for result in results:
result.set_score_aggregate_method(ListStats.nonemean)
self.assertAlmostEqual(results[0]['STRRED_feature_srred_score'], 1220.5679849999999, places=4)
self.assertAlmostEqual(results[0]['STRRED_feature_trred_score'], 50983.3097155, places=4)
self.assertAlmostEqual(results[0]['STRRED_feature_strred_score'], 62228595.6081, places=4)
self.assertAlmostEqual(results[1]['STRRED_feature_srred_score'], 0.0, places=4)
self.assertAlmostEqual(results[1]['STRRED_feature_trred_score'], 0.0, places=4)
self.assertAlmostEqual(results[1]['STRRED_feature_strred_score'], 0.0, places=4)
def test_run_parallel_vamf_fextractor_with_result_store(self):
print 'test on running VMAF feature extractor with result store ' \
'in parallel...'
ref_path = VmafConfig.test_resource_path("yuv", "src01_hrc00_576x324.yuv")
dis_path = VmafConfig.test_resource_path("yuv", "src01_hrc01_576x324.yuv")
asset = Asset(dataset="test", content_id=0, asset_id=0,
workdir_root=VmafConfig.workdir_path(),
ref_path=ref_path,
dis_path=dis_path,
asset_dict={'width':576, 'height':324})
asset_original = Asset(dataset="test", content_id=0, asset_id=1,
workdir_root=VmafConfig.workdir_path(),
ref_path=ref_path,
dis_path=ref_path,
asset_dict={'width':576, 'height':324})
result_store = FileSystemResultStore(logger=None)
print ' running for the first time with fresh calculation...'
self.fextractor = VmafFeatureExtractor(
[asset, asset_original],
None, fifo_mode=True,
result_store=result_store
)
self.fextractor.run(parallelize=True)
results = self.fextractor.results
result0, result1 = results
self.assertTrue(os.path.exists(result_store._get_result_file_path(result0)))
self.assertTrue(os.path.exists(result_store._get_result_file_path(result1)))
print ' running for the second time with stored results...'
self.fextractor = VmafFeatureExtractor(
[asset, asset_original, asset],
None, fifo_mode=True,
result_store=result_store
)
self.fextractor.run(parallelize=True)
results = self.fextractor.results
self.assertAlmostEqual(results[0]['VMAF_feature_vif_score'], 0.4460930625, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_motion_score'], 4.04982535417, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm2_score'],0.93458780728708746, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_ansnr_score'], 23.5095715208, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_vif_num_score'], 712650.023478, places=0)
self.assertAlmostEqual(results[0]['VMAF_feature_vif_den_score'], 1597314.95249, places=0)
self.assertAlmostEqual(results[0]['VMAF_feature_adm_num_score'], 371.83541406249998, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm_den_score'], 397.83378972916671, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_anpsnr_score'], 34.164776875, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_vif_scale0_score'], 0.363420489439, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_vif_scale1_score'], 0.766647542135, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_vif_scale2_score'], 0.862854666902, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_vif_scale3_score'], 0.915971778036, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm_scale0_score'], 0.90791933424090698, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm_scale1_score'], 0.89395660507453423, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm_scale2_score'], 0.93010045185439161, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm_scale3_score'], 0.96503534602850938, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_vif2_score'], 0.72722361912801026, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm3_score'], 0.92425293429958566, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_motion_score'], 4.04982535417, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm2_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_ansnr_score'], 31.2714392708, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_num_score'], 1597314.86733, places=0)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_den_score'], 1597314.95249, places=0)
self.assertAlmostEqual(results[1]['VMAF_feature_adm_num_score'], 397.83378972916671, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm_den_score'], 397.83378972916671, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_anpsnr_score'], 41.9266444375, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_scale0_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_scale1_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_scale2_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_scale3_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm_scale0_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm_scale1_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm_scale2_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm_scale3_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif2_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm3_score'], 1.0, places=4)
self.assertAlmostEqual(results[2]['VMAF_feature_vif_score'], 0.4460930625, places=4)
def test_run_parallel_vmaf_fextractor_with_result_store(self):
ref_path, dis_path, asset, asset_original = set_default_576_324_videos_for_testing()
result_store = FileSystemResultStore(logger=None)
self.fextractor = VmafFeatureExtractor(
[asset, asset_original],
None, fifo_mode=True,
result_store=result_store
)
self.fextractor.run(parallelize=True)
results = self.fextractor.results
result0, result1 = results
self.assertTrue(os.path.exists(result_store._get_result_file_path(result0)))
self.assertTrue(os.path.exists(result_store._get_result_file_path(result1)))
self.fextractor = VmafFeatureExtractor(
[asset, asset_original, asset],
None, fifo_mode=True,
result_store=result_store
)
self.fextractor.run(parallelize=True)
results = self.fextractor.results
self.assertAlmostEqual(results[0]['VMAF_feature_vif_score'], 0.4460930625, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_motion_score'], 4.04982535417, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm2_score'], 0.9345149030293786, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_ansnr_score'], 23.5095715208, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_vif_num_score'], 712650.023478, places=0)
self.assertAlmostEqual(results[0]['VMAF_feature_vif_den_score'], 1597314.95249, places=0)
self.assertAlmostEqual(results[0]['VMAF_feature_adm_num_score'], 371.80645372916666, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm_den_score'], 397.83378972916671, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_anpsnr_score'], 34.164776875, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_vif_scale0_score'], 0.363420489439, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_vif_scale1_score'], 0.766647542135, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_vif_scale2_score'], 0.862854666902, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_vif_scale3_score'], 0.915971778036, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm_scale0_score'], 0.90791933424090698, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm_scale1_score'], 0.8938705209242691, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm_scale2_score'], 0.9300123587874962, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm_scale3_score'], 0.9649663148179196, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_vif2_score'], 0.72722361912801026, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm3_score'], 0.9241841443734412, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_motion_score'], 4.04982535417, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm2_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_ansnr_score'], 31.2714392708, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_num_score'], 1597314.86733, places=0)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_den_score'], 1597314.95249, places=0)
self.assertAlmostEqual(results[1]['VMAF_feature_adm_num_score'], 397.83378972916671, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm_den_score'], 397.83378972916671, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_anpsnr_score'], 41.9266444375, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_scale0_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_scale1_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_scale2_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_scale3_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm_scale0_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm_scale1_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm_scale2_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm_scale3_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif2_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm3_score'], 1.0, places=4)
self.assertAlmostEqual(results[2]['VMAF_feature_vif_score'], 0.4460930625, places=4)
def test_run_vmaf_fextractor_with_result_store(self):
print 'test on running VMAF feature extractor with result store...'
ref_path, dis_path, asset, asset_original = set_default_576_324_videos_for_testing()
result_store = FileSystemResultStore(logger=None)
self.fextractor = VmafFeatureExtractor(
[asset, asset_original],
None, fifo_mode=True,
result_store=result_store
)
print ' running for the first time with fresh calculation...'
self.fextractor.run()
result0, result1 = self.fextractor.results
self.assertTrue(os.path.exists(result_store._get_result_file_path(result0)))
self.assertTrue(os.path.exists(result_store._get_result_file_path(result1)))
print ' running for the second time with stored results...'
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['VMAF_feature_vif_score'], 0.4460930625, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_motion_score'], 4.04982535417, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_motion2_score'], 3.8953518541666665, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm2_score'],0.93458780728708746, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_ansnr_score'], 23.5095715208, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_vif_num_score'], 712650.023478, places=0)
self.assertAlmostEqual(results[0]['VMAF_feature_vif_den_score'], 1597314.95249, places=0)
self.assertAlmostEqual(results[0]['VMAF_feature_adm_num_score'], 371.83541406249998, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm_den_score'], 397.83378972916671, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_anpsnr_score'], 34.164776875, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_vif_scale0_score'], 0.363420489439, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_vif_scale1_score'], 0.766647542135, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_vif_scale2_score'], 0.862854666902, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_vif_scale3_score'], 0.915971778036, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm_scale0_score'], 0.90791933424090698, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm_scale1_score'], 0.89395660507453423, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm_scale2_score'], 0.93010045185439161, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm_scale3_score'], 0.96503534602850938, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_vif2_score'], 0.72722361912801026, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm3_score'], 0.92425293429958566, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_motion_score'], 4.04982535417, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_motion2_score'], 3.8953518541666665, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm2_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_ansnr_score'], 31.2714392708, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_num_score'], 1597314.86733, places=0)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_den_score'], 1597314.95249, places=0)
self.assertAlmostEqual(results[1]['VMAF_feature_adm_num_score'], 397.83378972916671, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm_den_score'], 397.83378972916671, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_anpsnr_score'], 41.9266444375, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_scale0_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_scale1_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_scale2_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_scale3_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm_scale0_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm_scale1_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm_scale2_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm_scale3_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif2_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm3_score'], 1.0, places=4)
def test_run_parallel_vamf_fextractor_with_result_store(self):
print 'test on running VMAF feature extractor with result store ' \
'in parallel...'
ref_path = VmafConfig.test_resource_path("yuv", "src01_hrc00_576x324.yuv")
dis_path = VmafConfig.test_resource_path("yuv", "src01_hrc01_576x324.yuv")
asset = Asset(dataset="test", content_id=0, asset_id=0,
workdir_root=VmafConfig.workdir_path(),
ref_path=ref_path,
dis_path=dis_path,
asset_dict={'width':576, 'height':324})
asset_original = Asset(dataset="test", content_id=0, asset_id=1,
workdir_root=VmafConfig.workdir_path(),
ref_path=ref_path,
dis_path=ref_path,
asset_dict={'width':576, 'height':324})
result_store = FileSystemResultStore(logger=None)
print ' running for the first time with fresh calculation...'
self.fextractor = VmafFeatureExtractor(
[asset, asset_original],
None, fifo_mode=True,
result_store=result_store
)
self.fextractor.run(parallelize=True)
results = self.fextractor.results
result0, result1 = results
self.assertTrue(os.path.exists(result_store._get_result_file_path(result0)))
self.assertTrue(os.path.exists(result_store._get_result_file_path(result1)))
print ' running for the second time with stored results...'
self.fextractor = VmafFeatureExtractor(
[asset, asset_original, asset],
None, fifo_mode=True,
result_store=result_store
)
self.fextractor.run(parallelize=True)
results = self.fextractor.results
self.assertAlmostEqual(results[0]['VMAF_feature_vif_score'], 0.4460930625, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_motion_score'], 4.04982535417, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm2_score'],0.93458780728708746, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_ansnr_score'], 23.5095715208, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_vif_num_score'], 712650.023478, places=0)
self.assertAlmostEqual(results[0]['VMAF_feature_vif_den_score'], 1597314.95249, places=0)
self.assertAlmostEqual(results[0]['VMAF_feature_adm_num_score'], 371.83541406249998, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm_den_score'], 397.83378972916671, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_anpsnr_score'], 34.164776875, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_vif_scale0_score'], 0.363420489439, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_vif_scale1_score'], 0.766647542135, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_vif_scale2_score'], 0.862854666902, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_vif_scale3_score'], 0.915971778036, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm_scale0_score'], 0.90791933424090698, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm_scale1_score'], 0.89395660507453423, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm_scale2_score'], 0.93010045185439161, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm_scale3_score'], 0.96503534602850938, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_vif2_score'], 0.72722361912801026, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_adm3_score'], 0.92425293429958566, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_motion_score'], 4.04982535417, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm2_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_ansnr_score'], 31.2714392708, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_num_score'], 1597314.86733, places=0)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_den_score'], 1597314.95249, places=0)
self.assertAlmostEqual(results[1]['VMAF_feature_adm_num_score'], 397.83378972916671, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm_den_score'], 397.83378972916671, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_anpsnr_score'], 41.9266444375, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_scale0_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_scale1_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_scale2_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_scale3_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm_scale0_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm_scale1_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm_scale2_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm_scale3_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif2_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_adm3_score'], 1.0, places=4)
self.assertAlmostEqual(results[2]['VMAF_feature_vif_score'], 0.4460930625, places=4)
