class ResultStoreTest(unittest.TestCase):
def setUp(self):
ref_path = config.ROOT + "/resource/yuv/checkerboard_1920_1080_10_3_0_0.yuv"
dis_path = config.ROOT + "/resource/yuv/checkerboard_1920_1080_10_3_1_0.yuv"
asset = Asset(dataset="test", content_id=0, asset_id=0,
workdir_root=config.ROOT + "/workspace/workdir",
ref_path=ref_path,
dis_path=dis_path,
asset_dict={'width':1920, 'height':1080})
self.runner = VmafLegacyQualityRunner(
[asset], None, fifo_mode=True,
delete_workdir=True, result_store=None,
)
self.runner.run()
self.result = self.runner.results[0]
def tearDown(self):
if hasattr(self, 'result') and hasattr(self, 'result_store'):
self.result_store.delete(self.result.asset, self.result.executor_id)
pass
def test_file_system_result_store_save_load(self):
print 'test on file system result store save and load...'
self.result_store = FileSystemResultStore(logger=None)
asset = self.result.asset
executor_id = self.result.executor_id
self.result_store.save(self.result)
loaded_result = self.result_store.load(asset, executor_id)
self.assertEquals(self.result, loaded_result)
class ResultTest(unittest.TestCase):
def setUp(self):
ref_path = config.ROOT + "/resource/yuv/checkerboard_1920_1080_10_3_0_0.yuv"
dis_path = config.ROOT + "/resource/yuv/checkerboard_1920_1080_10_3_1_0.yuv"
asset = Asset(dataset="test", content_id=0, asset_id=0,
workdir_root=config.ROOT + "/workspace/workdir",
ref_path=ref_path,
dis_path=dis_path,
asset_dict={'width':1920, 'height':1080})
self.runner = VmafLegacyQualityRunner(
[asset], None, fifo_mode=True,
delete_workdir=True, result_store=FileSystemResultStore(),
)
self.runner.run()
self.result = self.runner.results[0]
def tearDown(self):
if hasattr(self, 'runner'):
self.runner.remove_results()
pass
def test_todataframe_fromdataframe(self):
print 'test on result to/from dataframe...'
df = self.result.to_dataframe()
df_vmaf = df.loc[df['scores_key'] == 'VMAF_legacy_scores']
df_adm = df.loc[df['scores_key'] == 'VMAF_feature_adm_scores']
df_vif = df.loc[df['scores_key'] == 'VMAF_feature_vif_scores']
df_ansnr = df.loc[df['scores_key'] == 'VMAF_feature_ansnr_scores']
df_motion = df.loc[df['scores_key'] == 'VMAF_feature_motion_scores']
df_adm_den = df.loc[df['scores_key'] == 'VMAF_feature_adm_den_scores']
self.assertEquals(len(df), 37)
self.assertEquals(len(df_vmaf), 1)
self.assertEquals(len(df_adm), 1)
self.assertEquals(len(df_vif), 1)
self.assertEquals(len(df_ansnr), 1)
self.assertEquals(len(df_motion), 1)
self.assertAlmostEquals(np.mean(df_vmaf.iloc[0]['scores']), 44.4942308947, places=4)
self.assertAlmostEquals(np.mean(df_adm.iloc[0]['scores']), 0.813856666667, places=4)
self.assertAlmostEquals(np.mean(df_vif.iloc[0]['scores']), 0.156834666667, places=4)
self.assertAlmostEquals(np.mean(df_ansnr.iloc[0]['scores']), 7.92623066667, places=4)
self.assertAlmostEquals(np.mean(df_motion.iloc[0]['scores']), 12.5548366667, places=4)
self.assertAlmostEquals(np.mean(df_adm_den.iloc[0]['scores']), 30814.9100813, places=3)
self.assertAlmostEquals(np.mean(Result.get_unique_from_dataframe(df, 'VMAF_legacy_scores', 'scores')), 44.4942308947, places=4)
self.assertAlmostEquals(np.mean(Result.get_unique_from_dataframe(df, 'VMAF_feature_adm_scores', 'scores')), 0.813856666667, places=4)
self.assertAlmostEquals(np.mean(Result.get_unique_from_dataframe(df, 'VMAF_feature_vif_scores', 'scores')), 0.156834666667, places=4)
self.assertAlmostEquals(np.mean(Result.get_unique_from_dataframe(df, 'VMAF_feature_ansnr_scores', 'scores')), 7.92623066667, places=4)
self.assertAlmostEquals(np.mean(Result.get_unique_from_dataframe(df, 'VMAF_feature_motion_scores', 'scores')), 12.5548366667, places=4)
self.assertEquals(df.iloc[0]['dataset'], 'test')
self.assertEquals(df.iloc[0]['content_id'], 0)
self.assertEquals(df.iloc[0]['asset_id'], 0)
self.assertEquals(df.iloc[0]['ref_name'], 'checkerboard_1920_1080_10_3_0_0.yuv')
self.assertEquals(df.iloc[0]['dis_name'], 'checkerboard_1920_1080_10_3_1_0.yuv')
self.assertEquals(
df.iloc[0]['asset'],
'{"asset_dict": {"height": 1080, "use_path_as_workpath": 1, "width": 1920}, "asset_id": 0, "content_id": 0, "dataset": "test", "dis_path": "checkerboard_1920_1080_10_3_1_0.yuv", "ref_path": "checkerboard_1920_1080_10_3_0_0.yuv", "workdir": ""}')
self.assertEquals(df.iloc[0]['executor_id'], 'VMAF_legacy_V1.2')
Result._assert_asset_dataframe(df)
recon_result = Result.from_dataframe(df)
self.assertEquals(self.result, recon_result)
self.assertTrue(self.result == recon_result)
self.assertFalse(self.result != recon_result)
def test_to_score_str(self):
print 'test on result aggregate scores...'
self.assertAlmostEquals(self.result.get_result('VMAF_legacy_score'), 44.494230894688833 , places=4)
self.assertAlmostEquals(self.result['VMAF_legacy_score'], 44.494230894688833, places=4)
self.assertAlmostEquals(self.result.get_result('VMAF_feature_adm_score'), 0.81386, places=4)
self.assertAlmostEquals(self.result['VMAF_feature_adm_score'], 0.81386, places=4)
self.assertAlmostEquals(self.result['VMAF_feature_vif_score'], 0.15683466666666665 , places=4)
self.assertAlmostEquals(self.result['VMAF_feature_motion_score'], 12.5548366667, places=4)
self.assertAlmostEquals(self.result['VMAF_feature_ansnr_score'], 7.92623066667, places=4)
self.result.set_score_aggregate_method(np.min)
self.assertAlmostEquals(self.result.get_result('VMAF_legacy_score'), 42.084764558485965, places=4)
self.result.set_score_aggregate_method(np.max)
self.assertAlmostEquals(self.result.get_result('VMAF_legacy_score'), 48.701976416017928, places=4)
self.result.set_score_aggregate_method(np.median)
self.assertAlmostEquals(self.result.get_result('VMAF_legacy_score'), 42.695951709562614, places=4)
self.result.set_score_aggregate_method(np.mean)
self.assertAlmostEquals(self.result.get_result('VMAF_legacy_score'), 44.494230894688833, places=4)
self.result.set_score_aggregate_method(np.std)
self.assertAlmostEquals(self.result.get_result('VMAF_legacy_score'), 2.9857694946316129, places=4)
self.result.set_score_aggregate_method(np.var)
self.assertAlmostEquals(self.result.get_result('VMAF_legacy_score'), 8.9148194750727168, places=4)
self.result.set_score_aggregate_method(partial(np.percentile, q=50))
self.assertAlmostEquals(self.result.get_result('VMAF_legacy_score'), 42.695951709562614, places=4)
self.result.set_score_aggregate_method(partial(np.percentile, q=80))
self.assertAlmostEquals(self.result.get_result('VMAF_legacy_score'), 46.299566533435808, places=4)
self.result.set_score_aggregate_method(ListStats.total_variation)
self.assertAlmostEquals(self.result.get_result('VMAF_legacy_score'), 6.3116182819936384, places=4)
self.result.set_score_aggregate_method(partial(ListStats.moving_average, n=2))
self.assertItemsEqual(self.result.get_result('VMAF_legacy_score'),
[46.922334053546891, 46.922334053546891, 46.922334053546891])
with self.assertRaises(KeyError):
self.result.get_result('VVMAF_legacy_score')
with self.assertRaises(KeyError):
self.result.get_result('VMAF_motion_scor')
class ResultTest(unittest.TestCase):
def setUp(self):
ref_path = config.ROOT + "/resource/yuv/checkerboard_1920_1080_10_3_0_0.yuv"
dis_path = config.ROOT + "/resource/yuv/checkerboard_1920_1080_10_3_1_0.yuv"
asset = Asset(dataset="test", content_id=0, asset_id=0,
workdir_root=config.ROOT + "/workspace/workdir",
ref_path=ref_path,
dis_path=dis_path,
asset_dict={'width':1920, 'height':1080})
self.runner = VmafLegacyQualityRunner(
[asset], None, fifo_mode=True,
delete_workdir=True, result_store=FileSystemResultStore(),
)
self.runner.run()
self.result = self.runner.results[0]
def tearDown(self):
if hasattr(self, 'runner'):
self.runner.remove_results()
pass
def test_todataframe_fromdataframe(self):
print 'test on result to/from dataframe...'
df = self.result.to_dataframe()
df_vmaf = df.loc[df['scores_key'] == 'VMAF_legacy_scores']
df_adm = df.loc[df['scores_key'] == 'VMAF_feature_adm_scores']
df_vif = df.loc[df['scores_key'] == 'VMAF_feature_vif_scores']
df_ansnr = df.loc[df['scores_key'] == 'VMAF_feature_ansnr_scores']
df_motion = df.loc[df['scores_key'] == 'VMAF_feature_motion_scores']
df_adm_den = df.loc[df['scores_key'] == 'VMAF_feature_adm_den_scores']
self.assertEquals(len(df), 24)
self.assertEquals(len(df_vmaf), 1)
self.assertEquals(len(df_adm), 1)
self.assertEquals(len(df_vif), 1)
self.assertEquals(len(df_ansnr), 1)
self.assertEquals(len(df_motion), 1)
self.assertAlmostEquals(np.mean(df_vmaf.iloc[0]['scores']), 43.460998585018046)
self.assertAlmostEquals(np.mean(df_adm.iloc[0]['scores']), 0.81386000000000003)
self.assertAlmostEquals(np.mean(df_vif.iloc[0]['scores']), 0.15612933333333334)
self.assertAlmostEquals(np.mean(df_ansnr.iloc[0]['scores']), 12.418291000000002)
self.assertAlmostEquals(np.mean(df_motion.iloc[0]['scores']), 12.343795333333333)
self.assertAlmostEquals(np.mean(df_adm_den.iloc[0]['scores']), 30814.909660333331)
self.assertAlmostEquals(np.mean(Result.get_unique_from_dataframe(df, 'VMAF_legacy_scores', 'scores')), 43.460998585018046)
self.assertAlmostEquals(np.mean(Result.get_unique_from_dataframe(df, 'VMAF_feature_adm_scores', 'scores')), 0.81386000000000003)
self.assertAlmostEquals(np.mean(Result.get_unique_from_dataframe(df, 'VMAF_feature_vif_scores', 'scores')), 0.15612933333333334)
self.assertAlmostEquals(np.mean(Result.get_unique_from_dataframe(df, 'VMAF_feature_ansnr_scores', 'scores')), 12.418291000000002)
self.assertAlmostEquals(np.mean(Result.get_unique_from_dataframe(df, 'VMAF_feature_motion_scores', 'scores')), 12.343795333333333)
self.assertEquals(df.iloc[0]['dataset'], 'test')
self.assertEquals(df.iloc[0]['content_id'], 0)
self.assertEquals(df.iloc[0]['asset_id'], 0)
self.assertEquals(df.iloc[0]['ref_name'], 'checkerboard_1920_1080_10_3_0_0.yuv')
self.assertEquals(df.iloc[0]['dis_name'], 'checkerboard_1920_1080_10_3_1_0.yuv')
self.assertEquals(
df.iloc[0]['asset'],
'{"asset_dict": {"height": 1080, "use_path_as_workpath": 1, "width": 1920}, "asset_id": 0, "content_id": 0, "dataset": "test", "dis_path": "checkerboard_1920_1080_10_3_1_0.yuv", "ref_path": "checkerboard_1920_1080_10_3_0_0.yuv", "workdir": ""}')
self.assertEquals(df.iloc[0]['executor_id'], 'VMAF_legacy_V1.0')
Result._assert_asset_dataframe(df)
recon_result = Result.from_dataframe(df)
self.assertEquals(self.result, recon_result)
self.assertTrue(self.result == recon_result)
self.assertFalse(self.result != recon_result)
def test_to_score_str(self):
print 'test on result aggregate scores...'
self.assertAlmostEquals(self.result.get_score('VMAF_legacy_score'), 43.46099858501805)
self.assertAlmostEquals(self.result['VMAF_legacy_score'], 43.46099858501805)
self.assertAlmostEquals(self.result.get_score('VMAF_feature_adm_score'), 0.81386)
self.assertAlmostEquals(self.result['VMAF_feature_adm_score'], 0.81386)
self.assertAlmostEquals(self.result['VMAF_feature_vif_score'], 0.15612933333333334)
self.assertAlmostEquals(self.result['VMAF_feature_motion_score'], 12.343795333333333)
self.assertAlmostEquals(self.result['VMAF_feature_ansnr_score'], 12.418291000000002)
self.result.set_aggregate_method(np.min)
self.assertAlmostEquals(self.result.get_score('VMAF_legacy_score'), 40.616811853256458)
self.result.set_aggregate_method(np.max)
self.assertAlmostEquals(self.result.get_score('VMAF_legacy_score'), 47.654468953859656)
self.result.set_aggregate_method(np.median)
self.assertAlmostEquals(self.result.get_score('VMAF_legacy_score'), 42.111714947938026)
self.result.set_aggregate_method(np.mean)
self.assertAlmostEquals(self.result.get_score('VMAF_legacy_score'), 43.460998585018046)
self.result.set_aggregate_method(np.std)
self.assertAlmostEquals(self.result.get_score('VMAF_legacy_score'), 3.0273838118510366)
self.result.set_aggregate_method(np.var)
self.assertAlmostEquals(self.result.get_score('VMAF_legacy_score'), 9.1650527442577125)
self.result.set_aggregate_method(partial(np.percentile, q=50))
self.assertAlmostEquals(self.result.get_score('VMAF_legacy_score'), 42.111714947938026)
self.result.set_aggregate_method(partial(np.percentile, q=80))
self.assertAlmostEquals(self.result.get_score('VMAF_legacy_score'), 45.437367351491005)
self.result.set_aggregate_method(ListStats.total_variation)
self.assertAlmostEquals(self.result.get_score('VMAF_legacy_score'), 6.2902055532624139)
self.result.set_aggregate_method(partial(ListStats.moving_average, n=2))
self.assertItemsEqual(self.result.get_score('VMAF_legacy_score'),
[45.76175145010879, 45.76175145010879, 45.76175145010879])
with self.assertRaises(KeyError):
self.result.get_score('VVMAF_legacy_score')
with self.assertRaises(KeyError):
self.result.get_score('VMAF_motion_scor')
