class ResultStoreTest(unittest.TestCase):
def setUp(self):
ref_path = VmafConfig.test_resource_path("yuv", "checkerboard_1920_1080_10_3_0_0.yuv")
dis_path = VmafConfig.test_resource_path("yuv", "checkerboard_1920_1080_10_3_1_0.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':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):
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.assertEqual(self.result, loaded_result)
def setUp(self):
ref_path = VmafConfig.test_resource_path(
"yuv", "checkerboard_1920_1080_10_3_0_0.yuv")
dis_path = VmafConfig.test_resource_path(
"yuv", "checkerboard_1920_1080_10_3_1_0.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': 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]
class ResultStoreTest(unittest.TestCase):
def setUp(self):
ref_path = VmafConfig.test_resource_path("yuv", "checkerboard_1920_1080_10_3_0_0.yuv")
dis_path = VmafConfig.test_resource_path("yuv", "checkerboard_1920_1080_10_3_1_0.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':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)
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 setUp(self):
ref_path = VmafConfig.test_resource_path("yuv", "checkerboard_1920_1080_10_3_0_0.yuv")
dis_path = VmafConfig.test_resource_path("yuv", "checkerboard_1920_1080_10_3_1_0.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':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]
class ResultTest(MyTestCase):
def setUp(self):
super().setUp()
ref_path = VmafConfig.test_resource_path(
"yuv", "checkerboard_1920_1080_10_3_0_0.yuv")
dis_path = VmafConfig.test_resource_path(
"yuv", "checkerboard_1920_1080_10_3_1_0.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': 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()
super().tearDown()
def test_todataframe_fromdataframe(self):
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.assertEqual(len(df), 38)
self.assertEqual(len(df_vmaf), 1)
self.assertEqual(len(df_adm), 1)
self.assertEqual(len(df_vif), 1)
self.assertEqual(len(df_ansnr), 1)
self.assertEqual(len(df_motion), 1)
self.assertAlmostEqual(np.mean(df_vmaf.iloc[0]['scores']),
40.421899030550769,
places=4)
self.assertAlmostEqual(np.mean(df_adm.iloc[0]['scores']),
0.78533833333333336,
places=4)
self.assertAlmostEqual(np.mean(df_vif.iloc[0]['scores']),
0.156834666667,
places=4)
self.assertAlmostEqual(np.mean(df_ansnr.iloc[0]['scores']),
7.92623066667,
places=4)
self.assertAlmostEqual(np.mean(df_motion.iloc[0]['scores']),
12.5548366667,
places=4)
self.assertAlmostEqual(np.mean(df_adm_den.iloc[0]['scores']),
2773.8912249999998,
places=3)
self.assertAlmostEqual(np.mean(
Result.get_unique_from_dataframe(df, 'VMAF_legacy_scores',
'scores')),
40.421899030550769,
places=4)
self.assertAlmostEqual(np.mean(
Result.get_unique_from_dataframe(df, 'VMAF_feature_adm_scores',
'scores')),
0.78533833333333336,
places=4)
self.assertAlmostEqual(np.mean(
Result.get_unique_from_dataframe(df, 'VMAF_feature_vif_scores',
'scores')),
0.156834666667,
places=4)
self.assertAlmostEqual(np.mean(
Result.get_unique_from_dataframe(df, 'VMAF_feature_ansnr_scores',
'scores')),
7.92623066667,
places=4)
self.assertAlmostEqual(np.mean(
Result.get_unique_from_dataframe(df, 'VMAF_feature_motion_scores',
'scores')),
12.5548366667,
places=4)
self.assertEqual(df.iloc[0]['dataset'], 'test')
self.assertEqual(df.iloc[0]['content_id'], 0)
self.assertEqual(df.iloc[0]['asset_id'], 0)
self.assertEqual(df.iloc[0]['ref_name'],
'checkerboard_1920_1080_10_3_0_0.yuv')
self.assertEqual(df.iloc[0]['dis_name'],
'checkerboard_1920_1080_10_3_1_0.yuv')
self.assertEqual(
df.iloc[0]['asset'],
'{"asset_dict": {"height": 1080, "use_path_as_workpath": 1, "use_workpath_as_procpath": 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": ""}'
) # noqa
self.assertEqual(df.iloc[0]['executor_id'], 'VMAF_legacy_VF0.2.7-1.1')
Result._assert_asset_dataframe(df)
recon_result = Result.from_dataframe(df)
self.assertEqual(self.result, recon_result)
self.assertTrue(self.result == recon_result)
self.assertFalse(self.result != recon_result)
def test_to_score_str(self):
self.assertAlmostEqual(self.result.get_result('VMAF_legacy_score'),
40.421899030550769,
places=4)
self.assertAlmostEqual(self.result['VMAF_legacy_score'],
40.421899030550769,
places=4)
self.assertAlmostEqual(
self.result.get_result('VMAF_feature_adm_score'),
0.78533833333333336,
places=4)
self.assertAlmostEqual(self.result['VMAF_feature_adm_score'],
0.78533833333333336,
places=4)
self.assertAlmostEqual(self.result['VMAF_feature_vif_score'],
0.15683466666666665,
places=4)
self.assertAlmostEqual(self.result['VMAF_feature_motion_score'],
12.5548366667,
places=4)
self.assertAlmostEqual(self.result['VMAF_feature_ansnr_score'],
7.92623066667,
places=4)
self.result.set_score_aggregate_method(np.min)
self.assertAlmostEqual(self.result.get_result('VMAF_legacy_score'),
37.573531379639725,
places=4)
self.result.set_score_aggregate_method(np.max)
self.assertAlmostEqual(self.result.get_result('VMAF_legacy_score'),
44.815357234059327,
places=4)
self.result.set_score_aggregate_method(np.median)
self.assertAlmostEqual(self.result.get_result('VMAF_legacy_score'),
38.876808477953254,
places=4)
self.result.set_score_aggregate_method(np.mean)
self.assertAlmostEqual(self.result.get_result('VMAF_legacy_score'),
40.421899030550769,
places=4)
self.result.set_score_aggregate_method(np.std)
self.assertAlmostEqual(self.result.get_result('VMAF_legacy_score'),
3.1518765879212993,
places=4)
self.result.set_score_aggregate_method(np.var)
self.assertAlmostEqual(self.result.get_result('VMAF_legacy_score'),
9.9343260254864134,
places=4)
self.result.set_score_aggregate_method(partial(np.percentile, q=50))
self.assertAlmostEqual(self.result.get_result('VMAF_legacy_score'),
38.876808477953254,
places=4)
self.result.set_score_aggregate_method(partial(np.percentile, q=80))
self.assertAlmostEqual(self.result.get_result('VMAF_legacy_score'),
42.439937731616901,
places=4)
self.result.set_score_aggregate_method(ListStats.total_variation)
self.assertAlmostEqual(self.result.get_result('VMAF_legacy_score'),
6.5901873052628375,
places=4)
self.result.set_score_aggregate_method(
partial(ListStats.moving_average, n=2))
self.assertEqual(
list(self.result.get_result('VMAF_legacy_score')),
[42.86773029545774, 42.86773029545774, 42.86773029545774])
with self.assertRaises(KeyError):
self.result.get_result('VVMAF_legacy_score')
with self.assertRaises(KeyError):
self.result.get_result('VMAF_motion_score')
class ResultTest(unittest.TestCase):
def setUp(self):
ref_path = VmafConfig.test_resource_path("yuv", "checkerboard_1920_1080_10_3_0_0.yuv")
dis_path = VmafConfig.test_resource_path("yuv", "checkerboard_1920_1080_10_3_1_0.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':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()
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), 38)
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']), 40.421899030550769, places=4)
self.assertAlmostEquals(np.mean(df_adm.iloc[0]['scores']), 0.78533833333333336, 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']), 2773.8912249999998, places=3)
self.assertAlmostEquals(np.mean(Result.get_unique_from_dataframe(df, 'VMAF_legacy_scores', 'scores')), 40.421899030550769, places=4)
self.assertAlmostEquals(np.mean(Result.get_unique_from_dataframe(df, 'VMAF_feature_adm_scores', 'scores')), 0.78533833333333336, 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": ""}') # noqa
self.assertEquals(df.iloc[0]['executor_id'], 'VMAF_legacy_VF0.2.4b-1.1')
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'), 40.421899030550769, places=4)
self.assertAlmostEquals(self.result['VMAF_legacy_score'], 40.421899030550769, places=4)
self.assertAlmostEquals(self.result.get_result('VMAF_feature_adm_score'), 0.78533833333333336, places=4)
self.assertAlmostEquals(self.result['VMAF_feature_adm_score'], 0.78533833333333336, 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'), 37.573531379639725, places=4)
self.result.set_score_aggregate_method(np.max)
self.assertAlmostEquals(self.result.get_result('VMAF_legacy_score'), 44.815357234059327, places=4)
self.result.set_score_aggregate_method(np.median)
self.assertAlmostEquals(self.result.get_result('VMAF_legacy_score'), 38.876808477953254, places=4)
self.result.set_score_aggregate_method(np.mean)
self.assertAlmostEquals(self.result.get_result('VMAF_legacy_score'), 40.421899030550769, places=4)
self.result.set_score_aggregate_method(np.std)
self.assertAlmostEquals(self.result.get_result('VMAF_legacy_score'), 3.1518765879212993, places=4)
self.result.set_score_aggregate_method(np.var)
self.assertAlmostEquals(self.result.get_result('VMAF_legacy_score'), 9.9343260254864134, places=4)
self.result.set_score_aggregate_method(partial(np.percentile, q=50))
self.assertAlmostEquals(self.result.get_result('VMAF_legacy_score'), 38.876808477953254, places=4)
self.result.set_score_aggregate_method(partial(np.percentile, q=80))
self.assertAlmostEquals(self.result.get_result('VMAF_legacy_score'), 42.439937731616901, places=4)
self.result.set_score_aggregate_method(ListStats.total_variation)
self.assertAlmostEquals(self.result.get_result('VMAF_legacy_score'), 6.5901873052628375, places=4)
self.result.set_score_aggregate_method(partial(ListStats.moving_average, n=2))
self.assertItemsEqual(self.result.get_result('VMAF_legacy_score'),
[42.86773029545774, 42.86773029545774, 42.86773029545774])
with self.assertRaises(KeyError):
self.result.get_result('VVMAF_legacy_score')
with self.assertRaises(KeyError):
self.result.get_result('VMAF_motion_scor')
