def test_noref_moment_fextractor_proc(self):
ref_path, dis_path, asset, asset_original = set_default_576_324_videos_for_testing()
callback_dict = {
'dis_proc_callback': 'identity',
}
asset.asset_dict.update(callback_dict)
asset_original.asset_dict.update(callback_dict)
self.fextractor = MomentNorefFeatureExtractor(
[asset, asset_original],
None, fifo_mode=True,
result_store=None
)
self.fextractor.run(parallelize=True)
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'], 61.332006624999984)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'], 4798.659574041666)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'], 1036.8371843488285)
self.assertAlmostEqual(results[1]['Moment_noref_feature_1st_score'], 59.788567297525134)
self.assertAlmostEqual(results[1]['Moment_noref_feature_2nd_score'], 4696.668388042271)
self.assertAlmostEqual(results[1]['Moment_noref_feature_var_score'], 1121.519917231207)
def test_noref_moment_fextractor_with_noref_asset(self):
print 'test on running Moment noref feature extractor on NorefAssets...'
ref_path = VmafConfig.test_resource_path("yuv", "src01_hrc00_576x324.yuv")
dis_path = VmafConfig.test_resource_path("yuv", "src01_hrc01_576x324.yuv")
asset = NorefAsset(dataset="test", content_id=0, asset_id=0,
workdir_root=VmafConfig.workdir_path(),
dis_path=dis_path,
asset_dict={'width':576, 'height':324})
asset_original = NorefAsset(dataset="test", content_id=0, asset_id=1,
workdir_root=VmafConfig.workdir_path(),
dis_path=ref_path,
asset_dict={'width':576, 'height':324})
self.fextractor = MomentNorefFeatureExtractor(
[asset, asset_original],
None, fifo_mode=True,
result_store=None
)
self.fextractor.run(parallelize=True)
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'], 61.332006624999984)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'], 4798.659574041666)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'], 1036.8371843488285)
self.assertAlmostEqual(results[1]['Moment_noref_feature_1st_score'], 59.788567297525134)
self.assertAlmostEqual(results[1]['Moment_noref_feature_2nd_score'], 4696.668388042271)
self.assertAlmostEqual(results[1]['Moment_noref_feature_var_score'], 1121.519917231207)
def test_run_parallel_moment_noref_fextractor(self):
ref_path, dis_path, asset, asset_original = set_default_576_324_videos_for_testing(
)
fextractor = MomentNorefFeatureExtractor(
[asset, asset_original],
None,
fifo_mode=True,
delete_workdir=True,
result_store=None,
)
self.fextractors = [fextractor]
fextractor.run(parallelize=True)
results = fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'],
61.332006624999984)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'],
4798.659574041666)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'],
1036.8371843488285)
self.assertAlmostEqual(results[1]['Moment_noref_feature_1st_score'],
59.788567297525134)
self.assertAlmostEqual(results[1]['Moment_noref_feature_2nd_score'],
4696.668388042271)
self.assertAlmostEqual(results[1]['Moment_noref_feature_var_score'],
1121.519917231207)
def test_noref_moment_fextractor_with_noref_asset_notyuv(self):
print 'test on running Moment noref feature extractor on NorefAssets ' \
'(non-YUV)...'
dis_path = VmafConfig.test_resource_path("mp4",
"Seeking_10_288_375.mp4")
asset = NorefAsset(dataset="test",
content_id=0,
asset_id=0,
workdir_root=VmafConfig.workdir_path(),
dis_path=dis_path,
asset_dict={
'yuv_type': 'notyuv',
'quality_width': 720,
'quality_height': 480,
})
self.fextractor = MomentNorefFeatureExtractor([asset],
None,
fifo_mode=True,
result_store=None)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'],
63.763580381944436,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'],
5158.9407083526221,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'],
1084.1635630076041,
places=4)
def test_noref_moment_fextractor_with_noref_asset(self):
print(
'test on running Moment noref feature extractor on NorefAssets...')
ref_path, dis_path, asset, asset_original = set_default_576_324_videos_for_testing(
)
self.fextractor = MomentNorefFeatureExtractor([asset, asset_original],
None,
fifo_mode=True,
result_store=None)
self.fextractor.run(parallelize=True)
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'],
61.332006624999984)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'],
4798.659574041666)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'],
1036.8371843488285)
self.assertAlmostEqual(results[1]['Moment_noref_feature_1st_score'],
59.788567297525134)
self.assertAlmostEqual(results[1]['Moment_noref_feature_2nd_score'],
4696.668388042271)
self.assertAlmostEqual(results[1]['Moment_noref_feature_var_score'],
1121.519917231207)
def test_noref_moment_fextractor_with_noref_asset_notyuv_gaussianblur(
self):
dis_path = VmafConfig.test_resource_path("mp4",
"Seeking_10_288_375.mp4")
asset = NorefAsset(dataset="test",
content_id=0,
asset_id=0,
workdir_root=VmafConfig.workdir_path(),
dis_path=dis_path,
asset_dict={
'yuv_type': 'notyuv',
'quality_width': 720,
'quality_height': 480,
'gblur_cmd': 'sigma=0.01:steps=1',
})
self.fextractor = MomentNorefFeatureExtractor([asset],
None,
fifo_mode=False,
result_store=None)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'],
63.25902145061728,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'],
5123.705637307099,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'],
1113.0346638689637,
places=4)
def test_noref_moment_fextractor_with_noref_asset_notyuv(self):
dis_path = VmafConfig.test_resource_path("mp4",
"Seeking_10_288_375.mp4")
asset = NorefAsset(dataset="test",
content_id=0,
asset_id=0,
workdir_root=VmafConfig.workdir_path(),
dis_path=dis_path,
asset_dict={
'yuv_type': 'notyuv',
'quality_width': 720,
'quality_height': 480,
})
self.fextractor = MomentNorefFeatureExtractor(
[asset],
None,
fifo_mode=False, # TODO python3: fifo mode fails in py3, needs fix
result_store=None)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'],
63.776442013888882,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'],
5194.9118422453694,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'],
1118.4952858425261,
places=4)
def test_noref_moment_fextractor_frames(self):
dis_path = VmafConfig.test_resource_path("yuv",
"src01_hrc01_576x324.yuv")
asset = NorefAsset(dataset="test",
content_id=0,
asset_id=0,
workdir_root=VmafConfig.workdir_path(),
dis_path=dis_path,
asset_dict={
'width': 576,
'height': 324,
'start_frame': 2,
'end_frame': 2,
})
self.fextractor = MomentNorefFeatureExtractor(
[asset],
None,
fifo_mode=False, # TODO python3: fifo mode fails in py3, needs fix
result_store=None)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'],
62.315495327503427,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'],
4888.7623296039092,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'],
1005.5413716918079,
places=4)
def test_run_parallel_moment_noref_fextractor(self):
print 'test on running Moment noref feature extractor on NorefAssets 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 = NorefAsset(dataset="test", content_id=0, asset_id=0,
workdir_root=VmafConfig.workdir_path(),
dis_path=dis_path,
asset_dict={'width':576, 'height':324})
asset_original = NorefAsset(dataset="test", content_id=0, asset_id=1,
workdir_root=VmafConfig.workdir_path(),
dis_path=ref_path,
asset_dict={'width':576, 'height':324})
fextractor = MomentNorefFeatureExtractor(
[asset, asset_original],
None,
fifo_mode=True,
delete_workdir=True,
result_store=None,
)
self.fextractors = [fextractor]
fextractor.run(parallelize=True)
results = fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'], 61.332006624999984)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'], 4798.659574041666)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'], 1036.8371843488285)
self.assertAlmostEqual(results[1]['Moment_noref_feature_1st_score'], 59.788567297525134)
self.assertAlmostEqual(results[1]['Moment_noref_feature_2nd_score'], 4696.668388042271)
self.assertAlmostEqual(results[1]['Moment_noref_feature_var_score'], 1121.519917231207)
def test_noref_moment_fextractor_with_noref_asset_notyuv_gaussianblur(
self):
dis_path = VmafConfig.test_resource_path("mp4",
"Seeking_10_288_375.mp4")
asset = NorefAsset(dataset="test",
content_id=0,
asset_id=0,
workdir_root=VmafConfig.workdir_path(),
dis_path=dis_path,
asset_dict={
'yuv_type': 'notyuv',
'quality_width': 720,
'quality_height': 480,
'gblur_cmd': 'sigma=0.01:steps=1',
})
self.fextractor = MomentNorefFeatureExtractor([asset],
None,
fifo_mode=True,
result_store=None)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'],
63.273978452932084,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'],
5124.572291840278,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'],
1111.9962740092349,
places=4)
def test_explain_train_test_model(self):
model_class = SklearnRandomForestTrainTestModel
train_dataset_path = VmafConfig.test_resource_path('test_image_dataset_diffdim.py')
train_dataset = import_python_file(train_dataset_path)
train_assets = read_dataset(train_dataset)
fextractor = MomentNorefFeatureExtractor(
train_assets,
None,
fifo_mode=True,
delete_workdir=True,
result_store=None,
optional_dict=None,
optional_dict2=None,
)
fextractor.run(parallelize=True)
self.features = fextractor.results
xys = model_class.get_xys_from_results(self.features[:7])
model = model_class({'norm_type':'normalize', 'random_state':0}, None)
model.train(xys)
np.random.seed(0)
xs = model_class.get_xs_from_results(self.features[7:])
explainer = LocalExplainer(neighbor_samples=1000)
exps = explainer.explain(model, xs)
self.assertAlmostEqual(exps['feature_weights'][0, 0], -0.12416, places=4)
self.assertAlmostEqual(exps['feature_weights'][1, 0], 0.00076, places=4)
self.assertAlmostEqual(exps['feature_weights'][0, 1], -0.20931, places=4)
self.assertAlmostEqual(exps['feature_weights'][1, 1], -0.01245, places=4)
self.assertAlmostEqual(exps['feature_weights'][0, 2], 0.02322, places=4)
self.assertAlmostEqual(exps['feature_weights'][1, 2], 0.03673, places=4)
self.assertAlmostEqual(exps['features'][0, 0], 107.73501, places=4)
self.assertAlmostEqual(exps['features'][1, 0], 35.81638, places=4)
self.assertAlmostEqual(exps['features'][0, 1], 13691.23881, places=4)
self.assertAlmostEqual(exps['features'][1, 1], 1611.56764, places=4)
self.assertAlmostEqual(exps['features'][0, 2], 2084.40542, places=4)
self.assertAlmostEqual(exps['features'][1, 2], 328.75389, places=4)
self.assertAlmostEqual(exps['features_normalized'][0, 0], -0.65527, places=4)
self.assertAlmostEqual(exps['features_normalized'][1, 0], -3.74922, places=4)
self.assertAlmostEqual(exps['features_normalized'][0, 1], -0.68872, places=4)
self.assertAlmostEqual(exps['features_normalized'][1, 1], -2.79586, places=4)
self.assertAlmostEqual(exps['features_normalized'][0, 2], 0.08524, places=4)
self.assertAlmostEqual(exps['features_normalized'][1, 2], -1.32625, places=4)
self.assertEqual(exps['feature_names'],
['Moment_noref_feature_1st_score',
'Moment_noref_feature_2nd_score',
'Moment_noref_feature_var_score']
)
def test_explain_train_test_model(self):
model_class = SklearnRandomForestTrainTestModel
train_dataset_path = VmafConfig.test_resource_path('test_image_dataset_diffdim.py')
train_dataset = import_python_file(train_dataset_path)
train_assets = read_dataset(train_dataset)
fextractor = MomentNorefFeatureExtractor(
train_assets,
None,
fifo_mode=True,
delete_workdir=True,
result_store=None,
optional_dict=None,
optional_dict2=None,
)
fextractor.run(parallelize=True)
self.features = fextractor.results
xys = model_class.get_xys_from_results(self.features[:7])
model = model_class({'norm_type':'normalize', 'random_state':0}, None)
model.train(xys)
np.random.seed(0)
xs = model_class.get_xs_from_results(self.features[7:])
explainer = LocalExplainer(neighbor_samples=1000)
exps = explainer.explain(model, xs)
self.assertAlmostEqual(exps['feature_weights'][0, 0], -0.12416, places=4)
self.assertAlmostEqual(exps['feature_weights'][1, 0], 0.00076, places=4)
self.assertAlmostEqual(exps['feature_weights'][0, 1], -0.20931, places=4)
self.assertAlmostEqual(exps['feature_weights'][1, 1], -0.01245, places=4)
self.assertAlmostEqual(exps['feature_weights'][0, 2], 0.02322, places=4)
self.assertAlmostEqual(exps['feature_weights'][1, 2], 0.03673, places=4)
self.assertAlmostEqual(exps['features'][0, 0], 107.73501, places=4)
self.assertAlmostEqual(exps['features'][1, 0], 35.81638, places=4)
self.assertAlmostEqual(exps['features'][0, 1], 13691.23881, places=4)
self.assertAlmostEqual(exps['features'][1, 1], 1611.56764, places=4)
self.assertAlmostEqual(exps['features'][0, 2], 2084.40542, places=4)
self.assertAlmostEqual(exps['features'][1, 2], 328.75389, places=4)
self.assertAlmostEqual(exps['features_normalized'][0, 0], -0.65527, places=4)
self.assertAlmostEqual(exps['features_normalized'][1, 0], -3.74922, places=4)
self.assertAlmostEqual(exps['features_normalized'][0, 1], -0.68872, places=4)
self.assertAlmostEqual(exps['features_normalized'][1, 1], -2.79586, places=4)
self.assertAlmostEqual(exps['features_normalized'][0, 2], 0.08524, places=4)
self.assertAlmostEqual(exps['features_normalized'][1, 2], -1.32625, places=4)
self.assertEqual(exps['feature_names'],
['Moment_noref_feature_1st_score',
'Moment_noref_feature_2nd_score',
'Moment_noref_feature_var_score']
)
class NorefFeatureExtractorTest(unittest.TestCase):
def tearDown(self):
if hasattr(self, 'fextractor'):
self.fextractor.remove_results()
pass
def test_noref_moment_fextractor_with_noref_asset_notyuv(self):
print 'test on running Moment noref feature extractor on NorefAssets ' \
'(non-YUV)...'
dis_path = VmafConfig.test_resource_path("mp4", "Seeking_10_288_375.mp4")
asset = NorefAsset(dataset="test", content_id=0, asset_id=0,
workdir_root=VmafConfig.workdir_path(),
dis_path=dis_path,
asset_dict={'yuv_type': 'notyuv',
'quality_width': 720, 'quality_height': 480,
})
self.fextractor = MomentNorefFeatureExtractor(
[asset],
None, fifo_mode=True,
result_store=None
)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'], 63.763580381944436, places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'], 5158.9407083526221, places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'], 1084.1635630076041, places=4)
def test_noref_moment_fextractor_frames(self):
print 'test on running Moment noref feature extractor on Assets with frames...'
dis_path = VmafConfig.test_resource_path("yuv", "src01_hrc01_576x324.yuv")
asset = NorefAsset(dataset="test", content_id=0, asset_id=0,
workdir_root=VmafConfig.workdir_path(),
dis_path=dis_path,
asset_dict={'width':576, 'height':324,
'start_frame':2, 'end_frame':2,
})
self.fextractor = MomentNorefFeatureExtractor(
[asset],
None, fifo_mode=True,
result_store=None
)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'], 62.315495327503427, places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'], 4888.7623296039092, places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'], 1005.5413716918079, places=4)
def test_run_noref_niqe_fextractor_with_patch_size(self):
ref_path, dis_path, asset, asset_original = set_default_576_324_videos_for_testing()
self.fextractor = NiqeNorefFeatureExtractor(
[asset, asset_original],
None, fifo_mode=False,
result_store=None,
optional_dict={'patch_size': 48},
optional_dict2=None,
)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['NIQE_noref_feature_alpha23_score'], 0.8430156250000006, places=4)
self.assertAlmostEqual(results[0]['NIQE_noref_feature_alpha13_score'], 0.71714583333333359, places=4)
self.assertAlmostEqual(results[0]['NIQE_noref_feature_alpha_m1_score'], 2.2195590277777795, places=4)
self.assertAlmostEqual(results[0]['NIQE_noref_feature_blbr1_score'], 0.74061215376929412, places=4)
self.assertAlmostEqual(results[1]['NIQE_noref_feature_alpha23_score'], 0.9144918981481488, places=4)
self.assertAlmostEqual(results[1]['NIQE_noref_feature_alpha13_score'], 0.87132291666666728, places=4)
self.assertAlmostEqual(results[1]['NIQE_noref_feature_alpha_m1_score'], 2.8193532986111136, places=4)
self.assertAlmostEqual(results[1]['NIQE_noref_feature_blbr1_score'], 0.99354006450609134, places=4)
def test_run_noref_niqe_fextractor_train(self):
ref_path, dis_path, asset, asset_original = set_default_576_324_videos_for_testing()
self.fextractor = NiqeNorefFeatureExtractor(
[asset, asset_original],
None, fifo_mode=False,
result_store=None,
optional_dict={'mode': 'train'},
optional_dict2=None,
)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['NIQE_noref_feature_alpha23_score'], 0.97259000000000073, places=4)
self.assertAlmostEqual(results[0]['NIQE_noref_feature_alpha13_score'], 0.80907000000000051, places=4)
self.assertAlmostEqual(results[0]['NIQE_noref_feature_alpha_m1_score'], 2.6135250000000019, places=4)
self.assertAlmostEqual(results[0]['NIQE_noref_feature_blbr1_score'], 0.9150526409258144, places=4)
self.assertAlmostEqual(results[1]['NIQE_noref_feature_alpha23_score'], 0.97447727272727347, places=4)
self.assertAlmostEqual(results[1]['NIQE_noref_feature_alpha13_score'], 0.89120909090909162, places=4)
self.assertAlmostEqual(results[1]['NIQE_noref_feature_alpha_m1_score'], 3.0300909090909118, places=4)
self.assertAlmostEqual(results[1]['NIQE_noref_feature_blbr1_score'], 1.0508255408831713, places=4)
def setUp(self):
train_dataset_path = VmafConfig.test_resource_path('test_image_dataset_diffdim.py')
train_dataset = import_python_file(train_dataset_path)
train_assets = read_dataset(train_dataset)
runner = MomentNorefFeatureExtractor(
train_assets,
None,
fifo_mode=True,
delete_workdir=True,
result_store=None,
optional_dict=None,
optional_dict2=None,
)
runner.run(parallelize=True)
self.features = runner.results
def setUp(self):
train_dataset_path = VmafConfig.test_resource_path('test_image_dataset_diffdim.py')
train_dataset = import_python_file(train_dataset_path)
train_assets = read_dataset(train_dataset)
runner = MomentNorefFeatureExtractor(
train_assets,
None,
fifo_mode=True,
delete_workdir=True,
result_store=None,
optional_dict=None,
optional_dict2=None,
)
runner.run(parallelize=True)
self.features = runner.results
class NorefFeatureExtractorTest(unittest.TestCase):
def tearDown(self):
if hasattr(self, 'fextractor'):
self.fextractor.remove_results()
pass
@unittest.skipIf('apps' in VmafExternalConfig.ffmpeg_path(),
'ffmpeg should not be in apps')
def test_noref_moment_fextractor_with_noref_asset_notyuv_gaussianblur(
self):
dis_path = VmafConfig.test_resource_path("mp4",
"Seeking_10_288_375.mp4")
asset = NorefAsset(dataset="test",
content_id=0,
asset_id=0,
workdir_root=VmafConfig.workdir_path(),
dis_path=dis_path,
asset_dict={
'yuv_type': 'notyuv',
'quality_width': 720,
'quality_height': 480,
'gblur_cmd': 'sigma=0.01:steps=1',
})
self.fextractor = MomentNorefFeatureExtractor([asset],
None,
fifo_mode=False,
result_store=None)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'],
63.25902145061728,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'],
5123.705637307099,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'],
1113.0346638689637,
places=4)
class NorefFeatureExtractorTest(unittest.TestCase):
def tearDown(self):
if hasattr(self, 'fextractor'):
self.fextractor.remove_results()
pass
def test_noref_moment_fextractor_with_noref_asset_notyuv(self):
print 'test on running Moment noref feature extractor on NorefAssets ' \
'(non-YUV)...'
dis_path = config.ROOT + "/python/test/resource/mp4/Seeking_10_288_375.mp4"
asset = NorefAsset(dataset="test",
content_id=0,
asset_id=0,
workdir_root=config.ROOT + "/workspace/workdir",
dis_path=dis_path,
asset_dict={
'yuv_type': 'notyuv',
'quality_width': 720,
'quality_height': 480,
})
self.fextractor = MomentNorefFeatureExtractor([asset],
None,
fifo_mode=True,
result_store=None)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'],
63.763580381944436,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'],
5158.9407083526221,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'],
1084.1635630076041,
places=4)
def test_noref_siti_fextractor_with_noref_asset(self):
ref_path, dis_path, asset, asset_original = set_default_576_324_noref_videos_for_testing(
)
self.fextractor = SiTiNorefFeatureExtractor([asset, asset_original],
None,
fifo_mode=True,
result_store=None)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['SITI_noref_feature_si_score'],
79.27042052471928)
self.assertAlmostEqual(results[0]['SITI_noref_feature_ti_score'],
13.580963712032636)
self.assertAlmostEqual(results[1]['SITI_noref_feature_si_score'],
83.46568284569439)
self.assertAlmostEqual(results[1]['SITI_noref_feature_ti_score'],
15.570422677885475)
perc75 = partial(np.percentile, q=75)
[result.set_score_aggregate_method(perc75) for result in results]
self.assertAlmostEqual(results[0]['SITI_noref_feature_si_score'],
80.01507800178135)
self.assertAlmostEqual(results[0]['SITI_noref_feature_ti_score'],
14.71399321502522)
self.assertAlmostEqual(results[1]['SITI_noref_feature_si_score'],
84.00886573293045)
self.assertAlmostEqual(results[1]['SITI_noref_feature_ti_score'],
16.862281850395433)
perc100 = partial(np.percentile, q=100)
[result.set_score_aggregate_method(perc100) for result in results]
self.assertAlmostEqual(results[0]['SITI_noref_feature_si_score'],
82.84005099011819)
self.assertAlmostEqual(results[0]['SITI_noref_feature_ti_score'],
17.60733889303054)
self.assertAlmostEqual(results[1]['SITI_noref_feature_si_score'],
85.28055474796807)
self.assertAlmostEqual(results[1]['SITI_noref_feature_ti_score'],
19.500837587311423)
def test_run_noref_brisque_fextractor(self):
ref_path, dis_path, asset, asset_original = set_default_576_324_videos_for_testing()
self.fextractor = BrisqueNorefFeatureExtractor(
[asset, asset_original],
None, fifo_mode=True,
result_store=None
)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['BRISQUE_noref_feature_alpha23_score'], 0.7640625000000005, places=4)
self.assertAlmostEqual(results[0]['BRISQUE_noref_feature_alpha13_score'], 0.6322500000000002, places=4)
self.assertAlmostEqual(results[0]['BRISQUE_noref_feature_N34_score'], -0.007239876204980851, places=4)
self.assertAlmostEqual(results[1]['BRISQUE_noref_feature_alpha23_score'], 0.8644583333333339, places=4)
self.assertAlmostEqual(results[1]['BRISQUE_noref_feature_alpha13_score'], 0.82906250000000103, places=4)
self.assertAlmostEqual(results[1]['BRISQUE_noref_feature_N34_score'], -0.0092448158862212092, places=4)
def test_run_noref_niqe_fextractor(self):
ref_path, dis_path, asset, asset_original = set_default_576_324_videos_for_testing(
)
self.fextractor = NiqeNorefFeatureExtractor([asset, asset_original],
None,
fifo_mode=False,
result_store=None)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['NIQE_noref_feature_alpha23_score'],
0.8168807870370377,
places=4)
self.assertAlmostEqual(results[0]['NIQE_noref_feature_alpha13_score'],
0.6949641203703707,
places=4)
self.assertAlmostEqual(results[0]['NIQE_noref_feature_alpha_m1_score'],
2.0924143518518536,
places=4)
self.assertAlmostEqual(results[0]['NIQE_noref_feature_blbr1_score'],
0.72958634325785898,
places=4)
self.assertAlmostEqual(results[1]['NIQE_noref_feature_alpha23_score'],
0.89566087962963026,
places=4)
self.assertAlmostEqual(results[1]['NIQE_noref_feature_alpha13_score'],
0.85539583333333391,
places=4)
self.assertAlmostEqual(results[1]['NIQE_noref_feature_alpha_m1_score'],
2.7192025462962985,
places=4)
self.assertAlmostEqual(results[1]['NIQE_noref_feature_blbr1_score'],
0.98723051960738684,
places=4)
def test_noref_moment_fextractor_frames(self):
print 'test on running Moment noref feature extractor on Assets with frames...'
dis_path = VmafConfig.test_resource_path("yuv", "src01_hrc01_576x324.yuv")
asset = NorefAsset(dataset="test", content_id=0, asset_id=0,
workdir_root=VmafConfig.workdir_path(),
dis_path=dis_path,
asset_dict={'width':576, 'height':324,
'start_frame':2, 'end_frame':2,
})
self.fextractor = MomentNorefFeatureExtractor(
[asset],
None, fifo_mode=True,
result_store=None
)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'], 62.315495327503427, places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'], 4888.7623296039092, places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'], 1005.5413716918079, places=4)
def test_noref_moment_fextractor_with_noref_asset_notyuv(self):
print 'test on running Moment noref feature extractor on NorefAssets ' \
'(non-YUV)...'
dis_path = VmafConfig.test_resource_path("mp4", "Seeking_10_288_375.mp4")
asset = NorefAsset(dataset="test", content_id=0, asset_id=0,
workdir_root=VmafConfig.workdir_path(),
dis_path=dis_path,
asset_dict={'yuv_type': 'notyuv',
'quality_width': 720, 'quality_height': 480,
})
self.fextractor = MomentNorefFeatureExtractor(
[asset],
None, fifo_mode=True,
result_store=None
)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'], 63.763580381944436, places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'], 5158.9407083526221, places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'], 1084.1635630076041, places=4)
class ParallelNorefFeatureExtractorTestNew(unittest.TestCase):
def tearDown(self):
if hasattr(self, 'fextractor'):
self.fextractor.remove_results()
pass
def test_noref_moment_fextractor(self):
ref_path, dis_path, asset, asset_original = set_default_576_324_videos_for_testing()
self.fextractor = MomentNorefFeatureExtractor(
[asset, asset_original],
None, fifo_mode=True,
result_store=None
)
self.fextractor.run(parallelize=True)
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'], 61.332006624999984)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'], 4798.659574041666)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'], 1036.8371843488285)
self.assertAlmostEqual(results[1]['Moment_noref_feature_1st_score'], 59.788567297525134)
self.assertAlmostEqual(results[1]['Moment_noref_feature_2nd_score'], 4696.668388042271)
self.assertAlmostEqual(results[1]['Moment_noref_feature_var_score'], 1121.519917231207)
def test_noref_moment_fextractor_with_noref_asset(self):
ref_path, dis_path, asset, asset_original = set_default_576_324_videos_for_testing()
self.fextractor = MomentNorefFeatureExtractor(
[asset, asset_original],
None, fifo_mode=True,
result_store=None
)
self.fextractor.run(parallelize=True)
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'], 61.332006624999984)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'], 4798.659574041666)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'], 1036.8371843488285)
self.assertAlmostEqual(results[1]['Moment_noref_feature_1st_score'], 59.788567297525134)
self.assertAlmostEqual(results[1]['Moment_noref_feature_2nd_score'], 4696.668388042271)
self.assertAlmostEqual(results[1]['Moment_noref_feature_var_score'], 1121.519917231207)
def test_run_parallel_brisque_noref_fextractor(self):
ref_path, dis_path, asset, asset_original = set_default_576_324_videos_for_testing()
self.fextractors, results = run_executors_in_parallel(
BrisqueNorefFeatureExtractor,
[asset, asset_original],
fifo_mode=True,
delete_workdir=True,
parallelize=True,
result_store=None,
)
self.assertAlmostEqual(results[0]['BRISQUE_noref_feature_alpha23_score'], 0.7640625000000005, places=4)
self.assertAlmostEqual(results[0]['BRISQUE_noref_feature_alpha13_score'], 0.6322500000000002, places=4)
self.assertAlmostEqual(results[0]['BRISQUE_noref_feature_N34_score'], -0.007239876204980851, places=4)
self.assertAlmostEqual(results[1]['BRISQUE_noref_feature_alpha23_score'], 0.8644583333333339, places=4)
self.assertAlmostEqual(results[1]['BRISQUE_noref_feature_alpha13_score'], 0.82906250000000103, places=4)
self.assertAlmostEqual(results[1]['BRISQUE_noref_feature_N34_score'], -0.0092448158862212092, places=4)
class NorefFeatureExtractorTest(unittest.TestCase):
def tearDown(self):
if hasattr(self, 'fextractor'):
self.fextractor.remove_results()
pass
def test_noref_moment_fextractor_with_noref_asset_notyuv(self):
dis_path = VmafConfig.test_resource_path("mp4",
"Seeking_10_288_375.mp4")
asset = NorefAsset(dataset="test",
content_id=0,
asset_id=0,
workdir_root=VmafConfig.workdir_path(),
dis_path=dis_path,
asset_dict={
'yuv_type': 'notyuv',
'quality_width': 720,
'quality_height': 480,
})
self.fextractor = MomentNorefFeatureExtractor(
[asset],
None,
fifo_mode=False, # TODO python3: fifo mode fails in py3, needs fix
result_store=None)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'],
63.776442013888882,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'],
5194.9118422453694,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'],
1118.4952858425261,
places=4)
def test_noref_moment_fextractor_frames(self):
dis_path = VmafConfig.test_resource_path("yuv",
"src01_hrc01_576x324.yuv")
asset = NorefAsset(dataset="test",
content_id=0,
asset_id=0,
workdir_root=VmafConfig.workdir_path(),
dis_path=dis_path,
asset_dict={
'width': 576,
'height': 324,
'start_frame': 2,
'end_frame': 2,
})
self.fextractor = MomentNorefFeatureExtractor(
[asset],
None,
fifo_mode=False, # TODO python3: fifo mode fails in py3, needs fix
result_store=None)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'],
62.315495327503427,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'],
4888.7623296039092,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'],
1005.5413716918079,
places=4)
class NorefFeatureExtractorTest(unittest.TestCase):
def tearDown(self):
if hasattr(self, 'fextractor'):
self.fextractor.remove_results()
pass
@unittest.skipIf(
sys.version_info > (3, ),
reason="TODO python3: unclear how YuvReader is supposed to work")
def test_noref_moment_fextractor_with_noref_asset_notyuv(self):
print(
'test on running Moment noref feature extractor on NorefAssets (non-YUV)...'
)
dis_path = VmafConfig.test_resource_path("mp4",
"Seeking_10_288_375.mp4")
asset = NorefAsset(dataset="test",
content_id=0,
asset_id=0,
workdir_root=VmafConfig.workdir_path(),
dis_path=dis_path,
asset_dict={
'yuv_type': 'notyuv',
'quality_width': 720,
'quality_height': 480,
})
self.fextractor = MomentNorefFeatureExtractor([asset],
None,
fifo_mode=True,
result_store=None)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'],
63.776442013888882,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'],
5194.9118422453694,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'],
1118.4952858425261,
places=4)
@unittest.skipIf(
sys.version_info > (3, ),
reason="TODO python3: unclear how YuvReader is supposed to work")
def test_noref_moment_fextractor_frames(self):
print(
'test on running Moment noref feature extractor on Assets with frames...'
)
dis_path = VmafConfig.test_resource_path("yuv",
"src01_hrc01_576x324.yuv")
asset = NorefAsset(dataset="test",
content_id=0,
asset_id=0,
workdir_root=VmafConfig.workdir_path(),
dis_path=dis_path,
asset_dict={
'width': 576,
'height': 324,
'start_frame': 2,
'end_frame': 2,
})
self.fextractor = MomentNorefFeatureExtractor([asset],
None,
fifo_mode=True,
result_store=None)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'],
62.315495327503427,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'],
4888.7623296039092,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'],
1005.5413716918079,
places=4)
class ParallelNorefFeatureExtractorTestNew(unittest.TestCase):
def tearDown(self):
if hasattr(self, 'fextractor'):
self.fextractor.remove_results()
pass
def test_noref_moment_fextractor(self):
print 'test on running Moment noref feature extractor on Assets...'
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})
self.fextractor = MomentNorefFeatureExtractor(
[asset, asset_original],
None, fifo_mode=True,
result_store=None
)
self.fextractor.run(parallelize=True)
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'], 61.332006624999984)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'], 4798.659574041666)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'], 1036.8371843488285)
self.assertAlmostEqual(results[1]['Moment_noref_feature_1st_score'], 59.788567297525134)
self.assertAlmostEqual(results[1]['Moment_noref_feature_2nd_score'], 4696.668388042271)
self.assertAlmostEqual(results[1]['Moment_noref_feature_var_score'], 1121.519917231207)
def test_noref_moment_fextractor_with_noref_asset(self):
print 'test on running Moment noref feature extractor on NorefAssets...'
ref_path = VmafConfig.test_resource_path("yuv", "src01_hrc00_576x324.yuv")
dis_path = VmafConfig.test_resource_path("yuv", "src01_hrc01_576x324.yuv")
asset = NorefAsset(dataset="test", content_id=0, asset_id=0,
workdir_root=VmafConfig.workdir_path(),
dis_path=dis_path,
asset_dict={'width':576, 'height':324})
asset_original = NorefAsset(dataset="test", content_id=0, asset_id=1,
workdir_root=VmafConfig.workdir_path(),
dis_path=ref_path,
asset_dict={'width':576, 'height':324})
self.fextractor = MomentNorefFeatureExtractor(
[asset, asset_original],
None, fifo_mode=True,
result_store=None
)
self.fextractor.run(parallelize=True)
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'], 61.332006624999984)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'], 4798.659574041666)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'], 1036.8371843488285)
self.assertAlmostEqual(results[1]['Moment_noref_feature_1st_score'], 59.788567297525134)
self.assertAlmostEqual(results[1]['Moment_noref_feature_2nd_score'], 4696.668388042271)
self.assertAlmostEqual(results[1]['Moment_noref_feature_var_score'], 1121.519917231207)
def test_run_parallel_brisque_noref_fextractor(self):
print 'test on running BRISQUE noref feature extractor on NorefAssets 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 = NorefAsset(dataset="test", content_id=0, asset_id=0,
workdir_root=VmafConfig.workdir_path(),
dis_path=dis_path,
asset_dict={'width':576, 'height':324})
asset_original = NorefAsset(dataset="test", content_id=0, asset_id=1,
workdir_root=VmafConfig.workdir_path(),
dis_path=ref_path,
asset_dict={'width':576, 'height':324})
self.fextractors, results = run_executors_in_parallel(
BrisqueNorefFeatureExtractor,
[asset, asset_original],
fifo_mode=True,
delete_workdir=True,
parallelize=True,
result_store=None,
)
self.assertAlmostEqual(results[0]['BRISQUE_noref_feature_alpha23_score'], 0.78020833333333384, places=4)
self.assertAlmostEqual(results[0]['BRISQUE_noref_feature_alpha13_score'], 0.6322500000000002, places=4)
self.assertAlmostEqual(results[0]['BRISQUE_noref_feature_N34_score'], -0.0071207420215536723, places=4)
self.assertAlmostEqual(results[1]['BRISQUE_noref_feature_alpha23_score'], 0.87156250000000046, places=4)
self.assertAlmostEqual(results[1]['BRISQUE_noref_feature_alpha13_score'], 0.82906250000000103, places=4)
self.assertAlmostEqual(results[1]['BRISQUE_noref_feature_N34_score'], -0.0092448158862212092, places=4)
class ParallelNorefFeatureExtractorTestNew(unittest.TestCase):
def tearDown(self):
if hasattr(self, 'fextractor'):
self.fextractor.remove_results()
pass
def test_noref_moment_fextractor(self):
print 'test on running Moment noref feature extractor on Assets...'
ref_path = config.ROOT + "/resource/yuv/src01_hrc00_576x324.yuv"
dis_path = config.ROOT + "/resource/yuv/src01_hrc01_576x324.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': 576,
'height': 324
})
asset_original = Asset(dataset="test",
content_id=0,
asset_id=1,
workdir_root=config.ROOT + "/workspace/workdir",
ref_path=ref_path,
dis_path=ref_path,
asset_dict={
'width': 576,
'height': 324
})
self.fextractor = MomentNorefFeatureExtractor([asset, asset_original],
None,
fifo_mode=True,
result_store=None)
self.fextractor.run(parallelize=True)
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'],
61.332006624999984)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'],
4798.659574041666)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'],
1036.8371843488285)
self.assertAlmostEqual(results[1]['Moment_noref_feature_1st_score'],
59.788567297525134)
self.assertAlmostEqual(results[1]['Moment_noref_feature_2nd_score'],
4696.668388042271)
self.assertAlmostEqual(results[1]['Moment_noref_feature_var_score'],
1121.519917231207)
def test_noref_moment_fextractor_with_noref_asset(self):
print 'test on running Moment noref feature extractor on NorefAssets...'
ref_path = config.ROOT + "/resource/yuv/src01_hrc00_576x324.yuv"
dis_path = config.ROOT + "/resource/yuv/src01_hrc01_576x324.yuv"
asset = NorefAsset(dataset="test",
content_id=0,
asset_id=0,
workdir_root=config.ROOT + "/workspace/workdir",
dis_path=dis_path,
asset_dict={
'width': 576,
'height': 324
})
asset_original = NorefAsset(dataset="test",
content_id=0,
asset_id=1,
workdir_root=config.ROOT +
"/workspace/workdir",
dis_path=ref_path,
asset_dict={
'width': 576,
'height': 324
})
self.fextractor = MomentNorefFeatureExtractor([asset, asset_original],
None,
fifo_mode=True,
result_store=None)
self.fextractor.run(parallelize=True)
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'],
61.332006624999984)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'],
4798.659574041666)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'],
1036.8371843488285)
self.assertAlmostEqual(results[1]['Moment_noref_feature_1st_score'],
59.788567297525134)
self.assertAlmostEqual(results[1]['Moment_noref_feature_2nd_score'],
4696.668388042271)
self.assertAlmostEqual(results[1]['Moment_noref_feature_var_score'],
1121.519917231207)
class ParallelNorefFeatureExtractorTestNew(unittest.TestCase):
def tearDown(self):
if hasattr(self, 'fextractor'):
self.fextractor.remove_results()
pass
def test_noref_moment_fextractor(self):
print 'test on running Moment noref feature extractor on Assets...'
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})
self.fextractor = MomentNorefFeatureExtractor(
[asset, asset_original],
None, fifo_mode=True,
result_store=None
)
self.fextractor.run(parallelize=True)
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'], 61.332006624999984)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'], 4798.659574041666)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'], 1036.8371843488285)
self.assertAlmostEqual(results[1]['Moment_noref_feature_1st_score'], 59.788567297525134)
self.assertAlmostEqual(results[1]['Moment_noref_feature_2nd_score'], 4696.668388042271)
self.assertAlmostEqual(results[1]['Moment_noref_feature_var_score'], 1121.519917231207)
def test_noref_moment_fextractor_with_noref_asset(self):
print 'test on running Moment noref feature extractor on NorefAssets...'
ref_path = VmafConfig.test_resource_path("yuv", "src01_hrc00_576x324.yuv")
dis_path = VmafConfig.test_resource_path("yuv", "src01_hrc01_576x324.yuv")
asset = NorefAsset(dataset="test", content_id=0, asset_id=0,
workdir_root=VmafConfig.workdir_path(),
dis_path=dis_path,
asset_dict={'width':576, 'height':324})
asset_original = NorefAsset(dataset="test", content_id=0, asset_id=1,
workdir_root=VmafConfig.workdir_path(),
dis_path=ref_path,
asset_dict={'width':576, 'height':324})
self.fextractor = MomentNorefFeatureExtractor(
[asset, asset_original],
None, fifo_mode=True,
result_store=None
)
self.fextractor.run(parallelize=True)
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'], 61.332006624999984)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'], 4798.659574041666)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'], 1036.8371843488285)
self.assertAlmostEqual(results[1]['Moment_noref_feature_1st_score'], 59.788567297525134)
self.assertAlmostEqual(results[1]['Moment_noref_feature_2nd_score'], 4696.668388042271)
self.assertAlmostEqual(results[1]['Moment_noref_feature_var_score'], 1121.519917231207)
class NorefFeatureExtractorTest(unittest.TestCase):
def tearDown(self):
if hasattr(self, 'fextractor'):
self.fextractor.remove_results()
pass
def test_noref_moment_fextractor_with_noref_asset_notyuv(self):
print 'test on running Moment noref feature extractor on NorefAssets ' \
'(non-YUV)...'
dis_path = VmafConfig.test_resource_path("mp4",
"Seeking_10_288_375.mp4")
asset = NorefAsset(dataset="test",
content_id=0,
asset_id=0,
workdir_root=VmafConfig.workdir_path(),
dis_path=dis_path,
asset_dict={
'yuv_type': 'notyuv',
'quality_width': 720,
'quality_height': 480,
})
self.fextractor = MomentNorefFeatureExtractor([asset],
None,
fifo_mode=True,
result_store=None)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'],
63.763580381944436,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'],
5158.9407083526221,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'],
1084.1635630076041,
places=4)
def test_noref_moment_fextractor_frames(self):
print 'test on running Moment noref feature extractor on Assets with frames...'
dis_path = VmafConfig.test_resource_path("yuv",
"src01_hrc01_576x324.yuv")
asset = NorefAsset(dataset="test",
content_id=0,
asset_id=0,
workdir_root=VmafConfig.workdir_path(),
dis_path=dis_path,
asset_dict={
'width': 576,
'height': 324,
'start_frame': 2,
'end_frame': 2,
})
self.fextractor = MomentNorefFeatureExtractor([asset],
None,
fifo_mode=True,
result_store=None)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'],
62.315495327503427,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'],
4888.7623296039092,
places=4)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'],
1005.5413716918079,
places=4)
class NorefFeatureExtractorTest(unittest.TestCase):
def tearDown(self):
if hasattr(self, 'fextractor'):
self.fextractor.remove_results()
pass
def test_noref_moment_fextractor(self):
ref_path, dis_path, asset, asset_original = set_default_576_324_videos_for_testing()
self.fextractor = MomentNorefFeatureExtractor(
[asset, asset_original],
None, fifo_mode=True,
result_store=None
)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'], 61.332006624999984)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'], 4798.659574041666)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'], 1036.8371843488285)
self.assertAlmostEqual(results[1]['Moment_noref_feature_1st_score'], 59.788567297525134)
self.assertAlmostEqual(results[1]['Moment_noref_feature_2nd_score'], 4696.668388042271)
self.assertAlmostEqual(results[1]['Moment_noref_feature_var_score'], 1121.519917231207)
def test_noref_moment_fextractor_with_noref_asset(self):
ref_path, dis_path, asset, asset_original = set_default_576_324_noref_videos_for_testing()
self.fextractor = MomentNorefFeatureExtractor(
[asset, asset_original],
None, fifo_mode=True,
result_store=None
)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'], 61.332006624999984)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'], 4798.659574041666)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'], 1036.8371843488285)
self.assertAlmostEqual(results[1]['Moment_noref_feature_1st_score'], 59.788567297525134)
self.assertAlmostEqual(results[1]['Moment_noref_feature_2nd_score'], 4696.668388042271)
self.assertAlmostEqual(results[1]['Moment_noref_feature_var_score'], 1121.519917231207)
def test_run_noref_brisque_fextractor(self):
ref_path, dis_path, asset, asset_original = set_default_576_324_videos_for_testing()
self.fextractor = BrisqueNorefFeatureExtractor(
[asset, asset_original],
None, fifo_mode=True,
result_store=None
)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['BRISQUE_noref_feature_alpha23_score'], 0.7640625000000005, places=4)
self.assertAlmostEqual(results[0]['BRISQUE_noref_feature_alpha13_score'], 0.6322500000000002, places=4)
self.assertAlmostEqual(results[0]['BRISQUE_noref_feature_N34_score'], -0.007239876204980851, places=4)
self.assertAlmostEqual(results[1]['BRISQUE_noref_feature_alpha23_score'], 0.8644583333333339, places=4)
self.assertAlmostEqual(results[1]['BRISQUE_noref_feature_alpha13_score'], 0.82906250000000103, places=4)
self.assertAlmostEqual(results[1]['BRISQUE_noref_feature_N34_score'], -0.0092448158862212092, places=4)
def test_run_noref_niqe_fextractor(self):
ref_path, dis_path, asset, asset_original = set_default_576_324_videos_for_testing()
self.fextractor = NiqeNorefFeatureExtractor(
[asset, asset_original],
None, fifo_mode=False,
result_store=None
)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['NIQE_noref_feature_alpha23_score'], 0.8168807870370377, places=4)
self.assertAlmostEqual(results[0]['NIQE_noref_feature_alpha13_score'], 0.6949641203703707, places=4)
self.assertAlmostEqual(results[0]['NIQE_noref_feature_alpha_m1_score'], 2.0924143518518536, places=4)
self.assertAlmostEqual(results[0]['NIQE_noref_feature_blbr1_score'], 0.72958634325785898, places=4)
self.assertAlmostEqual(results[1]['NIQE_noref_feature_alpha23_score'], 0.89566087962963026, places=4)
self.assertAlmostEqual(results[1]['NIQE_noref_feature_alpha13_score'], 0.85539583333333391, places=4)
self.assertAlmostEqual(results[1]['NIQE_noref_feature_alpha_m1_score'], 2.7192025462962985, places=4)
self.assertAlmostEqual(results[1]['NIQE_noref_feature_blbr1_score'], 0.98723051960738684, places=4)
def test_run_noref_niqe_fextractor_train(self):
ref_path, dis_path, asset, asset_original = set_default_576_324_videos_for_testing()
self.fextractor = NiqeNorefFeatureExtractor(
[asset, asset_original],
None, fifo_mode=False,
result_store=None,
optional_dict={'mode': 'train'},
optional_dict2=None,
)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['NIQE_noref_feature_alpha23_score'], 0.97259000000000073, places=4)
self.assertAlmostEqual(results[0]['NIQE_noref_feature_alpha13_score'], 0.80907000000000051, places=4)
self.assertAlmostEqual(results[0]['NIQE_noref_feature_alpha_m1_score'], 2.6135250000000019, places=4)
self.assertAlmostEqual(results[0]['NIQE_noref_feature_blbr1_score'], 0.9150526409258144, places=4)
self.assertAlmostEqual(results[1]['NIQE_noref_feature_alpha23_score'], 0.97447727272727347, places=4)
self.assertAlmostEqual(results[1]['NIQE_noref_feature_alpha13_score'], 0.89120909090909162, places=4)
self.assertAlmostEqual(results[1]['NIQE_noref_feature_alpha_m1_score'], 3.0300909090909118, places=4)
self.assertAlmostEqual(results[1]['NIQE_noref_feature_blbr1_score'], 1.0508255408831713, places=4)
def test_run_noref_niqe_fextractor_with_patch_size(self):
ref_path, dis_path, asset, asset_original = set_default_576_324_videos_for_testing()
self.fextractor = NiqeNorefFeatureExtractor(
[asset, asset_original],
None, fifo_mode=False,
result_store=None,
optional_dict={'patch_size': 48},
optional_dict2=None,
)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['NIQE_noref_feature_alpha23_score'], 0.8430156250000006, places=4)
self.assertAlmostEqual(results[0]['NIQE_noref_feature_alpha13_score'], 0.71714583333333359, places=4)
self.assertAlmostEqual(results[0]['NIQE_noref_feature_alpha_m1_score'], 2.2195590277777795, places=4)
self.assertAlmostEqual(results[0]['NIQE_noref_feature_blbr1_score'], 0.74061215376929412, places=4)
self.assertAlmostEqual(results[1]['NIQE_noref_feature_alpha23_score'], 0.9144918981481488, places=4)
self.assertAlmostEqual(results[1]['NIQE_noref_feature_alpha13_score'], 0.87132291666666728, places=4)
self.assertAlmostEqual(results[1]['NIQE_noref_feature_alpha_m1_score'], 2.8193532986111136, places=4)
self.assertAlmostEqual(results[1]['NIQE_noref_feature_blbr1_score'], 0.99354006450609134, places=4)
def test_noref_siti_fextractor_with_noref_asset(self):
ref_path, dis_path, asset, asset_original = set_default_576_324_noref_videos_for_testing()
self.fextractor = SiTiNorefFeatureExtractor(
[asset, asset_original],
None, fifo_mode=True,
result_store=None
)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['SITI_noref_feature_si_score'], 79.27042052471928)
self.assertAlmostEqual(results[0]['SITI_noref_feature_ti_score'], 13.580963712032636)
self.assertAlmostEqual(results[1]['SITI_noref_feature_si_score'], 83.46568284569439)
self.assertAlmostEqual(results[1]['SITI_noref_feature_ti_score'], 15.570422677885475)
perc75 = partial(np.percentile, q=75)
[result.set_score_aggregate_method(perc75) for result in results]
self.assertAlmostEqual(results[0]['SITI_noref_feature_si_score'], 80.01507800178135)
self.assertAlmostEqual(results[0]['SITI_noref_feature_ti_score'], 14.71399321502522)
self.assertAlmostEqual(results[1]['SITI_noref_feature_si_score'], 84.00886573293045)
self.assertAlmostEqual(results[1]['SITI_noref_feature_ti_score'], 16.862281850395433)
perc100 = partial(np.percentile, q=100)
[result.set_score_aggregate_method(perc100) for result in results]
self.assertAlmostEqual(results[0]['SITI_noref_feature_si_score'], 82.84005099011819)
self.assertAlmostEqual(results[0]['SITI_noref_feature_ti_score'], 17.60733889303054)
self.assertAlmostEqual(results[1]['SITI_noref_feature_si_score'], 85.28055474796807)
self.assertAlmostEqual(results[1]['SITI_noref_feature_ti_score'], 19.500837587311423)
def test_noref_moment_fextractor_proc(self):
ref_path, dis_path, asset, asset_original = set_default_576_324_videos_for_testing()
callback_dict = {
'dis_proc_callback': 'identity',
}
asset.asset_dict.update(callback_dict)
asset_original.asset_dict.update(callback_dict)
self.fextractor = MomentNorefFeatureExtractor(
[asset, asset_original],
None, fifo_mode=True,
result_store=None
)
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['Moment_noref_feature_1st_score'], 61.332006624999984)
self.assertAlmostEqual(results[0]['Moment_noref_feature_2nd_score'], 4798.659574041666)
self.assertAlmostEqual(results[0]['Moment_noref_feature_var_score'], 1036.8371843488285)
self.assertAlmostEqual(results[1]['Moment_noref_feature_1st_score'], 59.788567297525134)
self.assertAlmostEqual(results[1]['Moment_noref_feature_2nd_score'], 4696.668388042271)
self.assertAlmostEqual(results[1]['Moment_noref_feature_var_score'], 1121.519917231207)
