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_run_noref_niqe_fextractor_train(self):
print 'test on running NIQE noref feature extractor in train mode...'
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=1,
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=2,
workdir_root=VmafConfig.workdir_path(),
dis_path=ref_path,
asset_dict={'width':576, 'height':324,})
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):
print 'test on running NIQE noref feature extractor with custom patch size...'
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=1,
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=2,
workdir_root=VmafConfig.workdir_path(),
dis_path=ref_path,
asset_dict={'width':576, 'height':324})
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(self):
print 'test on running NIQE noref feature extractor...'
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=1,
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=2,
workdir_root=VmafConfig.workdir_path(),
dis_path=ref_path,
asset_dict={'width':576, 'height':324,})
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 setUp(self):
train_dataset_path = VmafConfig.test_resource_path(
'test_image_dataset.py')
train_dataset = import_python_file(train_dataset_path)
train_assets = read_dataset(train_dataset)
param = empty_object()
param.model_type = "NIQE"
param.model_param_dict = {
'patch_size': 96,
}
self.param = param
optional_dict = {'mode': 'train'}
self.fextractor = NiqeNorefFeatureExtractor(
train_assets,
None,
fifo_mode=True,
delete_workdir=True,
result_store=None,
optional_dict=optional_dict,
optional_dict2=None,
)
self.fextractor.run(parallelize=True)
self.features = self.fextractor.results
self.model_filename = VmafConfig.workspace_path(
'model', 'test_save_load.pkl')
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()
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):
print 'test on running BRISQUE noref feature extractor...'
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=1,
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=2,
workdir_root=VmafConfig.workdir_path(),
dis_path=ref_path,
asset_dict={'width':576, 'height':324,})
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'], 0.78020833333333384, 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)
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()
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_niqe_fextractor(self):
print('test on running NIQE noref feature extractor...')
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_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_brisque_fextractor(self):
print 'test on running BRISQUE noref feature extractor...'
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'], 0.78020833333333384, 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 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_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)
class NorefFeatureExtractorTest(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()
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()
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):
print 'test on running BRISQUE noref feature extractor...'
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=1,
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=2,
workdir_root=VmafConfig.workdir_path(),
dis_path=ref_path,
asset_dict={'width':576, 'height':324,})
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'], 0.78020833333333384, 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)
def test_run_noref_niqe_fextractor(self):
print 'test on running NIQE noref feature extractor...'
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=1,
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=2,
workdir_root=VmafConfig.workdir_path(),
dis_path=ref_path,
asset_dict={'width':576, 'height':324,})
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):
print 'test on running NIQE noref feature extractor in train mode...'
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=1,
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=2,
workdir_root=VmafConfig.workdir_path(),
dis_path=ref_path,
asset_dict={'width':576, 'height':324,})
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):
print 'test on running NIQE noref feature extractor with custom patch size...'
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=1,
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=2,
workdir_root=VmafConfig.workdir_path(),
dis_path=ref_path,
asset_dict={'width':576, 'height':324})
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)
class NiqeTrainTestModelTest(unittest.TestCase):
def setUp(self):
train_dataset_path = VmafConfig.test_resource_path(
'test_image_dataset.py')
train_dataset = import_python_file(train_dataset_path)
train_assets = read_dataset(train_dataset)
param = empty_object()
param.model_type = "NIQE"
param.model_param_dict = {
'patch_size': 96,
}
self.param = param
optional_dict = {'mode': 'train'}
self.fextractor = NiqeNorefFeatureExtractor(
train_assets,
None,
fifo_mode=True,
delete_workdir=True,
result_store=None,
optional_dict=optional_dict,
optional_dict2=None,
)
self.fextractor.run(parallelize=True)
self.features = self.fextractor.results
self.model_filename = VmafConfig.workspace_path(
'model', 'test_save_load.pkl')
def tearDown(self):
if os.path.exists(self.model_filename):
os.remove(self.model_filename)
def test_get_xs_from_results(self):
xs = NiqeTrainTestModel.get_xs_from_results(self.features)
self.assertEqual(len(xs['NIQE_noref_feature_N11_scores'][0]), 5)
self.assertEqual(len(xs['NIQE_noref_feature_N11_scores'][1]), 3)
self.assertEqual(len(xs['NIQE_noref_feature_N11_scores'][2]), 7)
self.assertEqual(len(xs['NIQE_noref_feature_N11_scores'][3]), 11)
self.assertEqual(len(xs['NIQE_noref_feature_N11_scores'][4]), 3)
self.assertAlmostEqual(xs['NIQE_noref_feature_N11_scores'][0][3],
-0.016672410493636325)
def test_train(self):
xys = NiqeTrainTestModel.get_xys_from_results(self.features)
model = NiqeTrainTestModel(self.param.model_param_dict, None)
model.train(xys)
self.assertAlmostEqual(np.mean(model.model_dict['model']['mu']),
0.58721456594247923,
places=4)
self.assertAlmostEqual(np.mean(model.model_dict['model']['cov']),
0.0062869078795764156,
places=4)
def test_predict(self):
xs = NiqeTrainTestModel.get_xs_from_results(self.features)
xys = NiqeTrainTestModel.get_xys_from_results(self.features)
model = NiqeTrainTestModel(self.param.model_param_dict, None)
model.train(xys)
ys_pred = model.predict(xs)['ys_label_pred']
self.assertAlmostEqual(np.mean(ys_pred), 3.7645955838278695, places=4)
self.assertAlmostEqual(ys_pred[0], 3.5840187532885257, places=3)
self.assertAlmostEqual(ys_pred[1], 5.1472584219091102, places=4)
def test_save_load_model(self):
xs = NiqeTrainTestModel.get_xs_from_results(self.features)
xys = NiqeTrainTestModel.get_xys_from_results(self.features)
model = NiqeTrainTestModel(self.param.model_param_dict, None)
model.train(xys)
model.to_file(self.model_filename)
model_new = TrainTestModel.from_file(self.model_filename, None)
ys_pred = model_new.predict(xs)['ys_label_pred']
self.assertAlmostEqual(np.mean(ys_pred), 3.7645955838278695, places=4)
