def test_copy_use_path_as_workpath(self):
asset = Asset(dataset="test", content_id=0, asset_id=0,
ref_path="", dis_path="",
asset_dict={'width': 720, 'height': 480,
'quality_width': 720, 'quality_height': 320,
'yuv_type': 'yuv422p',
'crop_cmd': '570:320:3:2',
'use_path_as_workpath': True
})
new_asset = asset.copy()
self.assertNotEquals(asset, new_asset) # use_path_as_workpath gets reset
self.assertTrue(asset.use_path_as_workpath)
self.assertFalse(new_asset.use_path_as_workpath)
def test_run_vmafossexec_runner_with_phone_model(self):
print 'test on running VMAFOSSEXEC runner with transform for phone...'
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_10_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 = VmafossExecQualityRunner(
[asset],
None, fifo_mode=False,
delete_workdir=True,
optional_dict={
'phone_model':True,
},
result_store=self.result_store,
)
self.runner.run()
results = self.runner.results
self.assertAlmostEqual(results[0]['VMAFOSSEXEC_vif_scale0_score'], 0.0, places=4)
self.assertAlmostEqual(results[0]['VMAFOSSEXEC_vif_scale1_score'], 0.0, places=4)
self.assertAlmostEqual(results[0]['VMAFOSSEXEC_vif_scale2_score'], 0.0, places=4)
self.assertAlmostEqual(results[0]['VMAFOSSEXEC_vif_scale3_score'], 0.0, places=4)
self.assertAlmostEqual(results[0]['VMAFOSSEXEC_motion2_score'], 12.5548366667, places=4)
self.assertAlmostEqual(results[0]['VMAFOSSEXEC_adm2_score'], 0.053996566666666669, places=4)
self.assertAlmostEqual(results[0]['VMAFOSSEXEC_score'], 14.982840000000001, places=4)
def test_run_vmafossexec_runner_with_transform_score_disabled(self):
print 'test on running VMAFOSSEXEC runner with score transforming disabled...'
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_10_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 = VmafossExecQualityRunner(
[asset],
None, fifo_mode=True,
delete_workdir=True,
optional_dict={
'model_filepath':VmafConfig.test_resource_path("test_model_transform_add40.pkl"),
'enable_transform_score':False,
},
result_store=self.result_store,
)
self.runner.run()
results = self.runner.results
self.assertAlmostEqual(results[0]['VMAFOSSEXEC_vif_scale0_score'], 0.0, places=4)
self.assertAlmostEqual(results[0]['VMAFOSSEXEC_vif_scale1_score'], 0.0, places=4)
self.assertAlmostEqual(results[0]['VMAFOSSEXEC_vif_scale2_score'], 0.0, places=4)
self.assertAlmostEqual(results[0]['VMAFOSSEXEC_vif_scale3_score'], 0.0, places=4)
self.assertAlmostEqual(results[0]['VMAFOSSEXEC_motion_score'], 12.5548366667, places=4)
self.assertAlmostEqual(results[0]['VMAFOSSEXEC_adm_scale0_score'], 0.23738393128710478, places=4)
self.assertAlmostEqual(results[0]['VMAFOSSEXEC_adm_scale1_score'], 0.08524788663335138, places=4)
self.assertAlmostEqual(results[0]['VMAFOSSEXEC_adm_scale2_score'], 0.024058909404945077, places=4)
self.assertAlmostEqual(results[0]['VMAFOSSEXEC_adm_scale3_score'], 0.018034879735107798, places=4)
self.assertAlmostEqual(results[0]['VMAFOSSEXEC_score'], 0.0, places=4)
def test_workfile_path(self):
asset = Asset(dataset="test",
content_id=0,
asset_id=0,
ref_path="dir/refvideo.yuv",
dis_path="dir/disvideo.yuv",
asset_dict={
'width': 720,
'height': 480,
'start_frame': 2,
'end_frame': 2,
'quality_width': 1920,
'quality_height': 1080
},
workdir_root="workdir")
expected_ref_workfile_path_re = \
r"^workdir/[a-zA-Z0-9-]+/" \
r"ref_test_0_0_refvideo_720x480_2to2_vs_disvideo_720x480_2to2_q_1920x1080"
expected_dis_workfile_path_re = \
r"^workdir/[a-zA-Z0-9-]+/" \
r"dis_test_0_0_refvideo_720x480_2to2_vs_disvideo_720x480_2to2_q_1920x1080"
self.assertTrue(
re.match(expected_ref_workfile_path_re, asset.ref_workfile_path))
self.assertTrue(
re.match(expected_dis_workfile_path_re, asset.dis_workfile_path))
def test_run_vmafrc_runner_akiyo_multiply_with_feature_enhn_gain_limit(self):
ref_path = VmafConfig.test_resource_path("yuv", "refp_vmaf_hacking_investigation_0_0_akiyo_cif_notyuv_0to0_identity_vs_akiyo_cif_notyuv_0to0_multiply_q_352x288")
dis_path = VmafConfig.test_resource_path("yuv", "disp_vmaf_hacking_investigation_0_0_akiyo_cif_notyuv_0to0_identity_vs_akiyo_cif_notyuv_0to0_multiply_q_352x288")
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': 352, 'height': 288})
self.runner = VmafrcQualityRunner(
[asset],
None, fifo_mode=False,
delete_workdir=True,
result_store=None,
optional_dict={'disable_clip_score': True, 'adm_enhn_gain_limit': 1.0, 'vif_enhn_gain_limit': 1.0}
)
self.runner.run(parallelize=False)
results = self.runner.results
self.assertAlmostEqual(results[0]['VMAFRC_adm2_score'], 0.9574308606115118, places=4) # 1.116691484215469
self.assertAlmostEqual(results[0]['VMAFRC_vif_scale0_score'], 0.983699512450884, places=4) # 1.0522544319369052
self.assertAlmostEqual(results[0]['VMAFRC_vif_scale1_score'], 0.9974276726830457, places=4) # 1.0705609423182443
self.assertAlmostEqual(results[0]['VMAFRC_vif_scale2_score'], 0.9984692380091739, places=4) # 1.0731529493098957
self.assertAlmostEqual(results[0]['VMAFRC_vif_scale3_score'], 0.999146211879154, places=4) # 1.0728060231246508
self.assertAlmostEqual(results[0]['VMAFRC_score'], 88.032956, places=4) # 132.78849246495625
def test_bitrate(self):
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,
ref_path=ref_path,
dis_path=dis_path,
asset_dict={
'ref_start_frame': 0,
'ref_end_frame': 47,
'dis_start_frame': 0,
'dis_end_frame': 47,
'fps': 23.976
},
)
self.assertAlmostEquals(asset.ref_bitrate_kbps_for_entire_file,
53693.964287999996,
places=4)
self.assertAlmostEquals(asset.dis_bitrate_kbps_for_entire_file,
53693.964287999996,
places=4)
def test_workdir(self):
import re
asset = Asset(dataset="test", content_id=0, asset_id=0,
ref_path="", dis_path="",
asset_dict={}, workdir_root="my_workdir_root")
workdir = asset.workdir
self.assertTrue(re.match(r"^my_workdir_root/[a-zA-Z0-9-]+$", workdir))
def test_run_float_adm_fextractor_akiyo_multiply_enhn_gain_limit_1d2(self):
ref_path = VmafConfig.test_resource_path(
"yuv",
"refp_vmaf_hacking_investigation_0_0_akiyo_cif_notyuv_0to0_identity_vs_akiyo_cif_notyuv_0to0_multiply_q_352x288"
)
dis_path = VmafConfig.test_resource_path(
"yuv",
"disp_vmaf_hacking_investigation_0_0_akiyo_cif_notyuv_0to0_identity_vs_akiyo_cif_notyuv_0to0_multiply_q_352x288"
)
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': 352,
'height': 288
})
self.fextractor = FloatAdmFeatureExtractor(
[asset],
None,
fifo_mode=False,
result_store=None,
optional_dict={'adm_enhn_gain_limit': 1.2})
self.fextractor.run()
results = self.fextractor.results
self.assertAlmostEqual(results[0]['float_ADM_feature_adm2_score'],
1.116595,
places=6)
def set_default_flat_1920_1080_videos_for_testing():
ref_path = VmafConfig.test_resource_path("yuv", "flat_1920_1080_0.yuv")
dis_path = VmafConfig.test_resource_path("yuv", "flat_1920_1080_10.yuv")
asset = Asset(dataset="test", content_id=0, asset_id=0,
workdir_root=VmafConfig.workdir_path(),
ref_path=ref_path,
dis_path=dis_path,
asset_dict={'width': 1920, 'height': 1080})
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': 1920, 'height': 1080})
return ref_path, dis_path, asset, asset_original
def set_default_576_324_videos_for_testing():
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})
return ref_path, dis_path, asset, asset_original
def test_run_vmafrc_runner_akiyo_multiply_with_feature_enhn_gain_limit_custom(self):
ref_path = VmafConfig.test_resource_path("yuv", "refp_vmaf_hacking_investigation_0_0_akiyo_cif_notyuv_0to0_identity_vs_akiyo_cif_notyuv_0to0_multiply_q_352x288")
dis_path = VmafConfig.test_resource_path("yuv", "disp_vmaf_hacking_investigation_0_0_akiyo_cif_notyuv_0to0_identity_vs_akiyo_cif_notyuv_0to0_multiply_q_352x288")
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': 352, 'height': 288})
self.runner = VmafrcQualityRunner(
[asset],
None, fifo_mode=False,
delete_workdir=True,
result_store=None,
optional_dict={'disable_clip_score': True, 'adm_enhn_gain_limit': 1.2, 'vif_enhn_gain_limit': 1.1}
)
self.runner.run(parallelize=False)
results = self.runner.results
self.assertAlmostEqual(results[0]['VMAFRC_adm2_score'], 1.116595, places=4) # 1.116691484215469
self.assertAlmostEqual(results[0]['VMAFRC_vif_scale0_score'], 1.029765, places=4) # 1.0522544319369052
self.assertAlmostEqual(results[0]['VMAFRC_vif_scale1_score'], 1.046767, places=4) # 1.0705609423182443
self.assertAlmostEqual(results[0]['VMAFRC_vif_scale2_score'], 1.049025, places=4) # 1.0731529493098957
self.assertAlmostEqual(results[0]['VMAFRC_vif_scale3_score'], 1.0491232394147363, places=4) # 1.0728060231246508
self.assertAlmostEqual(results[0]['VMAFRC_score'], 129.516141, places=4) # 132.78849246495625
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 test_dis_width_height(self):
asset = Asset(dataset="test", content_id=0, asset_id=0,
ref_path="", dis_path="",
asset_dict={'dis_width':1920, 'dis_height':1080,})
self.assertEquals(asset.dis_width_height, (1920, 1080))
asset = Asset(dataset="test", content_id=0, asset_id=0,
ref_path="", dis_path="",
asset_dict={'dis_width':1920, 'dis_height':1080,
'width':720, 'height':480})
self.assertEquals(asset.dis_width_height, (1920, 1080))
asset = Asset(dataset="test", content_id=0, asset_id=0,
ref_path="", dis_path="",
asset_dict={'width':720, 'height':480})
self.assertEquals(asset.dis_width_height, (720, 480))
def test_run_vmaf_runner_with_notyuv_gblur(self):
ref_path = VmafConfig.test_resource_path("mp4",
"Seeking_30_480_1050.mp4")
dis_path = VmafConfig.test_resource_path("mp4",
"Seeking_10_288_375.mp4")
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={
'yuv_type': 'notyuv',
'quality_width': 360,
'quality_height': 240,
'dis_gblur_cmd': 'sigma=0.01:steps=1',
})
self.runner = VmafQualityRunner([asset],
None,
fifo_mode=True,
delete_workdir=True,
result_store=None)
self.runner.run()
results = self.runner.results
self.assertAlmostEqual(results[0]['VMAF_score'],
77.28938600125885,
places=4)
def test_run_vmaf_runner_with_yuv_lutyuv(self):
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,
'quality_width': 360,
'quality_height': 240,
'lutyuv_cmd': 'y=2*val',
})
self.runner = VmafQualityRunner([asset],
None,
fifo_mode=False,
delete_workdir=True,
result_store=None)
self.runner.run()
results = self.runner.results
self.assertAlmostEqual(results[0]['VMAF_score'],
77.18873019841408,
places=4)
def test_run_vmafossexec_runner_with_notyuv(self):
print 'test on running VMAF runner...'
ref_path = VmafConfig.test_resource_path("mp4",
"Seeking_30_480_1050.mp4")
dis_path = VmafConfig.test_resource_path("mp4",
"Seeking_10_288_375.mp4")
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={
'yuv_type': 'notyuv',
'quality_width': 360,
'quality_height': 240,
})
self.runner = VmafossExecQualityRunner([asset],
None,
fifo_mode=True,
delete_workdir=True,
result_store=None)
self.runner.run()
results = self.runner.results
self.assertAlmostEqual(results[0]['VMAFOSSEXEC_score'],
79.052553444706504,
places=4)
def test_run_psnr_runner_with_notyuv_gblur(self):
ref_path = VmafConfig.test_resource_path("mp4",
"Seeking_10_288_375.mp4")
dis_path = VmafConfig.test_resource_path("mp4",
"Seeking_10_288_375.mp4")
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={
'yuv_type': 'notyuv',
'quality_width': 720,
'quality_height': 480,
'dis_gblur_cmd': 'sigma=0.01:steps=1',
})
self.runner = PsnrQualityRunner([asset],
None,
fifo_mode=False,
delete_workdir=True,
result_store=None)
self.runner.run()
results = self.runner.results
self.assertAlmostEqual(results[0]['PSNR_score'],
50.99313338666667,
places=4)
def test_run_vmaf_runner_with_notyuv_jpg(self):
print 'test on running VMAF runner on jpg...'
ref_path = VmafConfig.test_resource_path("test_images", "bikes.jpg")
dis_path = VmafConfig.test_resource_path("test_images",
"bikes_dis.jpg")
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={
'yuv_type': 'notyuv',
'quality_width': 512,
'quality_height': 384,
'workfile_yuv_type': 'yuv444p',
})
self.runner = VmafQualityRunner([asset],
None,
fifo_mode=True,
delete_workdir=True,
result_store=None)
self.runner.run()
results = self.runner.results
self.assertAlmostEqual(results[0]['VMAF_score'],
63.27798081002585,
places=4)
def test_run_psnr_runner_with_notyuv(self):
print 'test on running PSNR runner...'
ref_path = VmafConfig.test_resource_path("mp4",
"Seeking_10_288_375.mp4")
dis_path = VmafConfig.test_resource_path("mp4",
"Seeking_10_288_375.mp4")
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={
'yuv_type': 'notyuv',
'quality_width': 720,
'quality_height': 480,
})
self.runner = PsnrQualityRunner([asset],
None,
fifo_mode=True,
delete_workdir=True,
result_store=None)
self.runner.run()
results = self.runner.results
self.assertAlmostEqual(results[0]['PSNR_score'], 60.0, places=4)
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 = VmafQualityRunner(
[asset],
None,
fifo_mode=True,
delete_workdir=True,
result_store=FileSystemResultStore(),
)
self.runner.run()
self.result = self.runner.results[0]
Nframes = len(self.result.result_dict['VMAF_scores'])
self.result.result_dict['VMAF_array_scores'] = self.result.result_dict[
'VMAF_scores'].reshape(Nframes, 1)
self.result.result_dict['VMAF_two_models_array_scores'] = np.vstack(
(self.result.result_dict['VMAF_scores'].reshape(1, Nframes),
self.result.result_dict['VMAF_scores'].reshape(1, Nframes)))
self.result.result_dict['VMAF_3D_array_scores'] = np.zeros((1, 1, 1))
def test_run_vmaf_runner_with_notyuv_jpg(self):
ref_path = VmafConfig.test_resource_path("test_images", "bikes.jpg")
dis_path = VmafConfig.test_resource_path("test_images", "bikes_dis.jpg")
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={'yuv_type': 'notyuv',
'quality_width': 512, 'quality_height': 384,
'workfile_yuv_type': 'yuv444p',
})
self.runner = VmafQualityRunner(
[asset],
None, fifo_mode=True,
delete_workdir=True,
result_store=None,
optional_dict={
'model_filepath': VmafConfig.model_path("vmaf_float_v0.6.1.json"),
},
)
self.runner.run()
results = self.runner.results
self.assertAlmostEqual(results[0]['VMAF_score'], 63.255016130209064, places=4)
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 test_run_vmaf_runner_with_notyuv(self):
ref_path = VmafConfig.test_resource_path("mp4",
"Seeking_30_480_1050.mp4")
dis_path = VmafConfig.test_resource_path("mp4",
"Seeking_10_288_375.mp4")
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={
'yuv_type': 'notyuv',
'quality_width': 360,
'quality_height': 240,
})
self.runner = VmafQualityRunner(
[asset],
None,
fifo_mode=True,
delete_workdir=True,
result_store=None,
optional_dict={
'model_filepath':
VmafConfig.model_path("vmaf_float_v0.6.1.json"),
},
)
self.runner.run()
results = self.runner.results
self.assertAlmostEqual(results[0]['VMAF_score'],
77.61273448644646,
places=4)
def test_run_psnr_runner_with_notyuv(self):
ref_path = VmafConfig.test_resource_path(
"tiff", "src01_hrc00_576x324%05d.tiff", bypass_download=True)
dis_path = VmafConfig.test_resource_path(
"tiff", "src01_hrc01_576x324%05d.tiff", bypass_download=True)
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={
'yuv_type': 'notyuv',
'quality_width': 576,
'quality_height': 324,
})
self.runner = PsnrQualityRunner([asset],
None,
fifo_mode=False,
delete_workdir=True,
result_store=None)
self.runner.run()
results = self.runner.results
pprint.pprint(results[0]['PSNR_scores'])
pprint.pprint(results[0]['PSNR_score'])
self.assertAlmostEqual(results[0]['PSNR_score'], 32.12685675, places=4)
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()
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_strred_fextractor_blackframes(self):
print 'test on running STRRED feature extractor on flat frames...'
ref_path = VmafConfig.test_resource_path("yuv", "flat_1920_1080_0.yuv")
dis_path = VmafConfig.test_resource_path("yuv", "flat_1920_1080_10.yuv")
asset = Asset(dataset="test", content_id=0, asset_id=0,
workdir_root=VmafConfig.workdir_path(),
ref_path=ref_path,
dis_path=dis_path,
asset_dict={'width':576, 'height':324})
asset_original = Asset(dataset="test", content_id=0, asset_id=1,
workdir_root=VmafConfig.workdir_path(),
ref_path=ref_path,
dis_path=ref_path,
asset_dict={'width':576, 'height':324})
from vmaf.core.result_store import FileSystemResultStore
result_store = FileSystemResultStore(logger=None)
self.fextractor = StrredFeatureExtractor(
[asset, asset_original],
None, fifo_mode=True,
result_store=result_store
)
print ' running for the first time with fresh calculation...'
self.fextractor.run(parallelize=True)
result0, result1 = self.fextractor.results
import os
self.assertTrue(os.path.exists(result_store._get_result_file_path(result0)))
self.assertTrue(os.path.exists(result_store._get_result_file_path(result1)))
print ' running for the second time with stored results...'
self.fextractor.run(parallelize=True)
results = self.fextractor.results
# ignore NaN
for result in results:
result.set_score_aggregate_method(ListStats.nonemean)
self.assertAlmostEqual(results[0]['STRRED_feature_srred_score'], 1220.5679849999999, places=4)
self.assertAlmostEqual(results[0]['STRRED_feature_trred_score'], 50983.3097155, places=4)
self.assertAlmostEqual(results[0]['STRRED_feature_strred_score'], 62228595.6081, places=4)
self.assertAlmostEqual(results[1]['STRRED_feature_srred_score'], 0.0, places=4)
self.assertAlmostEqual(results[1]['STRRED_feature_trred_score'], 0.0, places=4)
self.assertAlmostEqual(results[1]['STRRED_feature_strred_score'], 0.0, places=4)
def test_feature_assembler_selected_atom_feature(self):
print 'test on feature assembler with selected atom features...'
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.fassembler = FeatureAssembler(
feature_dict={'VMAF_feature':['vif', 'motion']},
feature_option_dict=None,
assets=[asset, asset_original],
logger=None,
fifo_mode=True,
delete_workdir=True,
result_store=None,
optional_dict=None,
optional_dict2=None,
parallelize=True,
)
self.fassembler.run()
results = self.fassembler.results
self.assertAlmostEqual(results[0]['VMAF_feature_vif_score'], 0.44609306249999997, places=4)
self.assertAlmostEqual(results[0]['VMAF_feature_motion_score'], 4.0498253541666669, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_vif_score'], 1.0, places=4)
self.assertAlmostEqual(results[1]['VMAF_feature_motion_score'], 4.0498253541666669, places=4)
with self.assertRaises(KeyError):
results[0]['VMAF_feature_ansnr_scores']
with self.assertRaises(KeyError):
results[0]['VMAF_feature_ansnr_score']
with self.assertRaises(KeyError):
results[0]['VMAF_feature_adm_scores']
with self.assertRaises(KeyError):
results[0]['VMAF_feature_adm_score']
def test_pad_cmd(self):
asset = Asset(dataset="test", content_id=0, asset_id=0,
ref_path="", dis_path="",
asset_dict={'width':720, 'height':480,
'quality_width':720, 'quality_height':320,
'yuv_type':'yuv422p',
'pad_cmd':'iw+6:ih+4:3:2'})
self.assertEquals(asset.pad_cmd, 'iw+6:ih+4:3:2')
self.assertEquals(str(asset), "test_0_0__720x480_yuv422p_vs__720x480_yuv422p_q_720x320_padiw+6:ih+4:3:2")
asset = Asset(dataset="test", content_id=0, asset_id=0,
ref_path="", dis_path="",
asset_dict={'width':720, 'height':480,
'quality_width':720, 'quality_height':320,
'yuv_type':'yuv422p',})
self.assertTrue(asset.pad_cmd is None)
self.assertEquals(str(asset), "test_0_0__720x480_yuv422p_vs__720x480_yuv422p_q_720x320")
def test_resampling_type(self):
asset = Asset(dataset="test", content_id=0, asset_id=0,
ref_path="", dis_path="",
asset_dict={'fps':24, 'start_sec':2, 'end_sec': 3})
self.assertEquals(asset.resampling_type, 'bicubic')
asset = Asset(dataset="test", content_id=0, asset_id=0,
ref_path="", dis_path="",
asset_dict={'fps':24, 'start_sec':2, 'end_sec': 3,
'resampling_type':'lanczos'})
self.assertEquals(asset.resampling_type, 'lanczos')
asset = Asset(dataset="test", content_id=0, asset_id=0,
ref_path="", dis_path="",
asset_dict={'fps':24, 'start_sec':2, 'end_sec': 3,
'resampling_type':'bicubic'})
self.assertEquals(asset.resampling_type, 'bicubic')
def test_to_normalized_dict(self):
asset = Asset(dataset="test", content_id=0, asset_id=0,
ref_path="dir/refvideo.yuv", dis_path="dir/disvideo.yuv",
asset_dict={'width':720, 'height':480,
'start_frame':2, 'end_frame':2})
self.assertEquals(
asset.to_normalized_dict(),
{
'asset_dict': {'end_frame': 2, 'height': 480, 'start_frame': 2, 'width': 720},
'asset_id': 0,
'content_id': 0,
'dataset': 'test',
'dis_path': 'disvideo.yuv',
'ref_path': 'refvideo.yuv',
'workdir': ''
}
)
def test_to_normalized_dict(self):
asset = Asset(dataset="test", content_id=0, asset_id=0,
ref_path="dir/refvideo.yuv", dis_path="dir/disvideo.yuv",
asset_dict={'width':720, 'height':480,
'start_frame':2, 'end_frame':2})
self.assertEquals(
asset.to_normalized_dict(),
{
'asset_dict': {'end_frame': 2, 'height': 480, 'start_frame': 2, 'width': 720},
'asset_id': 0,
'content_id': 0,
'dataset': 'test',
'dis_path': 'disvideo.yuv',
'ref_path': 'refvideo.yuv',
'workdir': ''
}
)
def test_workdir_root(self):
asset = Asset(dataset="test",
content_id=0,
asset_id=0,
ref_path="",
dis_path="",
asset_dict={},
workdir_root="my_workdir_root")
self.assertEquals(asset.workdir_root, "my_workdir_root")
def test_copy(self):
asset = Asset(dataset="test", content_id=0, asset_id=0,
ref_path="", dis_path="",
asset_dict={'width':720, 'height':480,
'quality_width':720, 'quality_height':320,
'yuv_type':'yuv422p',
'crop_cmd':'570:320:3:2'})
new_asset = asset.copy()
self.assertEquals(asset, new_asset)
self.assertTrue(asset == new_asset)
self.assertNotEquals(id(asset), id(new_asset))
new_asset.asset_dict['yuv_type'] = 'yuv444p'
self.assertNotEquals(asset, new_asset)
new_asset2 = asset.copy(content_id=2)
self.assertFalse(asset == new_asset2)
self.assertEquals(new_asset2.content_id, 2)
self.assertEquals(new_asset2.asset_id, 0)
def test_use_path_as_workpath(self):
asset = Asset(dataset="test", content_id=0, asset_id=0,
ref_path="dir/refvideo.yuv", dis_path="dir/disvideo.yuv",
asset_dict={'width':720, 'height':480,
'start_frame':2, 'end_frame':2,
'quality_width':1920, 'quality_height':1080},
workdir_root="workdir")
expected_ref_workfile_path_re = \
r"^workdir/[a-zA-Z0-9-]+/" \
r"ref_test_0_0_refvideo_720x480_2to2_vs_disvideo_720x480_2to2_q_1920x1080"
expected_dis_workfile_path_re = \
r"^workdir/[a-zA-Z0-9-]+/" \
r"dis_test_0_0_refvideo_720x480_2to2_vs_disvideo_720x480_2to2_q_1920x1080"
self.assertTrue(re.match(expected_ref_workfile_path_re, asset.ref_workfile_path))
self.assertTrue(re.match(expected_dis_workfile_path_re, asset.dis_workfile_path))
self.assertFalse('use_path_as_workpath' in asset.asset_dict)
asset.use_path_as_workpath = True
self.assertTrue('use_path_as_workpath' in asset.asset_dict)
self.assertTrue(asset.asset_dict['use_path_as_workpath'])
self.assertEquals(asset.ref_workfile_path, 'dir/refvideo.yuv')
self.assertEquals(asset.dis_workfile_path, 'dir/disvideo.yuv')
def from_dataframe(cls, df):
# first, make sure the df conform to the format for a single asset
cls._assert_asset_dataframe(df)
asset_repr = df.iloc[0]['asset']
asset = Asset.from_repr(asset_repr)
executor_id = df.iloc[0]['executor_id']
result_dict = {}
for _, row in df.iterrows():
result_dict[row['scores_key']] = row['scores']
return Result(asset, executor_id, result_dict)
def test_str_repr(self):
asset = Asset(dataset="test", content_id=0, asset_id=0,
ref_path="dir/refvideo.yuv", dis_path="dir/disvideo.yuv",
asset_dict={'width':720, 'height':480,
'start_frame':2, 'end_frame':2})
self.assertEquals(
str(asset),
"test_0_0_refvideo_720x480_2to2_vs_disvideo_720x480_2to2_q_720x480"
)
expected_repr = '{"asset_dict": {"end_frame": 2, "height": 480, "start_frame": 2, "width": 720}, "asset_id": 0, "content_id": 0, "dataset": "test", "dis_path": "disvideo.yuv", "ref_path": "refvideo.yuv", "workdir": ""}' # noqa
self.assertEquals(repr(asset), expected_repr)
recon_asset = Asset.from_repr(expected_repr)
self.assertEquals(asset, recon_asset)
self.assertTrue(asset == recon_asset)
self.assertFalse(asset != recon_asset)
self.assertEquals(asset.to_normalized_repr(), expected_repr)
asset = Asset(dataset="test", content_id=0, asset_id=1,
ref_path="dir/refvideo.yuv", dis_path="dir/disvideo.yuv",
asset_dict={'width':720, 'height':480,})
self.assertEquals(
str(asset),
"test_0_1_refvideo_720x480_vs_disvideo_720x480_q_720x480"
)
expected_repr = '{"asset_dict": {"height": 480, "width": 720}, "asset_id": 1, "content_id": 0, "dataset": "test", "dis_path": "disvideo.yuv", "ref_path": "refvideo.yuv", "workdir": ""}'
self.assertEquals(repr(asset), expected_repr)
recon_asset = Asset.from_repr(expected_repr)
self.assertEquals(asset, recon_asset)
asset = Asset(dataset="test", content_id=0, asset_id=2,
ref_path="dir/refvideo.yuv", dis_path="dir/disvideo.yuv",
asset_dict={'width':720, 'height':480,
'quality_width':1920, 'quality_height':1080})
self.assertEquals(
str(asset),
"test_0_2_refvideo_720x480_vs_disvideo_720x480_q_1920x1080"
)
expected_repr = '{"asset_dict": {"height": 480, "quality_height": 1080, "quality_width": 1920, "width": 720}, "asset_id": 2, "content_id": 0, "dataset": "test", "dis_path": "disvideo.yuv", "ref_path": "refvideo.yuv", "workdir": ""}' # noqa
self.assertEquals(repr(asset), expected_repr)
recon_asset = Asset.from_repr(expected_repr)
self.assertEquals(asset, recon_asset)
asset = Asset(dataset="test", content_id=0, asset_id=2,
ref_path="dir/refvideo.yuv", dis_path="dir/disvideo.yuv",
asset_dict={'width':720, 'height':480,
'quality_width':1920, 'quality_height':1080,
'yuv_type':'yuv422p'})
self.assertEquals(
str(asset),
"test_0_2_refvideo_720x480_yuv422p_vs_disvideo_720x480_yuv422p_q_1920x1080"
)
expected_repr = '{"asset_dict": {"height": 480, "quality_height": 1080, "quality_width": 1920, "width": 720, "yuv_type": "yuv422p"}, "asset_id": 2, "content_id": 0, "dataset": "test", "dis_path": "disvideo.yuv", "ref_path": "refvideo.yuv", "workdir": ""}' # noqa
self.assertEquals(repr(asset), expected_repr)
recon_asset = Asset.from_repr(expected_repr)
self.assertEquals(asset, recon_asset)
asset = Asset(dataset="test", content_id=0, asset_id=2,
ref_path="dir/refvideo.yuv", dis_path="dir/disvideo.yuv",
asset_dict={'width':720, 'height':480,
'quality_width':1920, 'quality_height':1080,
'resampling_type':'lanczos'})
self.assertEquals(
str(asset),
"test_0_2_refvideo_720x480_vs_disvideo_720x480_q_1920x1080_lanczos"
)
expected_repr = '{"asset_dict": {"height": 480, "quality_height": 1080, "quality_width": 1920, "resampling_type": "lanczos", "width": 720}, "asset_id": 2, "content_id": 0, "dataset": "test", "dis_path": "disvideo.yuv", "ref_path": "refvideo.yuv", "workdir": ""}' # noqa
self.assertEquals(repr(asset), expected_repr)
recon_asset = Asset.from_repr(expected_repr)
self.assertEquals(asset, recon_asset)
