def _generate_result(self, asset):
# routine to call the command-line executable and generate feature
# scores in the log file.
quality_width, quality_height = asset.quality_width_height
log_file_path = self._get_log_file_path(asset)
yuv_type = self._get_workfile_yuv_type(asset)
ref_path = asset.ref_procfile_path
dis_path = asset.dis_procfile_path
w = quality_width
h = quality_height
logger = self.logger
ExternalProgramCaller.call_vmafexec_multi_features(
['float_adm', 'float_vif', 'float_motion', 'float_ansnr'],
yuv_type,
ref_path,
dis_path,
w,
h,
log_file_path,
logger,
options={
'float_adm': {
'debug': True
},
'float_vif': {
'debug': True
},
'float_motion': {
'debug': True
},
})
def _generate_result(self, asset):
quality_width, quality_height = asset.quality_width_height
log_file_path = self._get_log_file_path(asset)
yuv_type = self._get_workfile_yuv_type(asset)
ref_path = asset.ref_procfile_path
dis_path = asset.dis_procfile_path
w = quality_width
h = quality_height
logger = self.logger
ExternalProgramCaller.call_vmafexec_multi_features(
['adm', 'vif', 'motion', 'float_ansnr'],
yuv_type,
ref_path,
dis_path,
w,
h,
log_file_path,
logger,
options={
'adm': {
'debug': True
},
'vif': {
'debug': True
},
'motion': {
'debug': True
},
})
def _generate_result(self, asset):
# routine to call the command-line executable and generate quality
# scores in the log file.
quality_width, quality_height = asset.quality_width_height
assert asset.dis_encode_width_height is not None, \
'For Cambi, dis_encode_width_height cannot be None. One can specify dis_encode_width_height by adding ' \
'the following fields to asset_dict: 1) dis_enc_width and dis_enc_height, or 2) dis_width and ' \
'dis_height, or 3) width and height.'
encode_width, encode_height = asset.dis_encode_width_height
if encode_width != quality_width or encode_height != quality_height:
# hacky: unintended consequence of modifying the input. TODO: improve.
if self.optional_dict is None:
self.optional_dict = dict()
self.optional_dict['enc_width'] = encode_width
self.optional_dict['enc_height'] = encode_height
log_file_path = self._get_log_file_path(asset)
yuv_type = self._get_workfile_yuv_type(asset)
ref_path = asset.ref_procfile_path
dis_path = asset.dis_procfile_path
logger = self.logger
ExternalProgramCaller.call_vmafexec_single_feature(
'cambi',
yuv_type,
ref_path,
dis_path,
quality_width,
quality_height,
log_file_path,
logger,
options=self.optional_dict)
def _generate_result(self, asset):
# routine to call the command-line executable and generate quality
# scores in the log file.
quality_width, quality_height = asset.quality_width_height
encode_width, encode_height = asset.dis_encode_width_height
if encode_width != quality_width or encode_height != quality_height:
self.optional_dict['enc_width'] = encode_width
self.optional_dict['enc_height'] = encode_height
log_file_path = self._get_log_file_path(asset)
yuv_type = self._get_workfile_yuv_type(asset)
ref_path = asset.ref_procfile_path
dis_path = asset.dis_procfile_path
logger = self.logger
ExternalProgramCaller.call_vmafexec_single_feature(
'cambi',
yuv_type,
ref_path,
dis_path,
quality_width,
quality_height,
log_file_path,
logger,
options=self.optional_dict)
def _generate_result(self, asset):
# routine to call the command-line executable and generate quality
# scores in the log file.
log_file_path = self._get_log_file_path(asset)
if self.optional_dict is not None \
and 'model_filepath' in self.optional_dict \
and self.optional_dict['model_filepath'] is not None:
model_filepath = self.optional_dict['model_filepath']
else:
model_filepath = self.DEFAULT_MODEL_FILEPATH
if self.optional_dict is not None and 'disable_clip_score' in self.optional_dict:
disable_clip_score = self.optional_dict['disable_clip_score']
else:
disable_clip_score = False
if self.optional_dict is not None and 'enable_transform_score' in self.optional_dict:
enable_transform_score = self.optional_dict[
'enable_transform_score']
else:
enable_transform_score = False
if self.optional_dict is not None and 'phone_model' in self.optional_dict:
phone_model = self.optional_dict['phone_model']
else:
phone_model = False
if self.optional_dict is not None and 'disable_avx' in self.optional_dict:
disable_avx = self.optional_dict['disable_avx']
else:
disable_avx = False
if self.optional_dict is not None and 'thread' in self.optional_dict:
n_thread = self.optional_dict['thread']
else:
n_thread = 0
if self.optional_dict is not None and 'subsample' in self.optional_dict:
n_subsample = self.optional_dict['subsample']
else:
n_subsample = 1
quality_width, quality_height = asset.quality_width_height
fmt = self._get_workfile_yuv_type(asset)
w = quality_width
h = quality_height
ref_path = asset.ref_workfile_path
dis_path = asset.dis_workfile_path
model = model_filepath
exe = self._get_exec()
logger = self.logger
ExternalProgramCaller.call_vmafossexec(
fmt, w, h, ref_path, dis_path, model, log_file_path,
disable_clip_score, enable_transform_score, phone_model,
disable_avx, n_thread, n_subsample, exe, logger)
def _generate_result(self, asset):
quality_width, quality_height = asset.quality_width_height
log_file_path = self._get_log_file_path(asset)
yuv_type = self._get_workfile_yuv_type(asset)
ref_path = asset.ref_procfile_path
dis_path = asset.dis_procfile_path
w = quality_width
h = quality_height
logger = self.logger
features = ['adm', 'vif', 'motion', 'float_ansnr']
options = {
'adm': {
'debug': True
},
'vif': {
'debug': True
},
'motion': {
'debug': True
},
}
if self.optional_dict is not None:
for opt in self.optional_dict:
if opt == 'vif_enhn_gain_limit':
options['vif']['vif_enhn_gain_limit'] = self.optional_dict[
'vif_enhn_gain_limit']
elif opt == 'adm_enhn_gain_limit':
options['adm']['adm_enhn_gain_limit'] = self.optional_dict[
'adm_enhn_gain_limit']
elif opt == 'adm_norm_view_dist':
options['adm']['adm_norm_view_dist'] = self.optional_dict[
'adm_norm_view_dist']
elif opt == 'adm_ref_display_height':
options['adm'][
'adm_ref_display_height'] = self.optional_dict[
'adm_ref_display_height']
elif opt == 'motion_force_zero':
options['motion'][
'motion_force_zero'] = self.optional_dict[
'motion_force_zero']
else:
pass
ExternalProgramCaller.call_vmafexec_multi_features(features,
yuv_type,
ref_path,
dis_path,
w,
h,
log_file_path,
logger,
options=options)
def _generate_result(self, asset):
# routine to call the command-line executable and generate quality
# scores in the log file.
quality_width, quality_height = asset.quality_width_height
log_file_path = self._get_log_file_path(asset)
yuv_type=self._get_workfile_yuv_type(asset)
ref_path=asset.ref_workfile_path
dis_path=asset.dis_workfile_path
w=quality_width
h=quality_height
logger = self.logger
ExternalProgramCaller.call_ms_ssim(yuv_type, ref_path, dis_path, w, h, log_file_path, logger)
def _generate_result(self, asset):
# routine to call the command-line executable and generate quality
# scores in the log file.
quality_width, quality_height = asset.quality_width_height
log_file_path = self._get_log_file_path(asset)
yuv_type=self._get_workfile_yuv_type(asset)
ref_path=asset.ref_workfile_path
dis_path=asset.dis_workfile_path
w=quality_width
h=quality_height
logger = self.logger
ExternalProgramCaller.call_ms_ssim(yuv_type, ref_path, dis_path, w, h, log_file_path, logger)
def _generate_result(self, asset):
# routine to call the command-line executable and generate quality
# scores in the log file.
quality_width, quality_height = asset.quality_width_height
log_file_path = self._get_log_file_path(asset)
yuv_type=self._get_workfile_yuv_type(asset)
ref_path=asset.ref_procfile_path
dis_path=asset.dis_procfile_path
w=quality_width
h=quality_height
logger = self.logger
ExternalProgramCaller.call_vmafrc_single_feature('float_ms_ssim', yuv_type, ref_path, dis_path, w, h,
log_file_path, logger, options={'enable_lcs': True})
def _generate_result(self, asset):
# routine to call the command-line executable and generate quality
# scores in the log file.
log_file_path = self._get_log_file_path(asset)
if self.optional_dict is not None \
and 'model_filepath' in self.optional_dict \
and self.optional_dict['model_filepath'] is not None:
model_filepath = self.optional_dict['model_filepath']
else:
model_filepath = self.DEFAULT_MODEL_FILEPATH
if self.optional_dict is not None and 'disable_clip_score' in self.optional_dict:
disable_clip_score = self.optional_dict['disable_clip_score']
else:
disable_clip_score = False
if self.optional_dict is not None and 'enable_transform_score' in self.optional_dict:
enable_transform_score = self.optional_dict['enable_transform_score']
else:
enable_transform_score = False
if self.optional_dict is not None and 'phone_model' in self.optional_dict:
phone_model = self.optional_dict['phone_model']
else:
phone_model = False
if self.optional_dict is not None and 'disable_avx' in self.optional_dict:
disable_avx = self.optional_dict['disable_avx']
else:
disable_avx = False
quality_width, quality_height = asset.quality_width_height
fmt=self._get_workfile_yuv_type(asset)
w=quality_width
h=quality_height
ref_path=asset.ref_workfile_path
dis_path=asset.dis_workfile_path
model=model_filepath
exe=self._get_exec()
logger = self.logger
ExternalProgramCaller.call_vmafossexec(fmt, w, h, ref_path, dis_path, model, log_file_path,
disable_clip_score, enable_transform_score,
phone_model, disable_avx, exe, logger)
def _generate_result(self, asset):
# routine to call the command-line executable and generate feature
# scores in the log file.
quality_width, quality_height = asset.quality_width_height
log_file_path = self._get_log_file_path(asset)
yuv_type = self._get_workfile_yuv_type(asset)
ref_path = asset.ref_procfile_path
dis_path = asset.dis_procfile_path
w = quality_width
h = quality_height
logger = self.logger
features = ['float_adm', 'float_vif', 'float_motion', 'float_ansnr']
options = {
'float_adm': {
'debug': True
},
'float_vif': {
'debug': True
},
'float_motion': {
'debug': True
},
}
if self.optional_dict is not None:
for opt in self.optional_dict:
if opt == 'vif_enhn_gain_limit':
options['float_vif'][
'vif_enhn_gain_limit'] = self.optional_dict[
'vif_enhn_gain_limit']
elif opt == 'vif_kernelscale':
options['float_vif'][
'vif_kernelscale'] = self.optional_dict[
'vif_kernelscale']
elif opt == 'adm_enhn_gain_limit':
options['float_adm'][
'adm_enhn_gain_limit'] = self.optional_dict[
'adm_enhn_gain_limit']
elif opt == 'adm_norm_view_dist':
options['float_adm'][
'adm_norm_view_dist'] = self.optional_dict[
'adm_norm_view_dist']
elif opt == 'adm_ref_display_height':
options['float_adm'][
'adm_ref_display_height'] = self.optional_dict[
'adm_ref_display_height']
elif opt == 'motion_force_zero':
options['float_motion'][
'motion_force_zero'] = self.optional_dict[
'motion_force_zero']
else:
pass
if self.optional_dict2 is not None:
for opt in self.optional_dict2:
if opt == 'disable_avx':
options['disable_avx'] = self.optional_dict2['disable_avx']
ExternalProgramCaller.call_vmafexec_multi_features(features,
yuv_type,
ref_path,
dis_path,
w,
h,
log_file_path,
logger,
options=options)
