def ListOneTarget(codecs,
rate,
videofile,
do_score,
datatable,
score_function=None):
"""Extend a datatable with the info about one video file's scores."""
for codec_name in codecs:
# For testing:
# Allow for direct context injection rather than picking by name.
if isinstance(codec_name, basestring):
codec = pick_codec.PickCodec(codec_name)
my_optimizer = optimizer.Optimizer(codec,
score_function=score_function)
else:
my_optimizer = codec_name
codec_name = my_optimizer.context.codec.name
bestsofar = my_optimizer.BestEncoding(rate, videofile)
if do_score and not bestsofar.Result():
bestsofar.Execute()
bestsofar.Store()
assert (bestsofar.Result())
# Ignore results that score less than zero.
if my_optimizer.Score(bestsofar) < 0.0:
return
(datatable.setdefault(codec_name,
{}).setdefault(videofile.basename, []).append(
(bestsofar.result['bitrate'],
bestsofar.result['psnr'])))
def test_DistinctWorkdirs(self):
seen_dirs = set()
for codec_name in pick_codec.AllCodecNames():
codec = pick_codec.PickCodec(codec_name)
context = encoder.Context(codec)
workdir = os.path.abspath(context.cache.WorkDir())
self.assertNotIn(
workdir, seen_dirs,
'Duplicate workdir %s for codec %s' % (workdir, codec_name))
seen_dirs.add(workdir)
def ListOneTarget(codecs,
rate,
videofile,
do_score,
datatable,
score_function=None,
full_results=False):
"""Extend a datatable with the info about one video file's scores."""
for codec_name in codecs:
# For testing:
# Allow for direct context injection rather than picking by name.
if isinstance(codec_name, basestring):
codec = pick_codec.PickCodec(codec_name)
my_optimizer = optimizer.Optimizer(codec,
score_function=score_function)
else:
my_optimizer = codec_name
codec_name = my_optimizer.context.codec.name
bestsofar = my_optimizer.BestEncoding(rate, videofile)
if do_score and not bestsofar.Result():
bestsofar.Execute()
bestsofar.Store()
assert (bestsofar.Result())
# Ignore results that score less than zero.
if my_optimizer.Score(bestsofar) < 0.0:
return
if full_results:
# Datatable is a dictionary of codec name -> result sets.
# Each result set is an array containing result info.
# Each result info is a dictionary containing the
# ID of the configuration used, the
# target bitrate, the command line, the score and the result.
(datatable.setdefault(codec_name, {}).setdefault(
videofile.basename, []).append({
'config_id':
bestsofar.encoder.Hashname(),
'target_bitrate':
rate,
'encode_command':
bestsofar.EncodeCommandLine(),
'score':
my_optimizer.Score(bestsofar),
'result':
bestsofar.ResultWithoutFrameData()
}))
else:
# Datatable is a dictionary of codec name -> result sets.
# Each result set is an array containing result info.
# Each result info contains the achieved bitrate and the PSNR.
(datatable.setdefault(codec_name, {}).setdefault(
videofile.basename, []).append(
(bestsofar.result['bitrate'], bestsofar.result['psnr'])))
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--codec')
parser.add_argument('--score', action='store_true', default=False)
args = parser.parse_args()
codec = pick_codec.PickCodec(args.codec)
for classname in mpeg_settings.files.keys():
for filename in mpeg_settings.files[classname]:
for rate in mpeg_settings.rates[classname]:
videofile = encoder.Videofile('../mpeg_video/%s' % filename)
encoding = codec.BestEncoding(rate, videofile)
print rate, filename, encoding.Score(), encoding.result
AnalyzeVariants(encoding, args.score)
return 0
def ListMpegSingleConfigResults(codecs, datatable, score_function=None):
encoder_list = {}
optimizer_list = {}
for codec_name in codecs:
codec = pick_codec.PickCodec(codec_name)
my_optimizer = optimizer.Optimizer(codec,
score_function=score_function,
file_set=mpeg_settings.MpegFiles())
optimizer_list[codec_name] = my_optimizer
encoder_list[codec_name] = my_optimizer.BestOverallEncoder()
for rate, filename in sorted(mpeg_settings.MpegFiles().AllFilesAndRates()):
videofile = encoder.Videofile(filename)
for codec_name in codecs:
if encoder_list[codec_name]:
my_encoding = encoder_list[codec_name].Encoding(
rate, videofile)
my_encoding.Recover()
AddOneEncoding(codec_name, optimizer_list[codec_name],
my_encoding, videofile, datatable)
def ListOneTarget(codecs,
rate,
videofile,
do_score,
datatable,
score_function=None):
"""Extend a datatable with the info about one video file's scores."""
# pylint: disable=too-many-arguments
for codec_name in codecs:
# For testing:
# Allow for direct context injection rather than picking by name.
if isinstance(codec_name, basestring):
codec = pick_codec.PickCodec(codec_name)
my_optimizer = optimizer.Optimizer(codec,
score_function=score_function)
else:
my_optimizer = codec_name
codec_name = my_optimizer.context.codec.name
best_encoding = my_optimizer.BestEncoding(rate, videofile)
if do_score and not best_encoding.Result():
best_encoding.Execute()
best_encoding.Store()
AddOneEncoding(codec_name, my_optimizer, best_encoding, videofile,
datatable)