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ffmpeg2vmaf.py
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#!/usr/bin/env python
import sys
import os
import numpy as np
from vmaf.config import VmafConfig
from vmaf.core.asset import Asset
from vmaf.core.quality_runner import VmafQualityRunner
from vmaf.core.quality_runner_extra import VmafQualityRunnerWithLocalExplainer
from vmaf.tools.misc import get_file_name_without_extension, get_cmd_option, \
cmd_option_exists
from vmaf.tools.stats import ListStats
__copyright__ = "Copyright 2016-2017, Netflix, Inc."
__license__ = "Apache, Version 2.0"
OUT_FMTS = ['text (default)', 'xml', 'json']
POOL_METHODS = ['mean', 'harmonic_mean', 'min', 'median', 'perc5', 'perc10', 'perc20']
def print_usage():
print "usage: " + os.path.basename(sys.argv[0]) \
+ " quality_width quality_height ref_path dis_path [--model model_path] [--out-fmt out_fmt] [--work-dir work_dir] [--phone-model]\n"
print "out_fmt:\n\t" + "\n\t".join(OUT_FMTS) + "\n"
def main():
if len(sys.argv) < 5:
print_usage()
return 2
try:
q_width = int(sys.argv[1])
q_height = int(sys.argv[2])
ref_file = sys.argv[3]
dis_file = sys.argv[4]
except ValueError:
print_usage()
return 2
if q_width < 0 or q_height < 0:
print "quality_width and quality_height must be non-negative, but are {w} and {h}".format(w=q_width, h=q_height)
print_usage()
return 2
model_path = get_cmd_option(sys.argv, 5, len(sys.argv), '--model')
out_fmt = get_cmd_option(sys.argv, 5, len(sys.argv), '--out-fmt')
if not (out_fmt is None
or out_fmt == 'xml'
or out_fmt == 'json'
or out_fmt == 'text'):
print_usage()
return 2
work_dir = get_cmd_option(sys.argv, 5, len(sys.argv), '--work-dir')
pool_method = get_cmd_option(sys.argv, 5, len(sys.argv), '--pool')
if not (pool_method is None
or pool_method in POOL_METHODS):
print '--pool can only have option among {}'.format(', '.join(POOL_METHODS))
return 2
show_local_explanation = cmd_option_exists(sys.argv, 5, len(sys.argv), '--local-explain')
phone_model = cmd_option_exists(sys.argv, 5, len(sys.argv), '--phone-model')
if work_dir is None:
work_dir = VmafConfig.workdir_path()
asset = Asset(dataset="cmd",
content_id=abs(hash(get_file_name_without_extension(ref_file))) % (10 ** 16),
asset_id=abs(hash(get_file_name_without_extension(ref_file))) % (10 ** 16),
workdir_root=work_dir,
ref_path=ref_file,
dis_path=dis_file,
asset_dict={'quality_width':q_width, 'quality_height':q_height, 'yuv_type': 'notyuv'}
)
assets = [asset]
if not show_local_explanation:
runner_class = VmafQualityRunner
else:
runner_class = VmafQualityRunnerWithLocalExplainer
if model_path is None:
optional_dict = None
else:
optional_dict = {'model_filepath':model_path}
if phone_model:
if optional_dict is None:
optional_dict = {}
optional_dict['enable_transform_score'] = True
runner = runner_class(
assets, None, fifo_mode=True,
delete_workdir=True,
result_store=None,
optional_dict=optional_dict,
optional_dict2=None,
)
# run
runner.run()
result = runner.results[0]
# pooling
if pool_method == 'harmonic_mean':
result.set_score_aggregate_method(ListStats.harmonic_mean)
elif pool_method == 'min':
result.set_score_aggregate_method(np.min)
elif pool_method == 'median':
result.set_score_aggregate_method(np.median)
elif pool_method == 'perc5':
result.set_score_aggregate_method(ListStats.perc5)
elif pool_method == 'perc10':
result.set_score_aggregate_method(ListStats.perc10)
elif pool_method == 'perc20':
result.set_score_aggregate_method(ListStats.perc20)
else: # None or 'mean'
pass
# output
if out_fmt == 'xml':
print result.to_xml()
elif out_fmt == 'json':
print result.to_json()
else: # None or 'text'
print str(result)
# local explanation
if show_local_explanation:
import matplotlib.pyplot as plt
runner.show_local_explanations([result])
plt.show()
return 0
if __name__ == "__main__":
ret = main()
exit(ret)