mirror of
https://github.com/SickGear/SickGear.git
synced 2024-11-24 05:45:05 +00:00
147 lines
6 KiB
Python
147 lines
6 KiB
Python
|
#!/usr/bin/env python2
|
||
|
# -*- coding: utf-8 -*-
|
||
|
#
|
||
|
# GuessIt - A library for guessing information from filenames
|
||
|
# Copyright (c) 2012 Nicolas Wack <wackou@gmail.com>
|
||
|
#
|
||
|
# GuessIt is free software; you can redistribute it and/or modify it under
|
||
|
# the terms of the Lesser GNU General Public License as published by
|
||
|
# the Free Software Foundation; either version 3 of the License, or
|
||
|
# (at your option) any later version.
|
||
|
#
|
||
|
# GuessIt is distributed in the hope that it will be useful,
|
||
|
# but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||
|
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||
|
# Lesser GNU General Public License for more details.
|
||
|
#
|
||
|
# You should have received a copy of the Lesser GNU General Public License
|
||
|
# along with this program. If not, see <http://www.gnu.org/licenses/>.
|
||
|
#
|
||
|
|
||
|
from __future__ import unicode_literals
|
||
|
from guessit.transfo import found_property
|
||
|
from guessit.patterns import non_episode_title, unlikely_series
|
||
|
import logging
|
||
|
|
||
|
log = logging.getLogger(__name__)
|
||
|
|
||
|
|
||
|
def match_from_epnum_position(mtree, node):
|
||
|
epnum_idx = node.node_idx
|
||
|
|
||
|
# a few helper functions to be able to filter using high-level semantics
|
||
|
def before_epnum_in_same_pathgroup():
|
||
|
return [ leaf for leaf in mtree.unidentified_leaves()
|
||
|
if (leaf.node_idx[0] == epnum_idx[0] and
|
||
|
leaf.node_idx[1:] < epnum_idx[1:]) ]
|
||
|
|
||
|
def after_epnum_in_same_pathgroup():
|
||
|
return [ leaf for leaf in mtree.unidentified_leaves()
|
||
|
if (leaf.node_idx[0] == epnum_idx[0] and
|
||
|
leaf.node_idx[1:] > epnum_idx[1:]) ]
|
||
|
|
||
|
def after_epnum_in_same_explicitgroup():
|
||
|
return [ leaf for leaf in mtree.unidentified_leaves()
|
||
|
if (leaf.node_idx[:2] == epnum_idx[:2] and
|
||
|
leaf.node_idx[2:] > epnum_idx[2:]) ]
|
||
|
|
||
|
# epnumber is the first group and there are only 2 after it in same
|
||
|
# path group
|
||
|
# -> series title - episode title
|
||
|
title_candidates = [ n for n in after_epnum_in_same_pathgroup()
|
||
|
if n.clean_value.lower() not in non_episode_title ]
|
||
|
if ('title' not in mtree.info and # no title
|
||
|
before_epnum_in_same_pathgroup() == [] and # no groups before
|
||
|
len(title_candidates) == 2): # only 2 groups after
|
||
|
|
||
|
found_property(title_candidates[0], 'series', confidence=0.4)
|
||
|
found_property(title_candidates[1], 'title', confidence=0.4)
|
||
|
return
|
||
|
|
||
|
# if we have at least 1 valid group before the episodeNumber, then it's
|
||
|
# probably the series name
|
||
|
series_candidates = before_epnum_in_same_pathgroup()
|
||
|
if len(series_candidates) >= 1:
|
||
|
found_property(series_candidates[0], 'series', confidence=0.7)
|
||
|
|
||
|
# only 1 group after (in the same path group) and it's probably the
|
||
|
# episode title
|
||
|
title_candidates = [ n for n in after_epnum_in_same_pathgroup()
|
||
|
if n.clean_value.lower() not in non_episode_title ]
|
||
|
|
||
|
if len(title_candidates) == 1:
|
||
|
found_property(title_candidates[0], 'title', confidence=0.5)
|
||
|
return
|
||
|
else:
|
||
|
# try in the same explicit group, with lower confidence
|
||
|
title_candidates = [ n for n in after_epnum_in_same_explicitgroup()
|
||
|
if n.clean_value.lower() not in non_episode_title
|
||
|
]
|
||
|
if len(title_candidates) == 1:
|
||
|
found_property(title_candidates[0], 'title', confidence=0.4)
|
||
|
return
|
||
|
elif len(title_candidates) > 1:
|
||
|
found_property(title_candidates[0], 'title', confidence=0.3)
|
||
|
return
|
||
|
|
||
|
# get the one with the longest value
|
||
|
title_candidates = [ n for n in after_epnum_in_same_pathgroup()
|
||
|
if n.clean_value.lower() not in non_episode_title ]
|
||
|
if title_candidates:
|
||
|
maxidx = -1
|
||
|
maxv = -1
|
||
|
for i, c in enumerate(title_candidates):
|
||
|
if len(c.clean_value) > maxv:
|
||
|
maxidx = i
|
||
|
maxv = len(c.clean_value)
|
||
|
found_property(title_candidates[maxidx], 'title', confidence=0.3)
|
||
|
|
||
|
|
||
|
def process(mtree):
|
||
|
eps = [node for node in mtree.leaves() if 'episodeNumber' in node.guess]
|
||
|
if eps:
|
||
|
match_from_epnum_position(mtree, eps[0])
|
||
|
|
||
|
else:
|
||
|
# if we don't have the episode number, but at least 2 groups in the
|
||
|
# basename, then it's probably series - eptitle
|
||
|
basename = mtree.node_at((-2,))
|
||
|
title_candidates = [ n for n in basename.unidentified_leaves()
|
||
|
if n.clean_value.lower() not in non_episode_title
|
||
|
]
|
||
|
|
||
|
if len(title_candidates) >= 2:
|
||
|
found_property(title_candidates[0], 'series', 0.4)
|
||
|
found_property(title_candidates[1], 'title', 0.4)
|
||
|
elif len(title_candidates) == 1:
|
||
|
# but if there's only one candidate, it's probably the series name
|
||
|
found_property(title_candidates[0], 'series', 0.4)
|
||
|
|
||
|
# if we only have 1 remaining valid group in the folder containing the
|
||
|
# file, then it's likely that it is the series name
|
||
|
try:
|
||
|
series_candidates = mtree.node_at((-3,)).unidentified_leaves()
|
||
|
except ValueError:
|
||
|
series_candidates = []
|
||
|
|
||
|
if len(series_candidates) == 1:
|
||
|
found_property(series_candidates[0], 'series', 0.3)
|
||
|
|
||
|
# if there's a path group that only contains the season info, then the
|
||
|
# previous one is most likely the series title (ie: ../series/season X/..)
|
||
|
eps = [ node for node in mtree.nodes()
|
||
|
if 'season' in node.guess and 'episodeNumber' not in node.guess ]
|
||
|
|
||
|
if eps:
|
||
|
previous = [ node for node in mtree.unidentified_leaves()
|
||
|
if node.node_idx[0] == eps[0].node_idx[0] - 1 ]
|
||
|
if len(previous) == 1:
|
||
|
found_property(previous[0], 'series', 0.5)
|
||
|
|
||
|
# reduce the confidence of unlikely series
|
||
|
for node in mtree.nodes():
|
||
|
if 'series' in node.guess:
|
||
|
if node.guess['series'].lower() in unlikely_series:
|
||
|
new_confidence = node.guess.confidence('series') * 0.5
|
||
|
node.guess.set_confidence('series', new_confidence)
|