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136 lines
5.2 KiB
Python
136 lines
5.2 KiB
Python
#!/usr/bin/env python
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"""
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Unit Name: hs.picture._match
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Created By: Virgil Dupras
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Created On: 2007/02/25
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Last modified by:$Author: virgil $
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Last modified on:$Date: 2009-05-28 16:02:48 +0200 (Thu, 28 May 2009) $
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$Revision: 4388 $
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Copyright 2007 Hardcoded Software (http://www.hardcoded.net)
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"""
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import logging
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import multiprocessing
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from Queue import Empty
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from collections import defaultdict
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from hsutil import job
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from hsutil.misc import dedupe
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from dupeguru.engine import Match
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from block import avgdiff, DifferentBlockCountError, NoBlocksError
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from cache import Cache
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MIN_ITERATIONS = 3
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def get_match(first,second,percentage):
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if percentage < 0:
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percentage = 0
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return Match(first,second,percentage)
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class MatchFactory(object):
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cached_blocks = None
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block_count_per_side = 15
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threshold = 75
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match_scaled = False
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def _do_getmatches(self, files, j):
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raise NotImplementedError()
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def getmatches(self, files, j=job.nulljob):
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# The MemoryError handlers in there use logging without first caring about whether or not
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# there is enough memory left to carry on the operation because it is assumed that the
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# MemoryError happens when trying to read an image file, which is freed from memory by the
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# time that MemoryError is raised.
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j = j.start_subjob([2, 8])
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logging.info('Preparing %d files' % len(files))
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prepared = self.prepare_files(files, j)
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logging.info('Finished preparing %d files' % len(prepared))
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return self._do_getmatches(prepared, j)
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def prepare_files(self, files, j=job.nulljob):
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prepared = [] # only files for which there was no error getting blocks
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try:
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for picture in j.iter_with_progress(files, 'Analyzed %d/%d pictures'):
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picture.dimensions
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picture.unicode_path = unicode(picture.path)
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try:
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if picture.unicode_path not in self.cached_blocks:
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blocks = picture.get_blocks(self.block_count_per_side)
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self.cached_blocks[picture.unicode_path] = blocks
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prepared.append(picture)
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except IOError as e:
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logging.warning(unicode(e))
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except MemoryError:
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logging.warning(u'Ran out of memory while reading %s of size %d' % (picture.unicode_path, picture.size))
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if picture.size < 10 * 1024 * 1024: # We're really running out of memory
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raise
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except MemoryError:
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logging.warning('Ran out of memory while preparing files')
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return prepared
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def async_compare(ref_id, other_ids, dbname, threshold):
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cache = Cache(dbname, threaded=False)
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limit = 100 - threshold
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ref_blocks = cache[ref_id]
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pairs = cache.get_multiple(other_ids)
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results = []
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for other_id, other_blocks in pairs:
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try:
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diff = avgdiff(ref_blocks, other_blocks, limit, MIN_ITERATIONS)
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percentage = 100 - diff
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except (DifferentBlockCountError, NoBlocksError):
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percentage = 0
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if percentage >= threshold:
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results.append((ref_id, other_id, percentage))
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cache.con.close()
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return results
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class AsyncMatchFactory(MatchFactory):
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def _do_getmatches(self, pictures, j):
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def empty_out_queue(queue, into):
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try:
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while True:
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into.append(queue.get(block=False))
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except Empty:
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pass
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j = j.start_subjob([1, 8, 1], 'Preparing for matching')
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cache = self.cached_blocks
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id2picture = {}
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dimensions2pictures = defaultdict(set)
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for picture in pictures[:]:
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try:
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picture.cache_id = cache.get_id(picture.unicode_path)
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id2picture[picture.cache_id] = picture
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except ValueError:
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pictures.remove(picture)
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if not self.match_scaled:
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dimensions2pictures[picture.dimensions].add(picture)
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pool = multiprocessing.Pool()
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async_results = []
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pictures_copy = set(pictures)
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for ref in j.iter_with_progress(pictures):
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others = pictures_copy if self.match_scaled else dimensions2pictures[ref.dimensions]
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others.remove(ref)
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if others:
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cache_ids = [f.cache_id for f in others]
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args = (ref.cache_id, cache_ids, self.cached_blocks.dbname, self.threshold)
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async_results.append(pool.apply_async(async_compare, args))
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matches = []
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for result in j.iter_with_progress(async_results, 'Matched %d/%d pictures'):
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matches.extend(result.get())
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result = []
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for ref_id, other_id, percentage in j.iter_with_progress(matches, 'Verified %d/%d matches', every=10):
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ref = id2picture[ref_id]
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other = id2picture[other_id]
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if percentage == 100 and ref.md5 != other.md5:
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percentage = 99
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if percentage >= self.threshold:
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result.append(get_match(ref, other, percentage))
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return result
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multiprocessing.freeze_support() |