mirror of
https://github.com/flynx/ImageGrid.git
synced 2025-10-29 10:20:08 +00:00
reorganized index2.py and split off gid.py...
Signed-off-by: Alex A. Naanou <alex.nanou@gmail.com>
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gid.py
Executable file
65
gid.py
Executable file
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#=======================================================================
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__version__ = '''0.0.01'''
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__sub_version__ = '''20120310183438'''
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__copyright__ = '''(c) Alex A. Naanou 2011'''
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#-----------------------------------------------------------------------
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import os
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import pyexiv2 as metadata
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#-----------------------------------------------------------------------
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# XXX need a strategy to check if two files that have the same GID are
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# identical, and if so, need to destinguish them in the GID...
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# might be a good idea to add a file hash
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# XXX not yet sure if this is unique enough to avoid conflicts if one
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# photographer has enough cameras...
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# XXX also might be wise to add a photographer ID into here...
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def image_gid(path, format='%(artist)s-%(date)s-%(name)s', date_format='%Y%m%d-%H%M%S'):
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'''
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Calgulate image GID.
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Main gid criteria:
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- unique
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- calculable from the item (preferably any sub-item)
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- human-readable
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Default format:
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<artist>-<datetime>-<filename>
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Example:
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Alex_A.Naanou-20110627-195706-DSC_1234
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Supported fields:
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%(artist)s - Exif.Image.Artist field, stripped and spaces replaced with underscores.
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%(date)s - Exif.Image.DateTime formated to date_format argument.
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%(name)s - file name.
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NOTE: date and time are the date and time the image was made ('Exif.Image.DateTime')
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NOTE: need EXIF data to generate a GID
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'''
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# get the filename...
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data = {
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'name': os.path.splitext(os.path.split(path)[-1])[0],
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}
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# check if we need a date in the id...
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if '%(date)s' in format:
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i = metadata.ImageMetadata('%s' % path)
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i.read()
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d = i['Exif.Image.DateTime'].value
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data['date'] = d.strftime(date_format)
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# check if we need an artist...
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if '%(artist)s' in format:
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data['artist'] = i['Exif.Image.Artist'].value.strip().replace(' ', '_')
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return format % data
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#=======================================================================
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# vim:set ts=4 sw=4 nowrap :
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272
index2.py
272
index2.py
@ -1,7 +1,7 @@
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#=======================================================================
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__version__ = '''0.0.01'''
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__sub_version__ = '''20120309173155'''
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__sub_version__ = '''20120310191654'''
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__copyright__ = '''(c) Alex A. Naanou 2011'''
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@ -20,14 +20,14 @@ import json
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import zipfile
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import uuid
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import time
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from pprint import pprint
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from itertools import izip, izip_longest
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import pyexiv2 as metadata
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from itertools import izip, izip_longest
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from pli.logictypes import ANY, OR
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from pprint import pprint
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from gid import image_gid
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#-----------------------------------------------------------------------
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@ -82,50 +82,6 @@ SUBTREE_CLASSES = {
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#-----------------------------------------------------------------------
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# XXX need a strategy to check if two files that have the same GID are
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# identical, and if so, need to destinguish them in the GID...
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# might be a good idea to add a file hash
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# XXX not yet sure if this is unique enough to avoid conflicts if one
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# photographer has enough cameras...
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# XXX also might be wise to add a photographer ID into here...
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def image_gid(path, format='%(artist)s-%(date)s-%(name)s', date_format='%Y%m%d-%H%M%S'):
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'''
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Calgulate image GID.
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Main gid criteria:
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- unique
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- calculable from the item (preferably any sub-item)
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- human-readable
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Default format:
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<artist>-<datetime>-<filename>
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Example:
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Alex_A.Naanou-20110627-195706-DSC_1234
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Supported fields:
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%(artist)s - Exif.Image.Artist field, stripped and spaces replaced with underscores.
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%(date)s - Exif.Image.DateTime formated to date_format argument.
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%(name)s - file name.
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NOTE: date and time are the date and time the image was made ('Exif.Image.DateTime')
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NOTE: need EXIF data to generate a GID
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'''
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# get the filename...
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data = {
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'name': os.path.splitext(os.path.split(path)[-1])[0],
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}
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# check if we need a date in the id...
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if '%(date)s' in format:
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i = metadata.ImageMetadata('%s' % path)
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i.read()
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d = i['Exif.Image.DateTime'].value
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data['date'] = d.strftime(date_format)
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# check if we need an artist...
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if '%(artist)s' in format:
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data['artist'] = i['Exif.Image.Artist'].value.strip().replace(' ', '_')
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return format % data
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##!!! we will need to normalize the paths to one single scheme (either relative or absolute)...
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@ -171,7 +127,123 @@ def path_distance(a, b):
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return len(a) + len(b) - common_len(a, b)*2
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def index_by_name(lst):
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'''
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index by file name (indexing preparation)...
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format:
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{
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<name> : [
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(<path>, <name>, ...),
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...
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],
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...
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}
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'''
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res = {}
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# NOTE: this is to avoid side-effects...
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lst = lst[:]
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# sort via name, ext, path
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lst.sort(key=lambda e: (e[1], e[2], e[0]))
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for e in lst:
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n = e[1]
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if n in res:
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res[n] += [e]
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else:
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res[n] = [e]
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return res
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def split_by_raws(raws, lst, failed):
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'''
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'''
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## raws = [e for e in lst if e[2] == RAW]
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common = common_len(*[ e[0] for e in raws ])
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# NOTE: do not change the order of raws after this point
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# and till the end of the loop...
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# XXX revise if there is a simpler way...
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##!!! this kills code like sets[0][1] += [...]
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## sets = [ (r, [r]) for r in raws ]
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sets = [ [r, [r]] for r in raws ]
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for e in lst:
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if e[2] == RAW:
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continue
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# check if we are closer to other raws...
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# NOTE: this depends on stability of order in raws
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c_index = [(common_len(r[0], e[0]), r, i) for i, r in enumerate(raws)]
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c, raw, i = max(*c_index)
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# we have two locations with identical weight...
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if c_index.count([c, ANY, ANY]) > 1:
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# a file is at a path junction exactly...
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print ' !!! can\'t decide where to put %s.%s...' % (e[1], e[2])
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##!!! try different strategies here...
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##!!!
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failed += [e]
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# found a location...
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elif c > common:
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##!!! for some odd reason this does not work....
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sets[i][1] += [e]
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# file in an odd location ##!!! list these locations...
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else:
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print ' !!! can\'t decide where to put %s.%s...' % (e[1], e[2])
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##!!! try different strategies here...
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##!!!
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failed += [e]
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## return sets, failed
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return sets
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def gid_index(index):
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'''
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'''
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# index via a propper GID...
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# split similarly named but different files...
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res = {}
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failed = []
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for name, l in index.iteritems():
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l.sort()
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raws = [e for e in l if e[2] == RAW]
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# multiple raw files...
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if len(raws) > 1:
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# spit this into a seporate func...
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sets = split_by_raws(raws, l, failed)
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# single raw...
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elif len(raws) == 1:
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sets = [(raws[0], l)]
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# no raw files...
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else:
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print 'no raw file found for "%s"...' % os.path.join(name)
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sets = []
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##!!! need to report this in a usable way...
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failed += l
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# add actual elements to index...
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for raw, l in sets:
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# get file GID...
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GID = image_gid('%s.%s' % (os.path.join(*[config['ARCHIVE_ROOT']] + raw[0] + [raw[1]]), raw[2]))
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res[GID] = {
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'gid': GID,
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'name': name,
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'imported': time.time(),
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# NOTE: this might get distorted on archiving or
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# copying...
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# mostly intended for importing...
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'ctime': raw[3],
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##!!! make these more general...
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'RAW': raws,
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'XMP': [e for e in l if e[2] == XMP],
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'JPG': [e for e in l if e[2] == JPEG],
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'PSD': [e for e in l if e[2] == PSD],
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'TIFF': [e for e in l if e[2] == TIFF],
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'other': [e for e in l if e[2] != OR(TIFF, PSD, JPEG, XMP, RAW)],
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}
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return res, failed
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#-----------------------------------------------------------------------
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@ -192,102 +264,12 @@ if __name__ == '__main__':
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lst = json.load(file(FILE_LIST))
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print len(lst)
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# sort via name, ext, path
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lst.sort(key=lambda e: (e[1], e[2], e[0]))
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# index by name (indexing preparation)...
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# {
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# <name> : [
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# (<path>, <name>, <type>),
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# ...
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# ],
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# ...
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# }
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index = {}
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for p, n, t, c in lst:
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if n in index:
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index[n] += [(p, n, t, c)]
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else:
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index[n] = [(p, n, t, c)]
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# index via a propper GID...
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# split similarly named but different files...
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GID_index = {}
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failed = []
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for name, l in index.items():
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l.sort()
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raws = [e for e in l if e[2] == RAW]
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# handle multiple raw files...
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if len(raws) > 1:
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common = common_len(*[ e[0] for e in raws ])
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# NOTE: do not change the order of raws after this point
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# and till the end of the loop...
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# XXX revise if there is a simpler way...
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##!!! this kills code like sets[0][1] += [...]
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## sets = [ (r, [r]) for r in raws ]
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sets = [ [r, [r]] for r in raws ]
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for e in l:
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if e[2] == RAW:
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continue
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# check if we are closer to other raws...
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# NOTE: this depends on stability of order in raws
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c_index = [(common_len(r[0], e[0]), r, i) for i, r in enumerate(raws)]
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c, raw, i = max(*c_index)
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# we have two locations with identical weight...
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if c_index.count([c, ANY, ANY]) > 1:
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# a file is at a path junction exactly...
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print ' !!! can\'t decide where to put %s.%s...' % (e[1], e[2])
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##!!! try different strategies here...
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##!!!
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failed += [e]
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# found a location...
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elif c > common:
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# XXX hack (se below)
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## s = sets[i][1]
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## s += [e]
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##!!! for some odd reason this does not work....
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sets[i][1] += [e]
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# file in an odd location ##!!! list these locations...
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else:
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print ' !!! can\'t decide where to put %s.%s...' % (e[1], e[2])
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##!!! try different strategies here...
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##!!!
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failed += [e]
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# single raw...
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elif len(raws) == 1:
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sets = [(raws[0], l)]
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# no raw files...
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else:
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print 'no raw file found for "%s"...' % os.path.join(name)
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sets = []
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##!!! need to report this in a usable way...
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failed += l
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index = index_by_name(lst)
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for raw, l in sets:
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# get file GID...
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GID = image_gid('%s.%s' % (os.path.join(*[config['ARCHIVE_ROOT']] + raw[0] + [raw[1]]), raw[2]))
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GID_index, failed = gid_index(index)
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GID_index[GID] = {
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'gid': GID,
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'name': name,
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'imported': time.time(),
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# NOTE: this might get distorted on archiving or
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# copying...
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# mostly intended for importing...
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'ctime': raw[3],
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'RAW': raws,
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'XMP': [e for e in l if e[2] == XMP],
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'JPG': [e for e in l if e[2] == JPEG],
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'PSD': [e for e in l if e[2] == PSD],
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'TIFF': [e for e in l if e[2] == TIFF],
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'other': [e for e in l if e[2] != OR(TIFF, PSD, JPEG, XMP, RAW)],
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}
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##!!! TODO: archive descriptions to help index/tag items...
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@ -303,16 +285,14 @@ if __name__ == '__main__':
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indexed: %s
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raws: %s
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failed: %s
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''' % (len(GID_index), len([ e for e in lst if e[2] == RAW]), len(failed))
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''' % (
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len(GID_index),
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len([ e for e in lst if e[2] == RAW]),
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len(failed))
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pprint(GID_index.values()[0])
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#=======================================================================
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