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https://github.com/flynx/ImageGrid.git
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417 lines
9.5 KiB
Python
Executable File
417 lines
9.5 KiB
Python
Executable File
#=======================================================================
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__version__ = '''0.0.01'''
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__sub_version__ = '''20130326030151'''
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__copyright__ = '''(c) Alex A. Naanou 2011'''
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#-----------------------------------------------------------------------
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# The first index.py might be a little too complicated. try and resolve
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# this as so:
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# - list all relevant files (RAW, XMP, JPG, PSD, ...)
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# - group by path (closeness)
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# - deepest common path to contain all files with common name.
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# this will fail if we have different files with same names.
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#
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#-----------------------------------------------------------------------
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import os
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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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import couchdb
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from pli.logictypes import ANY, OR
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import store
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from gid import image_gid
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#-----------------------------------------------------------------------
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##CONFIG_NAME = 'hdd9_config.json'
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CONFIG_NAME = 'P7000_config.json'
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##CONFIG_NAME = 'staging_config.json'
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config = json.load(open(CONFIG_NAME))
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# XXX move this to a context-dependant module...
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RAW = OR(
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# Nikon
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'NEF', 'nef',
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# Panasonic/Leica
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'RW2', 'rw2',
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# Canon
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'CRW', 'crw',
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'CR2', 'cr2',
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# Sigma
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'X3F', 'x3f',
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# Adobe/Leica
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'DNG', 'dng',
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)
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JPEG = OR(
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'JPG', 'jpg',
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'JPEG', 'jpeg',
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)
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PSD = OR(
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'PSD', 'psd'
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)
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TIFF = OR(
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'TIFF', 'tiff',
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'TIF', 'tif'
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)
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XMP = OR(
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'XMP', 'xmp'
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)
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ITEM = OR(RAW, JPEG, PSD, TIFF, XMP)
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TYPES = {
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'raw': RAW,
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'jpeg': JPEG,
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'psd': PSD,
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'tiff': TIFF,
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'xmp': XMP,
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}
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SKIP_DIRS = '.sys2'
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SKIP_MARKER = '.skipindexing'
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SUBTREE_CLASSES = {
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'preview': 'preview',
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'preview (RAW)': 'RAW preview',
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}
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#-----------------------------------------------------------------------
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#----------------------------------------------------------list_files---
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##!!! we will need to normalize the paths to one single scheme (either relative or absolute)...
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# XXX might need to fetch file data too...
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def list_files(root, sub_trees=SUBTREE_CLASSES, type=ITEM,
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include_root_path=False, include_ctime=True,
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skip_marker=SKIP_MARKER, skip_dirs=SKIP_DIRS):
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'''
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yields:
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(<path>, <name>, <ext>[, <ctime>]),
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'''
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for orig_path, dirs, files in os.walk(root):
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# skip dir trees containing skip_filename...
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if skip_marker in files:
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del dirs[:]
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continue
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# skip dirs...
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while skip_dirs in dirs:
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dirs.remove(skip_dirs)
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# XXX is this correct...
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path = orig_path.split(os.path.sep)
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# remove root from path...
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if not include_root_path:
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path = path[len(root.split(os.path.sep)):]
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# process files...
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for f in files:
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name, ext = os.path.splitext(f)
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# we need the extension wothout the dot...
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ext = ext[1:]
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# filter by ext...
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if ext == type:
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if include_ctime:
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t = os.path.getctime(os.path.join(orig_path, f))
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yield path, name, ext, t
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else:
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yield path, name, ext
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#----------------------------------------------------------common_len---
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def common_len(a, *b):
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'''
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calculate the common path length.
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'''
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for i, l in enumerate(izip(*(a,) + b)):
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if len(set(l)) != 1:
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return i
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return len(min(*(a,) + b))
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#-------------------------------------------------------path_distance---
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##!!! is this meaningless?
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def path_distance(a, b):
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'''
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'''
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return len(a) + len(b) - common_len(a, b)*2
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#-------------------------------------------------------index_by_name---
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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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#-------------------------------------------------------split_by_raws---
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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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# top level common path...
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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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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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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
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#-----------------------------------------------------------gid_index---
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##!!! this will rewrite existing data -- should only update...
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def gid_index(index, existing=None):
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'''
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'''
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skipped = []
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# index via a propper GID...
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# split similarly named but different files...
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if existing is None:
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res = {}
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else:
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res = existing
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failed = []
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im_n = 0
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up_n = 0
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new_n = 0
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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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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 (' '*78), '\rno 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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im_n += 1
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print 'Processing image:', im_n, 'new:', new_n, 'updated:', up_n, '\r',
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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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##!!! normalize the image format...
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img = {
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'gid': GID,
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'name': name,
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'imported': time.time(),
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'updated': 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': [e for e in l if e[2] == RAW],
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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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# add new data...
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if GID not in res:
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res[GID] = img
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new_n += 1
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# update existing...
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else:
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cur = res[GID]
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updating = False
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for k, v in img.iteritems():
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# skip
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if k in ('imported', 'name', 'gid', 'ctime', 'updated'):
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continue
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if v != cur[k]:
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cur[k] = v
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updating = True
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# do the actual update...
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if updating:
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cur['updated'] = time.time()
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res[GID] = cur
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up_n += 1
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else:
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skipped += [GID]
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return res, failed, skipped
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#-----------------------------------------------------------------------
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if __name__ == '__main__':
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INDEX_PATH = config.get('INDEX_ROOT', os.path.join('test', 'index2'))
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FILE_LIST = os.path.join('test', 'flatfilelist-P7000-new.json')
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## FILE_LIST = os.path.join('test', 'flatfilelist-120kfiles.json')
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## FILE_LIST = os.path.join('test', 'flatfilelist.json')
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BUILD_FILE_LIST = False if os.path.exists(FILE_LIST) else True
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if BUILD_FILE_LIST:
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lst = list(list_files(config['ARCHIVE_ROOT']))
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print 'found files:', len(lst)
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## pprint(lst[0])
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json.dump(lst, file(FILE_LIST, 'w'))
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print 'saved...'
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lst = json.load(file(FILE_LIST))
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print 'loaded:', len(lst)
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IMPORT_DIFF = False
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# skip already read files...
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if IMPORT_DIFF and not BUILD_FILE_LIST:
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lst_cur = list(list_files(config['ARCHIVE_ROOT']))
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print 'found files:', len(lst_cur)
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lst_cur = [ e for e in lst_cur if e not in lst ]
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print 'found new or updated files:', len(lst_cur)
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lst = lst_cur
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raise SystemExit
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index = index_by_name(lst)
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## GID_index = store.IndexWithCache(INDEX_PATH)
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GID_index = store.Index(INDEX_PATH)
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# a cheating waw to say if we are empty...
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index_empty = True
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for k in GID_index.iterkeys():
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index_empty = False
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break
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t0 = time.time()
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if not index_empty:
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print 'updating...'
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##!!! this takes a substantially longer time initially... (about 30x longer)
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GID_index, failed, skipped = gid_index(index, GID_index)
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else:
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print 'indexing...'
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GID_index, failed, skipped = gid_index(index)
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store.dump(GID_index, INDEX_PATH, index_depth=2)
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t1 = time.time()
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print 'done in:', t1-t0, 'seconds.'
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json.dump(failed, file(os.path.join('test', 'failed-to-categorise.json'), 'w'))
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##!!! TODO: archive descriptions to help index/tag items...
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# NOTE: each import from an existing archive will be as follows:
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# - full listing
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# - find new subtrees
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# - find modified items (file date diff)
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# NOTE: raws number here may be more than indexed because some raws
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# may get grouped by GID
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print '''results:
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indexed: %s
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raws: %s
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failed: %s
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skipped: %s
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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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len(skipped))
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## ##!!! this is really slow because it pulls ALL the data... wonder who wrote this? :)
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## pprint(GID_index.itervalues().next())
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## store.dump(GID_index, INDEX_PATH)
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## store.pack(INDEX_PATH)
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#=======================================================================
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# vim:set ts=4 sw=4 nowrap :
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