770 lines
29 KiB
Python
Executable File
770 lines
29 KiB
Python
Executable File
#!/usr/bin/python
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from __future__ import print_function
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import sys
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import os
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import re
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import sqlite3
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import subprocess
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import hashlib
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from argparse import ArgumentParser
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SQLFILE='list_of_images.sqlite'
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DESCFILE='descriptions.csv'
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IMGMATCH=re.compile('.*\.jpg$|.*\.jpeg$|.*\.png$|.*\.gif$',re.I)
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BADDIRS=['_tn','_med']
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MINSIZE=0
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def setup_options():
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parser=ArgumentParser(description="Maintains the list of images sqlite file")
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parser.add_argument("-a",action="store_false",dest="add",default=True,
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help="Do not add new files [%(default)s]")
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parser.add_argument("-c",action="store_true",dest="changed",default=False,
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help="Modify changed files [%(default)s]")
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parser.add_argument("-d",action="store_true",dest="delete",default=False,
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help="Delete non-existing entries [%(default)s]")
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parser.add_argument("--du",type=str,action='store',dest="diskused",default=False,
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help="Print directory sizes. Argument is the path where directories are listed from.")
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parser.add_argument("--du-depth",type=str,action='store',dest="diskused_depth",default=1,
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help="Depth of summarization for --du.")
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parser.add_argument("-f",action="store",dest="sqlfile",default=SQLFILE,
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help="SQL file name to use [%(default)s]")
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parser.add_argument("-l",action="store_true",dest="symlinks",default=False,
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help="Follow symbolic links [%(default)s]")
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parser.add_argument("-m",type=int,dest="minsize",default=MINSIZE,
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help="Minimum pixel width/height of stored image [%(default)s]")
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parser.add_argument("-r",action="store_true",dest="random",default=False,
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help="Create randomized files for landscape and portrait images [%(default)s]")
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parser.add_argument("-s",type=str,dest="search",default=False,
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help="Search list based on path pattern")
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parser.add_argument("--measure",action="store_true",dest="measure",default=False,
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help="Measure various statistics for similarity/color searches. This option will flip the 'Add new files' option. [%(default)s]")
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parser.add_argument("--nearest",type=str,dest="nearestcolor",default=False,
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help="Search list for nearest ambient color. format: R,G,B in float 0-1. Add fourth value to limit search to number of hits. Also accepts format file,hits to find nearest color to given file.")
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parser.add_argument("--dup",action="store_true",dest="duplicate",default=False,
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help="Return a list of duplicate files, based on hashes. This option will flip the 'Add new files' option. [%(default)s]")
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parser.add_argument("--del",action="store_true",dest="deleteFiles",default=False,
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help="Delete files listed with --small. [%(default)s]")
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parser.add_argument("--small",action="store_true",dest="searchsmall",default=False,
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help="Return a list of small files, smaller than -m INT. This option will flip the 'Add new files' option. [%(default)s]")
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parser.add_argument("--similar",type=str,dest="similarity",default=None,
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help="Search list for similar images. Value 0-255 for similarity threshold. 0=high similarity. "+
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"If value is a filename, search similar to that image. "+
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"Append with ',value' to limit similarity. "+
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"The output columns: SD SimilarityDiff., CD ColorDiff., "+
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"RD AspectRatioDiff.,Shp SharpnessIndex.")
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parser.add_argument("--viewer",type=str,dest="viewer",default=None,
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help="Program to view images, %%f refers to filename(s)."+
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"If '1', defaults to: 'geeqie -l %%f'")
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parser.add_argument("-x",action="append",dest="exclude",default=[],
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help="Exclude folder name from the lists. This option may be issued several times.")
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parser.add_argument('startpath', action="store",default='.', nargs='?')
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options=parser.parse_args()
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BADDIRS.extend(options.exclude)
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if options.duplicate or options.searchsmall or options.measure or options.nearestcolor or options.similarity!=None or options.search or options.diskused:
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options.add=not options.add
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return options
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def createdb(sqlfile):
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conn=sqlite3.connect(sqlfile)
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db=conn.cursor()
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conn.text_factory=str
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db.execute('CREATE TABLE list (id INTEGER PRIMARY KEY AUTOINCREMENT,\
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file TEXT,date INTEGER,portrait NUMERIC, hash TEXT,\
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width INTEGER,height INTEGER,size INTEGER,\
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fingerprint TEXT,sharpness NUMERIC,\
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R REAL,G REAL, B REAL, BR REAL, BG REAL, BB REAL)')
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db.execute('CREATE TABLE descriptions (\
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file PRIMARY KEY TEXT,path TEXT, hash TEXT,\
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description TEXT)')
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conn.commit()
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return
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def delete_nonexisting(sqlfile):
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conn=sqlite3.connect(sqlfile)
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conn.text_factory=str
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#conn.row_factory=sqlite3.Row
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db=conn.cursor()
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dbdel=conn.cursor()
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db.execute('SELECT file FROM list')
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for row in db:
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if not os.path.exists(row[0]):
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print('removing.. '+row[0])
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dbdel.execute("DELETE FROM list where file == ?",(row[0],))
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conn.commit()
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return
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def delete_files(files):
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''' Actually deletes files! '''
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print_structure(files)
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doit=confirm(prompt="Sure to delete these files?")
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if doit:
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print("now delling")
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for hash in files:
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for f in hash[1]:
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print(f[0])
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os.remove(f[0])
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return
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def add_recurse(options):
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conn=sqlite3.connect(options.sqlfile)
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conn.text_factory=str
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db=conn.cursor()
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for path,dirs,files in os.walk(options.startpath,followlinks=options.symlinks):
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print('Checking '+path)
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dirs=clean_dirs(dirs)
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if not options.symlinks:
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files=clean_syms(files)
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files.sort()
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dirs.sort()
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db_files=get_folder_contents(db,os.path.realpath(path)+'/')
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for file in files:
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if IMGMATCH.match(file):
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filename=os.path.realpath(os.path.join(path,file))
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#if not is_listed(db,filename):
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if file not in db_files:
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if options.add:
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try:
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add_single(conn,filename,change=False,minsize=options.minsize)
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except:
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print('error adding file: '+filename)
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sys.exit(1)
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else:
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if options.changed:
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ftime=os.path.getmtime(filename)
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#hash=get_md5(filename)
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#if not hash_match(db,filename,hash):
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if not ftime_match(db,filename,ftime):
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#file content changed
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try:
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add_single(conn,filename,change=True,minsize=options.minsize)
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except:
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print('error changing file: '+filename)
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sys.exit(1)
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# if file mentioned, and hash same, no need to change entry
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conn.commit()
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return
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def add_single(conn,filename,change=False,hash=None,minsize=0):
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dims=get_dims(filename)
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if int(dims[0])<int(dims[1]):
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portrait=1
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else:
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portrait=0
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if (int(dims[0])<minsize) & (int(dims[1])<minsize):
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print(filename+" too small (%s)" % dims)
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return
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db=conn.cursor()
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if hash==None:
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hash=get_md5(filename)
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ftime=os.path.getmtime(filename)
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fsize=os.path.getsize(filename)
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if change:
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db.execute("UPDATE list SET date=?, portrait=?, hash=?, width=? ,height=?, \
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fingerprint=NULL, sharpness=NULL, R=NULL, G=NULL, B=NLL, BR=NULL, BG=NULL, BB=NULL, \
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size=? WHERE file=?",(ftime,portrait,hash,dims[0],dims[1],fsize,filename))
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print("changing: %(f)s (%(x)sx%(y)s)" % {'f':filename, 'x':dims[0], 'y':dims[1]})
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else:
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db.execute("INSERT INTO list(file,date,portrait,hash,width,height,size)\
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VALUES(?,?,?,?,?,?,?)",(filename,ftime,portrait,hash,dims[0],dims[1],fsize))
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print("adding: %(f)s (%(x)sx%(y)s)" % {'f':filename, 'x':dims[0], 'y':dims[1]})
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return
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def random_lists(sqlfile):
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conn=sqlite3.connect(sqlfile)
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conn.text_factory=str
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db=conn.cursor()
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db.execute('SELECT file FROM list WHERE portrait=0')
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lfile=open('landscape.list.s','w')
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for row in db:
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lfile.write(row[0]+'\n')
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db.execute('SELECT file FROM list WHERE portrait=1')
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pfile=open('portrait.list.s','w')
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for row in db:
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pfile.write(row[0]+'\n')
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lfile.close()
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pfile.close()
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sortargs=['sort','-R','-o','landscape.list','landscape.list.s']
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p=subprocess.call(sortargs)
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sortargs=['sort','-R','-o','portrait.list','portrait.list.s']
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p=subprocess.call(sortargs)
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os.unlink('portrait.list.s')
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os.unlink('landscape.list.s')
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return
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def is_listed(db,filename):
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db.execute("SELECT COUNT(*) FROM list where file == ?",(filename,))
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count=db.fetchall()
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return count[0][0]>0
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def get_folder_contents(db,path):
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''' return the contents of the folder '''
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files=[]
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db.execute("SELECT file FROM list where file LIKE ?",(path+'%',))
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for row in db:
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base=row[0].replace(path,'',1)
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if base.find('/')==-1:
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files.append(base)
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return files
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def ftime_match(db,filename,ftime):
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db.execute("SELECT date FROM list where file == ?",(filename,))
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count=db.fetchall()
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return count[0][0]==ftime
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def hash_match(db,filename,hash):
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db.execute("SELECT hash FROM list where file == ?",(filename,))
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count=db.fetchall()
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return count[0][0]==hash
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def get_md5(filename):
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''' Return hash of the first 5 megabytes of the file '''
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return hashlib.md5(open(filename,'rb').read(1024*1024*5)).hexdigest()
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def get_dims(filename):
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idargs=['identify','-format','%wx%h',filename+'[0]']
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p=subprocess.Popen(idargs,stdout=subprocess.PIPE)
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out, err = p.communicate()
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return (out.strip().split('x'))
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def call_viewer(opts, files):
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""" Runs the viewer program, contains defaults """
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if opts.viewer=="1":
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opts.viewer="geeqie -l %f"
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devnull = open('/dev/null', 'w')
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subprocess.call(opts.viewer.replace('%f', " ".join(files)), stderr=devnull, shell=True)
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def append_colors(sqlfile):
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conn=sqlite3.connect(sqlfile)
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conn.text_factory=str
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db=conn.cursor()
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dbh=conn.cursor()
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db.execute("SELECT file,R FROM list WHERE R IS NULL ORDER BY file")
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i=0
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dirname_old=""
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for row in db:
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colors=get_colors(row[0])
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dbh.execute("UPDATE list SET R=?, G=?, B=?, BR=?, BG=?, BB=? \
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WHERE file=?",(colors[0][0],colors[0][1],colors[0][2],
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colors[1][0],colors[1][1],colors[1][2],row[0]))
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filename=" "+os.path.basename(row[0])
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dirname=os.path.dirname(row[0])
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if dirname!=dirname_old:
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dirname_old=dirname
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filename=row[0]
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print("colors: %(f)s (%(r)s %(g)s %(b)s)" % {'f':filename, 'r':colors[0][0],
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'g':colors[0][1], 'b':colors[0][2]})
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i+=1
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if (i%50==0):
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conn.commit();
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conn.commit()
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return
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def find_color_nearest(opts):
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""" Find closest matching images to given RGB color """
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src=opts.nearestcolor
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conn=sqlite3.connect(opts.sqlfile)
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conn.text_factory=str
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db=conn.cursor()
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src=[float(i) for i in src.strip().strip('"').split(',')]
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if len(src)==3:
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src.append(1)
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db.execute("SELECT file, ABS(BR-?)+ABS(BG-?)+ABS(BB-?) as K,BR,BG,BB FROM list ORDER BY K LIMIT ?",
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(src[0],src[1],src[2],src[3]))
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hits=[]
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for hit in db:
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hits.append(hit)
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file_len=str(max([len(x[0]) for x in hits]))
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for c in range(len(hits)):
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print( ('{: <'+file_len+'} D {:.2f} (RGB {:.2f},{:.2f},{:.2f})').format(hits[c][0],
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hits[c][1],
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hits[c][2],
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hits[c][3],
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hits[c][4]))
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if opts.viewer:
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fnames=[x[0] for x in hits]
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call_viewer(opts, fnames)
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return
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def find_color_nearest_file(opts):
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""" Find closest matching images to given files with RGB color """
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cmp=opts.nearestcolor.rsplit(",",1)
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if len(cmp)==1:
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thr=1
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else:
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thr=int(cmp[1])
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cmp=cmp[0]
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conn=sqlite3.connect(opts.sqlfile)
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conn.text_factory=str
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db=conn.cursor()
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if is_listed(db, cmp):
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db1.execute("SELECT file,fingerprint,sharpness,width,height,BR,BG,BB FROM list WHERE file=?",(cmp,))
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for hit1 in db:
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fp=int(hit1[1])
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sp=hit1[2]
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dims=hit1[3:5]
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src=hit1[5:8]
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else:
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fp=int(get_fingerprint(cmp))
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sp=get_sharpness(cmp)
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dims=get_dims(cmp)
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src=get_colors(cmp)[1]
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src=[float(i) for i in src]
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db.execute("SELECT file, ABS(BR-?)+ABS(BG-?)+ABS(BB-?) as K,BR,BG,BB FROM list ORDER BY K LIMIT ?",
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(src[0],src[1],src[2],thr))
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hits=[]
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for hit in db:
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if hit[0]==cmp:
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continue
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hits.append(hit)
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file_len=str(max([len(x[0]) for x in hits]))
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for c in range(len(hits)):
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print( ('{: <'+file_len+'} D {:.2f} (RGB {:.2f},{:.2f},{:.2f})').format(hits[c][0],
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hits[c][1],
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hits[c][2],
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hits[c][3],
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hits[c][4]))
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if opts.viewer:
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fnames=[x[0] for x in hits]
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call_viewer(opts, fnames)
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return
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def get_colors(filename):
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small_args=['convert','-define','jpeg:size=64x64',filename+'[0]','-resize','10x10!','TEXT:-']
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p=subprocess.Popen(small_args,stdout=subprocess.PIPE)
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img, err = p.communicate()
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mean_args=['convert','-','-format','"%[fx:mean.r],%[fx:mean.g],%[fx:mean.b]"','info:-']
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p=subprocess.Popen(mean_args,stdout=subprocess.PIPE,stdin=subprocess.PIPE)
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mean, err = p.communicate(input=img)
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mean_args=['convert','-',
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'(','+clone','-gravity','North','-crop','10x1+0+0','-write','mpr:top','+delete',')',
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'(','+clone','-gravity','South','-crop','10x1+0+0','-write','mpr:bot','+delete',')',
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'(','+clone','-gravity','West','-crop','1x10+0+0','-rotate','90','-write','mpr:lef','+delete',')',
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'(','+clone','-gravity','East','-crop','1x10+0+0','-rotate','90','-write','mpr:rig','+delete',')',
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'+delete','mpr:top','mpr:bot','mpr:lef','mpr:rig','+append',
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'-format','"%[fx:mean.r],%[fx:mean.g],%[fx:mean.b]"','info:-']
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p=subprocess.Popen(mean_args,stdout=subprocess.PIPE,stdin=subprocess.PIPE)
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border, err = p.communicate(input=img)
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mean=[float(i) for i in mean.strip().strip('"').split(',')]
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border=[float(i) for i in border.strip().strip('"').split(',')]
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return (mean,border)
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def get_color_diff(c1,c2):
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""" Return color difference from two RGB triplets """
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return abs( c1[0] - c2[0] )+abs( c1[1] - c2[1] )+abs( c1[2] - c2[2] )
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def get_ratio_diff(d1,d2):
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""" Return ratio difference from two w,h dimension tuplets """
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return abs( float(d1[0])/float(d1[1]) - float(d2[0])/float(d2[1]) )
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def append_fingerprints(sqlfile):
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conn=sqlite3.connect(sqlfile)
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conn.text_factory=str
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db=conn.cursor()
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dbh=conn.cursor()
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db.execute("SELECT file FROM list WHERE fingerprint IS NULL ORDER BY file")
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i=0
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dirname_old=""
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for row in db:
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fp=get_fingerprint(row[0])
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dbh.execute("UPDATE list SET fingerprint=? \
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WHERE file=?",(fp,row[0]))
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filename=" "+os.path.basename(row[0])
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dirname=os.path.dirname(row[0])
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if dirname!=dirname_old:
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dirname_old=dirname
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filename=row[0]
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i+=1
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print("%(nr)i %(f)s" % {'f':filename, 'nr':i})
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if (i%50==0):
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conn.commit();
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conn.commit()
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def get_fingerprint(filename):
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small_args=['convert','-define','jpeg:size=256x256',filename+'[0]','-resize','160x160!',
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'-colorspace','Gray','-blur','2x2','-normalize','-equalize','-resize','16x16','-depth','1','TEXT:-']
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p=subprocess.Popen(small_args,stdout=subprocess.PIPE)
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img, err = p.communicate()
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values=''
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for row in img.split('\n'):
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gray=row.split(',')
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if len(gray)<3:
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continue
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if gray[2]=="255":
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values+='1'
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else:
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values+='0'
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return str(int(values,2))
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def find_fingerprint_similar(opts):
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''' Find all similar images, nearest match more similar than thr '''
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thr=int(opts.similarity)
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conn=sqlite3.connect(opts.sqlfile)
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conn.text_factory=str
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db1=conn.cursor()
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db2=conn.cursor()
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db1.execute("SELECT file,fingerprint,sharpness,width,height,R,G,B FROM list WHERE sharpness > 0 ORDER BY file")
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hits=[]
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hit_list=[]
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i=None
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for i,hit1 in enumerate(db1):
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if hit1[0] in hit_list:
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continue
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cmp=hit1[0]
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fp=int(hit1[1])
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sp=hit1[2]
|
|
dims=hit1[3:5]
|
|
pixels=dims[0]*dims[1]
|
|
colors=hit1[5:8]
|
|
db2.execute("SELECT file,fingerprint,sharpness,width,height,R,G,B FROM list WHERE sharpness > 0 ORDER BY file")
|
|
this1=[ [cmp, 0,sp,int(hit1[3]),int(hit1[4]),0,pixels,0] ]
|
|
for hit2 in db2:
|
|
if hit2[0]==cmp:
|
|
continue
|
|
similarity=bin(fp^int(hit2[1])).count('1')
|
|
if similarity<thr:
|
|
this2=[hit2[0], similarity, hit2[2],
|
|
int(hit2[3]),int(hit2[4]),
|
|
get_color_diff(hit2[5:8],colors),
|
|
int(hit2[3])*int(hit2[4]),
|
|
get_ratio_diff(hit2[3:5],dims)]
|
|
this1.append(this2)
|
|
hit_list.append(hit2[0])
|
|
this1.sort(key=lambda x: x[1])
|
|
if len(this1)>1:
|
|
hits.append(this1)
|
|
hit_list.append(cmp)
|
|
|
|
if i==None:
|
|
print("No measurements found")
|
|
sys.exit(1)
|
|
|
|
for src in hits:
|
|
file_len=str(max([len(x[0]) for x in src]))
|
|
print( ('{: <'+file_len+'} {: ^4} {: ^4} {: ^4} {: ^4} {: ^5}x{: ^5}').format("File","SD","CD","RD","Shp","W","H"))
|
|
for c in range(len(src)):
|
|
print( ('{: <'+file_len+'} {: >4} {: >4} {: >4} {: >4} {: >5}x{: >5}').format(src[c][0],src[c][1],
|
|
"%.2f"%src[c][5],"%.2f"%src[c][7],
|
|
"%.1f" % src[c][2],src[c][3],src[c][4]))
|
|
if opts.viewer:
|
|
fnames=[x[0] for x in src]
|
|
call_viewer(opts, fnames)
|
|
|
|
return
|
|
|
|
def find_fingerprint_nearest(opts):
|
|
''' Find nearest match to given file '''
|
|
|
|
cmp=os.path.realpath(opts.similarity.rsplit(",")[0])
|
|
thr=sys.maxint
|
|
if len(opts.similarity.rsplit(","))>1:
|
|
thr=int(opts.similarity.rsplit(",",1)[1])
|
|
conn=sqlite3.connect(opts.sqlfile)
|
|
conn.text_factory=str
|
|
db1=conn.cursor()
|
|
if is_listed(db1, cmp):
|
|
db1.execute("SELECT file,fingerprint,sharpness,width,height,R,G,B FROM list WHERE file=?",(cmp,))
|
|
for hit1 in db1:
|
|
fp=int(hit1[1])
|
|
sp=hit1[2]
|
|
dims=hit1[3:5]
|
|
colors=hit1[5:8]
|
|
else:
|
|
fp=int(get_fingerprint(cmp))
|
|
sp=get_sharpness(cmp)
|
|
dims=get_dims(cmp)
|
|
colors=get_colors(cmp)[0]
|
|
|
|
db1.execute("SELECT file,fingerprint,sharpness,width,height,R,G,B FROM list WHERE sharpness > 0 ORDER BY file")
|
|
this=['',thr,0,0,0,0,0]
|
|
hit1=None
|
|
for i,hit1 in enumerate(db1):
|
|
if hit1[0] == cmp:
|
|
continue
|
|
similarity=bin(fp^int(hit1[1])).count('1')
|
|
if similarity<this[1]:
|
|
this[1]=similarity
|
|
this[0]=hit1[0]
|
|
this[2]=hit1[2]
|
|
this[3]=int(hit1[3])
|
|
this[4]=int(hit1[4])
|
|
this[5]=get_color_diff(colors, hit1[5:8]) #abs( hit1[5] - colors[0] )+abs( hit1[6] - colors[1] )+abs( hit1[7] - colors[2] )
|
|
this[6]=get_ratio_diff(this[3:5], dims)# (this[3]/float(this[4])) / (float(dims[0])/float(dims[1]))
|
|
if hit1==None:
|
|
print("No measurements found")
|
|
sys.exit(1)
|
|
if this[1]==thr:
|
|
print("No similarities < "+str(thr)+": "+cmp, file=sys.stderr)
|
|
return
|
|
file_len=str(max(len(cmp), len(this[0])))
|
|
print( ('{: <'+file_len+'} {: ^4} {: ^4} {: ^4} {: ^4} {: ^5}x{: ^5}').format("File","SD","CD","RD","Shp","W","H"))
|
|
print( ('{: <'+file_len+'} {: >4} {: ^4} {: ^4} {: ^4} {: >5}x{: >5}').format(cmp,"","","","%.1f" % sp,dims[0],dims[1]))
|
|
print( ('{: <'+file_len+'} {: >4} {: >4} {: >4} {: >4} {: >5}x{: >5}').format(this[0], this[1],"%.2f"%this[5],
|
|
"%.2f"%this[6], "%.1f" % this[2],this[3], this[4]))
|
|
|
|
if opts.viewer:
|
|
call_viewer(opts, (cmp,this[0]))
|
|
|
|
|
|
|
|
def append_sharpness(sqlfile):
|
|
conn=sqlite3.connect(sqlfile)
|
|
conn.text_factory=str
|
|
db=conn.cursor()
|
|
dbh=conn.cursor()
|
|
db.execute("SELECT file FROM list WHERE sharpness IS NULL ORDER BY file")
|
|
i=0
|
|
dirname_old=""
|
|
for row in db:
|
|
sp=get_sharpness(row[0])
|
|
dbh.execute("UPDATE list SET sharpness=? \
|
|
WHERE file=?",(sp,row[0]))
|
|
filename=" "+os.path.basename(row[0])
|
|
dirname=os.path.dirname(row[0])
|
|
if dirname!=dirname_old:
|
|
dirname_old=dirname
|
|
filename=row[0]
|
|
i+=1
|
|
print("%(nr)i %(f)s %(s)f" % {'f':filename, 'nr':i,'s':sp})
|
|
if (i%50==0):
|
|
conn.commit();
|
|
conn.commit()
|
|
|
|
def get_sharpness(filename):
|
|
""" Difference in X, Difference in Y, get smaller diff = smaller sharpness.
|
|
May change if bugs found.. """
|
|
|
|
# Resize to 1024 smaller axis, crop with golden ratio
|
|
# grayscale and equalize histogram. calculate difference between x neighbor
|
|
# and y neigbor. smaller difference = less sharp.
|
|
small_args="convert ( -define jpeg:size=2048x2048 -resize 1024^ -gravity center -crop 62%x62%+0+0 -colorspace gray XXX -equalize ) \
|
|
( -clone 0 ( -clone 0 -roll +1+0 ) -compose Difference -composite -shave 1x1 ) \
|
|
( -clone 0 ( -clone 0 -roll +0+1 ) -compose Difference -composite -shave 1x1 ) \
|
|
-delete 0 -compose Darken -composite -format %[fx:mean*1000] info:".split(" ")
|
|
small_args[12]=filename+'[0]'
|
|
p=subprocess.Popen(small_args,stdout=subprocess.PIPE)
|
|
sharpness, err = p.communicate()
|
|
return float(sharpness.strip())
|
|
|
|
def searchdb(sqlfile,needle):
|
|
conn=sqlite3.connect(sqlfile)
|
|
conn.text_factory=str
|
|
db=conn.cursor()
|
|
dbh=conn.cursor()
|
|
db.execute("SELECT file,width,height,date FROM list WHERE file LIKE ? ORDER BY file",('%'+needle+'%',))
|
|
results=[]
|
|
flist=[]
|
|
for row in db:
|
|
results.append(row)
|
|
flist.append(('search',results))
|
|
return flist
|
|
|
|
def clean_dirs(dirs):
|
|
for s in dirs[:]:
|
|
if (s in BADDIRS) or (s.startswith(".")):
|
|
dirs.remove(s)
|
|
return dirs
|
|
|
|
def clean_syms(files):
|
|
for f in files[:]:
|
|
if os.path.islink(f):
|
|
files.remove(f)
|
|
return files
|
|
|
|
def confirm(prompt=None, resp=False):
|
|
"""prompts for yes or no response from the user. Returns True for yes and
|
|
False for no.
|
|
'resp' should be set to the default value assumed by the caller when
|
|
user simply types ENTER.
|
|
"""
|
|
|
|
if prompt is None:
|
|
prompt = 'Confirm'
|
|
if resp:
|
|
prompt = '%s [%s]|%s: ' % (prompt, 'y', 'n')
|
|
else:
|
|
prompt = '%s [%s]|%s: ' % (prompt, 'n', 'y')
|
|
|
|
while True:
|
|
ans = raw_input(prompt)
|
|
if not ans:
|
|
return resp
|
|
if ans not in ['y', 'Y', 'n', 'N']:
|
|
print('please enter y or n.')
|
|
continue
|
|
if ans == 'y' or ans == 'Y':
|
|
return True
|
|
if ans == 'n' or ans == 'N':
|
|
return False
|
|
|
|
def find_duplicates(sqlfile,search):
|
|
if (search=='.'):
|
|
search='%'
|
|
else:
|
|
search='%'+search+'%'
|
|
conn=sqlite3.connect(sqlfile)
|
|
conn.text_factory=str
|
|
db=conn.cursor()
|
|
dbh=conn.cursor()
|
|
db.execute("SELECT hash,count(*) FROM list WHERE file LIKE ? group by hash HAVING count(*) > 1 ",(search,))
|
|
duphash=[]
|
|
for row in db:
|
|
hash=row[0]
|
|
dbh.execute("SELECT file,width,height,date FROM list WHERE hash = ?",(hash,))
|
|
flist=[]
|
|
for row in dbh:
|
|
flist.append(row)
|
|
flist.sort(key=lambda file: file[3])
|
|
duphash.append((hash, flist))
|
|
duphash.sort(key=lambda file: file[1][0])
|
|
return duphash
|
|
|
|
def find_smalls(minsize,sqlfile):
|
|
conn=sqlite3.connect(sqlfile)
|
|
conn.text_factory=str
|
|
db=conn.cursor()
|
|
db.execute("SELECT file,width,height FROM list WHERE width < ? OR height < ?",(minsize,minsize))
|
|
smalls=[]
|
|
flist=[]
|
|
for row in db:
|
|
smalls.append(row)
|
|
flist.append(('smalls',smalls))
|
|
return flist
|
|
|
|
def disk_used(options):
|
|
conn=sqlite3.connect(options.sqlfile)
|
|
conn.text_factory=str
|
|
db=conn.cursor()
|
|
db.execute('SELECT size,replace(file,?,"") as path FROM list WHERE file LIKE ?',
|
|
(os.path.realpath(options.diskused)+"/",
|
|
os.path.realpath(options.diskused)+"%",
|
|
))
|
|
entries=[]
|
|
sizes=[]
|
|
for row in db:
|
|
start_path=row[1].split('/')
|
|
start_path="/".join(start_path[0:int(options.diskused_depth)])
|
|
if start_path not in entries:
|
|
entries.append(start_path)
|
|
sizes.append(row[0])
|
|
else:
|
|
sizes[ entries.index(start_path) ]+=row[0]
|
|
for entry in zip(sizes,entries):
|
|
print("| ".join([ str(entry[0]).ljust(14),
|
|
humanize_size(entry[0]).rjust(8),
|
|
entry[1]]))
|
|
|
|
def print_structure(files):
|
|
for hash in files:
|
|
#print(hash[0])
|
|
i=1
|
|
for f in hash[1]:
|
|
print("%(i)d: (%(x)dx%(y)d):%(f)s " % {'i':i, 'f':f[0], 'x':f[1], 'y':f[2]})
|
|
i+=1
|
|
return
|
|
|
|
def print_dup_structure(files,opts):
|
|
i=1
|
|
for hash in files:
|
|
#print(hash[0])
|
|
fnames=[]
|
|
for f in hash[1]:
|
|
fnames.append(' "'+f[0]+'"')
|
|
print("%(i)d:%(n)d:%(f)s " % {'i':i, 'n':len(fnames), 'f':",".join(fnames)})
|
|
if opts.viewer:
|
|
fnames=[x[0] for x in hash[1]]
|
|
subprocess.call(opts.viewer.replace('%f', " ".join(fnames)), shell=True)
|
|
i+=1
|
|
return
|
|
|
|
def humanize_size(size,precision=1):
|
|
if size==None:
|
|
return 'nan'
|
|
suffixes=['B','KB','MB','GB','TB']
|
|
suffixIndex = 0
|
|
defPrecision=0
|
|
while size > 1024:
|
|
suffixIndex += 1
|
|
size = size/1024.0
|
|
defPrecision=precision
|
|
return "%.*f%s"%(defPrecision,size,suffixes[suffixIndex])
|
|
|
|
def import_descriptions(options):
|
|
""" Walk through the path from given [startpath] and read
|
|
any DESCFILE, importing the contents in the DB """
|
|
pass
|
|
|
|
def export_descriptions(options):
|
|
""" Get unique paths from DB, matching [startpath], write
|
|
DESCFILE for each file found. Export gets a format argument:
|
|
%wx%h %n %d """
|
|
# width, height, basename, description
|
|
#%R%G%B %S %F %D
|
|
# Red Green Blue Sharpness Fingerprint Date(formatting?)
|
|
# %s %H
|
|
# filesize Hash
|
|
pass
|
|
|
|
|
|
def main():
|
|
options=setup_options();
|
|
if not os.path.exists(options.sqlfile):
|
|
createdb(options.sqlfile);
|
|
if options.delete:
|
|
print('Deleting entries...')
|
|
delete_nonexisting(options.sqlfile)
|
|
if options.add or options.changed:
|
|
print('Adding entries...')
|
|
add_recurse(options)
|
|
if options.search:
|
|
print_structure(searchdb(options.sqlfile,options.search))
|
|
if options.measure:
|
|
print('Measure colors...')
|
|
append_colors(options.sqlfile)
|
|
print('Measure fingerprints...')
|
|
append_fingerprints(options.sqlfile)
|
|
print('Measure sharpness...')
|
|
append_sharpness(options.sqlfile)
|
|
if options.random:
|
|
print('Random lists...')
|
|
random_lists(options.sqlfile)
|
|
if options.nearestcolor:
|
|
if os.path.exists(options.nearestcolor.rsplit(",")[0]):
|
|
find_color_nearest_file(options)
|
|
else:
|
|
find_color_nearest(options)
|
|
|
|
if options.similarity!=None:
|
|
if os.path.exists(options.similarity.rsplit(",")[0]):
|
|
find_fingerprint_nearest(options)
|
|
else:
|
|
find_fingerprint_similar(options)
|
|
if options.duplicate:
|
|
files=find_duplicates(options.sqlfile,options.startpath)
|
|
print_dup_structure(files,options)
|
|
if options.searchsmall:
|
|
files=find_smalls(options.minsize,options.sqlfile)
|
|
if options.deleteFiles:
|
|
if len(files[0][1])>0:
|
|
delete_files(files)
|
|
delete_nonexisting(options.sqlfile)
|
|
else:
|
|
print_structure(files)
|
|
if options.diskused:
|
|
disk_used(options)
|
|
#print(files)
|
|
|
|
sys.exit(0)
|
|
|
|
if __name__ == "__main__":
|
|
main()
|
|
|