nearest color search for files

image_list.py

@@ -33,7 +33,7 @@ def setup_options():
     parser.add_argument("--measure",action="store_true",dest="measure",default=False,
                      help="Measure various statistics for similarity/color searches. This option will flip the 'Add new files' option. [%(default)s]")
     parser.add_argument("--nearest",type=str,dest="nearestcolor",default=False,
-                     help="Search list for nearest mean color. format: R,G,B in float 0-1. Add fourth value to limit search to number")
+                     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.")
     parser.add_argument("--dup",action="store_true",dest="duplicate",default=False,
                      help="Return a list of duplicate files, based on hashes. This option will flip the 'Add new files' option. [%(default)s]")
     parser.add_argument("--del",action="store_true",dest="deleteFiles",default=False,
@@ -274,9 +274,54 @@ def find_color_nearest(opts):
                                                                          hits[c][4]))
     if opts.viewer:
         fnames=[x[0] for x in hits]
-        subprocess.call(opts.viewer.replace('%f', " ".join(fnames)), shell=True)
+        call_viewer(opts, fnames)
     return
 
+def find_color_nearest_file(opts):
+    """ Find closest matching images to given files with RGB color """
+    cmp=opts.nearestcolor.rsplit(",",1)
+    if len(cmp)==1:
+        thr=1
+    else:
+        thr=int(cmp[1])
+    cmp=cmp[0]
+    conn=sqlite3.connect(opts.sqlfile)
+    conn.text_factory=str
+    db=conn.cursor()
+    if is_listed(db, cmp):
+        db1.execute("SELECT file,fingerprint,sharpness,width,height,BR,BG,BB FROM list WHERE file=?",(cmp,))
+        for hit1 in db:
+            fp=int(hit1[1])
+            sp=hit1[2]
+            dims=hit1[3:5]
+            src=hit1[5:8]
+    else:
+        fp=int(get_fingerprint(cmp))
+        sp=get_sharpness(cmp)
+        dims=get_dims(cmp)
+        src=get_colors(cmp)[1]
+    src=[float(i) for i in src]
+    db.execute("SELECT file, ABS(BR-?)+ABS(BG-?)+ABS(BB-?) as K,BR,BG,BB FROM list ORDER BY K LIMIT ?",
+                        (src[0],src[1],src[2],thr))
+    hits=[]
+    for hit in db:
+        if hit[0]==cmp:
+            continue
+        hits.append(hit)
+                    
+    file_len=str(max([len(x[0]) for x in hits]))
+    for c in range(len(hits)):
+        print( ('{: <'+file_len+'} D {:.2f} (RGB {:.2f},{:.2f},{:.2f})').format(hits[c][0],
+                                                                         hits[c][1],
+                                                                         hits[c][2],
+                                                                         hits[c][3],
+                                                                         hits[c][4]))
+    if opts.viewer:
+        fnames=[x[0] for x in hits]
+        call_viewer(opts, fnames)
+    return
+
+
 def get_colors(filename):
     small_args=['convert','-define','jpeg:size=64x64',filename+'[0]','-resize','10x10!','TEXT:-']
     p=subprocess.Popen(small_args,stdout=subprocess.PIPE)
@@ -627,7 +672,11 @@ def main():
         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)