Yesterday I posted about how to put multiple tags in tons of pictures, with digiKam. Apparently, the method I described there does not work (blame it on digiKam, of course). Still, the post makes for an interesting reading (hey, I am the author. What would I say?).
Here I'll describe a new way to acomplish what the previous method couldn't. If you want to know what on Earth I'm talking about, read the The problem section of the previous post.
Fairy tale-like solution
I found out how to implement a solution much like the one in the Fairy tale solution section of my previous post. Question: what is the next best thing to a single keystroke to tag a file? Answer: a single mouse click.
Following our ideal method, we will do a visual scan of all photos, one by one, succesively tagging (or ignoring) each file in which a certain person appears (or doesn't). The tagging will be done by a single mouse click (right hand always on mouse), and the photos will advance with space bar strokes (left thumb always on space bar).
To do so, one must go to the first picture in the set, and maximize it. Next, open the right panel, and go to the Captions/Tags tab. Find the tag of the person you are dealing with in the tag tree, and place the mouse over it. See the following screenshot (click on it to maximize):
Now, place your left hand on the keyboard (to hit the space bar), and let the fun begin. Each time person A appears in a photo, left-click with the mouse (never ever move the pointer from the tag. Space bar will make the photos advance wherever the mouse pointer is). When it doesn't, ignore and go on. When you reach the last pic, rinse, and repeat for persons B through Z.
With this method I tagged 197 pictures in under one hour yesterday. A bit over 3 pictures tagged per minute does not look too impressive, but the 197 pictures contained 9 different persons (9 tags to apply), each one of which appeared in roughly 30 pictures. This means I did 9 slide shows of all the pictures, applying a total of more than 250 tags.
Linearly scaling method
The above method is very fast with respect to each tag applied. However it scales up quite badly, because it is slower the more pictures one has to tag (obviously), and also the more different tags one is applying (one full scan of the picture set per individual tag to apply). The dependency with pic count is unavoidable, but let's see if we can devise a way to reduce the impact of the latter.
We begin by grouping all the potential tags (say, all people who appear in the set of pictures) within a single parent tag (see following screenshot):
Now, we can follow steps similar to the ones above, for the fairy tale method, but for each picture we will apply tags for all people appearing in it. This will make tagging each picture slower, but will require a single pass. Doesn't a single N-times-slower pass take as long as N fast passes? Yes. But recall our single pass here will not take N times longer (assuming N people to tag for). A lot of pictures with no people on it will be just as fast to (not) tag as in the method above, plus most photos will feature one or two people, and very seldom will all N people appear together, so this single pass will not be N-times slower than our N passes above.
[Update]: After writing this post, I put the second method here to test, and tagged almost 1300 pics in one hour!