The nightmare of tagging multiple photos with digiKam, and a hacky way around it. Part II

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):

I assure you the fabled person A is hidding somewhere within those Cuban trees

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):

A’s friend, C, is somewhere over there, as well. Do you C him?

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!

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The nightmare of tagging multiple photos with digiKam, and a hacky way around it

[Update and big fat warning]: apparently, renaming or moving files does mess with the tags the image already has. A way around this, and maybe a generally good idea (use your own judgement on that one), is to make digiKam save the tags as [[metadata]] into the picture files themselves. On the con side, tagging your pictures will actually modify the files (maybe you don’t want that), but on the pro side, the tags will travel along with the files, no matter what name or location they have (even to other computers, which may or may not be what you want).

[Update #2]: apparently the metadata approach doesn’t work either. It seems that each time a tag is assigned, the metadata is immediately saved (which is great), but only the tags digiKam is aware of at that moment. Also, digiKam is not immediately aware of the tag metadata of the pics it’s showing (you have to tell him so, I think). Let’s say you tag a pic as “A”. Metadata for “A” is saved. OK. Now, you change the name of the file, and digiKam loses track of it. You rename back, and digiKam thinks the picture has no tag (the metadata is obviously still there, inside the file, but digiKam doesn’t read it until you tell it to). Now, you assign tag “B” to the picture, expecting the file to end up with both tags: A and B. Tough luck. The split second you tag the file with “B”, it is written to the metadata (OK), but only tag B is written (the only one digiKam is aware of at that moment), so tag “A” is lost. In two words: the following post is full of crap. If a third word is allowed, let me say that digiKam is too.

First off, let me admit that my problem might have a simple solution. Maybe my goal is much simpler to achieve than I think. But what I am doing seems fairly common to me, and a pain-free recipe to do it escapes me.

The problem

I use [[digiKam]] to manage my photo collection. A very handy (and basic) function of digiKam is to tag photos. I tag photos with three criteria: where it was taken (e.g. “Donostia”), the event it can be framed within (e.g. “Wedding of A and B”), and a tag per person that appears in it (e.g. “John Smith”, “Jane Doe” and “Janet Johnson”). It involves some work, but afterwards I can really easily find say, all pictures in which John Smith and Jane Doe appear together, in any place but Donostia. Why I would want to do that is anyone’s guess, but that’s offtopic.

Every time I have a batch of photos (say, a wedding or some holidays), I sit down in front of my computer, and tag evey one of them. Tagging by event is a breeze (99.9% of the time, the whole batch of pics belongs to the same event), and tagging by location is also simple (each pic has a single location, and many, if not all, share that location). However, tagging by person is a bit trickier. Each photo can have many (or no) people appearing on it, plus it takes a bit of attention to spot all people appearing.

When tagging by people, two approaches can be taken:

  1. Parse photo by photo, tagging each one once per person appearing on it. Don’t move to the next photo until tags for eveyone appearing on current one have been asigned.
  2. Parse whole batch, once per person. You pick a person, select all pics where she appears, then you tag all of them simultaneously. Repeat for each person.

I have found that, for large amounts of pictures, the second approach is fairly superior. However, it is not problem-free. Firstly, multiple selection is only possible in a grid view. That is, pictures are presented as [[thumbnails]], aligned in columns and rows. Even in the largest possible size for such pictures, often times there are many photos that are too small to spot all people in them. Secondly, having selected some dozens of pictures out of some hundreds, and mistakenly unselecting them by clicking where you shouldn’t, or failing to hold the Ctrl key when clicking (or whatever error whose probability to happen increases with the amount of pictures to tag) is just painful.

Fairy tale solution

I realized a hybrid method would be advantageous, but that’s where the problem comes: I find no simple way to accomplish it. I would like to be able to do the following comfortably: inspect the photos one by one, tagging each one in which person A appears. When all are tagged, repeat for person B, and so on. Right now this approach will take longer than either approaches above, because it borrows the worse characteristics from both (one-by-one tagging of method 1, scanning all the photos repeatedly, once per person, from method 2). The reason for that is that asigning a single tag to a single photo is cumbersome. You right-click on the photo, then select “Assign Tag” from the menu that appears, then choose a tag from the drop-down menu (and submenus if case be).

There is no shortcut that one can assign to some tag, or, even better, a single-key shortcut for “assign to this photo the last tag I have assigned to the previous one”. If there was, my hybrid approach would be really fast: take person A, appearing in picture 1. Tag pic 1 with “A”. Then go picture by picture (a single hit of the space bar), either ignoring the pics where person “A” does not appear, or pressing the “apply last tag” shortcut (a single keystroke) where she does.

Hacky solution

Of the tools that digiKam offers, which one can modify a photo in a way that the contents are not touched, yet we can group them afterwards based on that change? Easy: rename (F2 key). When you press F2, a rename dialog appears, with a field where you can enter the new name for the currently selected pic. The good thing is the field is already filled with the current name of the photo. So, if you want to rename a photo to, say, the same name but with a trailing dot, all you have to do is press the sequence: F2 + . + Enter.

Now, how on Earth would the renaming help? Well, we could use the above “trick” to quickly rename all pictures in which person A appears, making all of them have the same name, but with a trailing dot added. Then, we could Alt-Tab to a terminal, cd to the dir where the photos reside, and execute the following ([[Z shell|zsh]] syntax, translate to your favorite shell):

% mkdir totag
% for file in *.; mv $file totag/`echo $file | sed ‘s/.$//’`

That will put all files ending in a dot inside a subfolder called “totag”, renaming them back to their original name (chopping off the last character, which would be the dot). Don’t forget the fact that these files happen to be all in which person A appears. Recall as well that digiKam keeps track of the tags applied to each photo by its [[md5sum]] (OK, I made that up, but it must be true), so moving files around and/or renaming them (both things are one and the same, actually) doesn’t mess with the tags. (see warning at the top of this post).

So, once all pics with person A reside in folder “totag”, we can Alt-Tab back to digiKam, go to that folder, select all pics, and tag them all at once. After that, Alt-Tab to the terminal, and execute:

% mv totag/* .

The real beauty of using a shell for that (even with the apparently complicated command with the for loop above), is that you can reuse the commands trivially. For person B, once all relevant photos have been renamed with a dot, Alt-Tab to the terminal, hit the Up arrow twice, then Enter, and you will move and rename all files again in just three keystrokes (two of them being the same key hit twice). Alt-Tab to digiKam, tag all pics in the “totag” dir. Alt-Tab to the terminal, Up+Up+Enter (which now executes the mv), and you have the files in the main dir again.

Conclusion

Yeah, I bet right now you are considering whether my idea of what is “simple” or “comfortable” is seriously off. I’d still vote for the “Reapply last tag” shortcut in digiKam. It would make a three-keystroke step (F2+.+Enter, to rename) a single keystroke one (reapply last tag with shortcut), plus would make the steps involving the terminal unnecessary. But reality is a bitch, and we don’t have such a shortcut. I could either just rant about it on my blog, or go ahead and find a solution myself. I chose to do both :^)

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MacOSX ate my pics

OK, so the 2GB [[Secure Digital card|SD]] card I use in my camera has its problems. Apparently, only 1GB of it are recognized by the OS (Linux) and/or the card readers I own. The problem seems to be common, as you can see by googling about it. More info, from the Wikipedia article for SD cards:

Devices that use SD cards identify the card by requesting a 128-bit identification string from the card. For standard-capacity SD cards, 12 of the bits are used to identify the number of memory clusters (ranging from 1 to 4096) and 3 of the bits are used to identify the number of blocks per cluster (which decode to 4, 8, 16, 32, 64, 128, 256 or 512 blocks per cluster).

In older 1.x implementations the standard capacity block was exactly 512 bytes. This gives 4096 x 512 x 512 = 1 gigabyte of storage memory. A later revision of the 1.x standard allowed a 4-bit field to indicate 1024 or 2048 bytes per block instead, yielding more than 1 gigabyte of memory storage. Devices designed before this change may incorrectly identify such cards. Usually by misidentify a card with lower capacity than is the case by assuming 512 bytes per block rather than 1024 or 2048.

For the new SDHC high capacity card (2.0) implementation, 22 bits of the identification string are used to indicate the memory size in increments of 512 KBytes. Currently 16 of the 22 bits are allowed to be used, giving a maximum size of 32 GB. All SDHC 4-GB and larger cards must be 2.0 implementations. Two bits that were previously reserved and fixed at 0 are now used for identifying the type of card, 0=standard, 1=HC, 2=reserved, 3=reserved. Non-HC devices are not programmed to read this code and therefore cannot correctly read the identification of the card.

All SDHC readers work with standard SD cards.[ref]

Many older devices will not accept the 2 or 4 GB size even though it is in the revised standard. The following statement is from the SD association specification:

“To make 2 GByte card, the Maximum Block Length (READ_BL_LEN=WRITE_BL_LEN) shall be set to 1024 bytes. However, the Block Length, set by CMD16, shall be up to 512 bytes to keep consistency with 512 bytes Maximum Block Length cards (Less than and equal 2 Gbyte cards[ref].”

I have had problems in the past with this issue, and could only retrieve the photos exceeding the “first GB” of the card with a tedious operation: copy some photos from the card to the internal memory of the camera (28MB), remove the card from camera, connect camera to computer, download the photos in the internal memory (and empty it), unplug and repeat. 1GB/28MB = boring as hell.

However yesterday I realized that I had a shinny MacBook with its MacOSX intact. I read somewhere that Windows would sometimes read 2GB cards that Linux couldn’t, by the simple method of happily ignoring the f*cked up file system in them. Maybe MacOSX could, too.

Well, it turns out it couldn’t. When I attached the card in the card reader (I didn’t try with the camera directly), MacOSX found the device and mounted it, giving me a nice icon in the Mac version of “My PC”. However, the directory the icon led to was empty. I thought “Tough luck, Mac reads nothing in the card”, unmounted it and unplug it. Then I placed it in the camera again, turned it on and… there was no photo in the darned thing! MacOSX had erased them!

There is still the (likely) possibility that I made some deep mistake, but the explanation for now seems that MacOSX ate my pics. Sad.

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