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Adobe face recognition: beat the system?

The Kobayashi Maru test is not a test of character unless you see the world in terms of “go down in dignity with the [star]ship” or “be a coward.” Or whatever Nick Meyer thought the outcomes would be. Captain Kirk won the test by not accepting a binary decision tree. This is exactly how you should approach any problem that looks like it is unwinnable. Rewrite the simulation. Use a screwdriver as a chisel.

One of the ways you can do this is to ignore the process as presented completely, decide your goal state, and then selectively use whatever is available to get there. Face recognition is exactly such an exercise. Adobe would have you select one of two suboptimal tools (Lightroom Classic or Lightroom) and have you build out the recognition process and leave it in the platform where it started.

Not believing in the no-win scen-ah-ri-o (sorry, Shatner), I started with the first principle:

What is the purpose of face recognition in photos?

This is actually a really good question. The way the process on Lightroom proceeds (either version), you think the purpose is to name every person in every photo and know what precise face goes with every name. This view assumes that you are a photojournalist who needs to capture stuff. You will go bat crazy trying to achieve this goal if your back catalog is hundreds of thousands of pictures and you use Lightroom Classic (“Classic”) as your primary tool.

Let’s face it – you are (at least this year) a work-at-home salary man, not Gene Capa. The real utility of face recognition is to pull up all pictures of someone you actually care about. You need it for a funeral. For a birthday party. For blackmail.

That does not actually require you to identify precise faces, just to know that one face in the picture is the one you want. You already know this person’s name and how the person looks. And even if you didn’t remember, a collection of pictures of that person – no matter who else was in or out of the shot – would have one subject in common. You would know within a few pictures who John Smith was.

Taking this view, a face identification is just another keyword.

It’s not even 100% clear that you would ever need it done in advance, on spec, or before you had a real need to use it.

What do we know about face recognition in LrC vs LR?

Our statement of problem: 250,000 images of various people, some memorable and some not. I want to get to being able to pull up all pictures of John, Joe, Jane, or Bill. And I want this capability to last longer than my patience with Lightroom cloud. I want to be able to ditch Lightroom, even Classic, one day and change platforms without losing my work.

When you are figuring out a work flow, or trying to, it’s helpful to consider what your tools can and cannot do; hence, with Classic and Cloud, start breaking down the capabilities.

  • Both recognize faces with rudimentary training.
  • Cloud is much faster than Classic and tends to have fewer false hits (due to Sensei)
  • Both can do face recognition within a subset of photos.
  • Classic can an apply keywords to images that Cloud can see/
  • Cloud cannot create keywords that Classic can see.
  • LrC has better keyword capabilities, period.
  • You can make an album in Cloud and have it (and its contents) show up as a collection in Classic.
  • You can put things in one of these items in either program and have it show up in the other.

Do these suggest anything? No? Let’s step through.


Let’s talk about some preliminaries that no one ever seems to address.

Order of operations. If you are starting from zero, you should identify faces in the import every time you import something. Not only are names of near-strangers fresher in your mind, it also prevents the kind of effort we are about to explore.

What’s my name? You must have a naming convention and a normalized list of names. It doesn’t matter whether you pick someone’s nickname, real name, married name, whatever. Whatever you decide for a person must be treated consistently. Is my name Machine Planet? Planet Machine? PlanetMachine? This has implications for Classic, where you can’t simply type a two-word name (Bill Jones) into the text search box without getting everyone named Bill and everyone named Jones. For that you might want to concatenate both names together (unless you want to use keywords in the hierarchical filters). In Cloud, the program can sort by first and last name, so there is value in leaving these separate.

Stay in the moment. Although you might be tempted to run learning against every single picture you have at once, this leads to a congested Faces view (or People view), slow recalculation on Classic and a lot of frustration. Do a day or a week at a time. Or an event. This will give you far fewer faces from which to choose, and fewer faces to identify. Likewise, if there is a large group picture in the set, focus your effort on tagging everyone in it. This will set up any additional Identified People in Classic and will kickstart Cloud.

Who’s your friend? You next need to decide who is worth doing a lot of work to ID. You are not going to do iterative identification (especially on Classic) with people you don’t care about. Leave their faces unidentified. Or better yet, delete the face zones. This is a very small amount of effort in a 200-shot session or a 36-shot roll of scanned pictures.

Start in Cloud. This part is not intuitive at all. Go ahead and sync (do not migrate!) all your pictures to Lightroom mobile. This consumes no storage space on the Adobe plan. If there are a lot that have no humans, use a program like Excire Search to detect pictures with at least one face pointed at the camera. This is a reasonable cut, since there are few pictures you would bother tagging that have one face, solely in profile.

The synch process will take forever. I don’t think there is a lot of point in preserving the Classic folder structure when you do this; I would just make a collection like “Color 2000-2010” in the Classic synched collections and dump your targets into that (n.b. a collection in Classic is just an alias to your pictures; making a collection does not change the folder arrangement on your computer). We are only using Cloud for face recognition; its foldering is too rudimentary and inflexible to be useful – although right-clicking in Classic to make folders (or groups of folders) into synched folders will let you adopt the Classic organization in Cloud, albeit flattened, without re-synching. Again, not very useful. Also, for reasons described further on, you want to have a relatively clean folder panel in Cloud because you will be making some albums, and you don’t need extra clutter.

Ok. Let the synch run its course, or start your identification work on Cloud as it goes. Cloud will start aggregating what it thinks is the same face into face groups, which you then must name. Start naming these according to the convention you chose. I would put the People view to sort by “count,” which naturally puts the most important people at the top (you have the most pictures of them). Let’s say you name one face group “John Smith.”

Crossing over

The process so far is pretty generic. To start crossing things over to Classic, you need to make folders (“albums”) in Cloud. Start with one per important person (“___ John Smith”). Search for that person. Dump the search results into the album. You can always add more later.

Now flip back to Classic. You will see collections under “From Lightroom.” Voilà! One of them is “John Smith.”

Now you can do one of two things.

You can simply make a quick check to make sure there are no pictures included that obviously are not John Smith. But after you do that, or not, you can mass-keyword everything in that collection “John Smith.” If you named John Smith consistently with any pre-existing Classic face identification of John Smith (i.e., not two different variations of the name), your searches will now have the benefit of both tools. Save those keywords down to the JPG/TIFF files (Control-S/Command-S) or XML files (same), and you will forever have them, regardless of whether you leave the Adobe infrastructure. In fact, many computer-level file indexes can find JPGs and TIFFs by embedded keywords (which the index sees as text).

Congratulations. Now you’ve highjacked Sensei into doing the dirty work on Classic.

With a small but not overwhelming amount of creativity, you could use a technique like this to cross-check your past Classic calls.


Second, if you’ve missed your OCD meds, you can also use the results of this to inform your Classic face-recognition process.

a. Select this “From Lightroom–>John Smith” collection and flip to Faces view in Classic.

You are now seeing all “Named People” and all “Unnamed People.” Unnamed people are shown by who Photoshop thinks they are most likely to be. You can sort Unnamed people in various ways, but however you do it, you want to get John Smith?s in a contiguous section where you can then confirm or X out. By going into this in the From Lightroom–>John Smith collection, you are not waiting for recalculations against every photo you have – just the ones that Sensei thought should have John Smith.

So the cool trick is this: if you see 106 pictures in From Lightroom–>John Smith, then you know you are probably going to be done when you have 106 confirmed pictures of him. Or done enough. John can only appear in a picture once. There will be a margin of error due to how closely Classic can approximate Sensei, but you can get to about 90% of the Sensei results without a lot of trouble. This is a bit better than Classic on its own, where more pictures of John Smith at an earlier age might be really buried down in the near matches. Further, Classic is something of a black hole for similar pictures because unlike Cloud with Sensei, there is no minimum required similarity score to be a suspected match.

b. You can, of course, drill down on John Smith as a Named Person. You don’t have much control over how “Similar” pictures are ordered (I believe it is degree of match for the face), but here, you can confirm a much more concentrated set (after you decide how to deal with the “fliers” who are not John Smith).

One other technique I have developed while in the “confirming” stage is that it may be easier to confirm en masse (even if some are wrong) down to the point where the “not John Smiths” are about a third of the results in a row of Similar faces. A small number of “fliers” can be removed by going up to the Confirmed pictures, selecting them, and hitting delete. Trying to select huge swaths of unconfirmed faces in Similar and then unselecting scattered fliers tends to really slow things down. As in Classic really slows down as it tries to read metadata from everything you selected.

Incidentally including and then manually removing a few fliers from Confirmed does not seem to affect accuracy (because every recomputation of similarity is on the then-current set of Confirmed faces – changing that set changes the computation). If you have 99 pictures that are right and one that is wrong, it won’t even change the accuracy appreciably. If in Confirmed, you have 995 pictures that are John Smith and 5 that are not, again, the bigger set of correct ones will predominate future calculations.

Next, at some point, especially with siblings, Classic is going to reach a point where Jane Smith (John’s Sister) is going to show up as a lot of the “Similars” with John Smith. When this happens, go back to Faces (top level, always within From Lightroom–>John Smith), click on her, and confirm a bunch of her pictures. When you go back to Named Person John Smith, a lot of the noise will be gone, and hopefully more John Smiths will be visible in a concentrated set you can bulk-confirm.

Crossing back (optional)

I did write “iterate,” right? You might want to keep your Cloud face IDs as complete as possible, since there is not 100% correspondence between results from the methods used by the two platforms. This is relevant if you have already trained Classic on John Smith.

  1. In Classic, note the count in your From Lightroom–>John Smith collection. Say it’s 106 pictures.
  2. Do a search from your Classic Library for all pictures of John Smith. If you used a space in the name, add Keywords to the field chooser menus (via preferences) and select that line.
  3. Drag all of those results to From Lightroom–>John Smith.
  4. Flip to Cloud. They are now in that “John Smith” album. Or they will be when it synchs.
  5. Select all the pictures in the “John Smith” album.
  6. Hit Control-K (or Command-K) to bring up keywords and detected/recognized faces in the “John Smith” album.
  7. Now name any faces that are blanks – but should be John Smith.
  8. Now from the All Pictures view, search for John Smith and drag all his pictures to the John Smith album.
  9. In Classic, check your count. If it’s say 128 pictures, now, that means that Cloud took your examples and found more John Smiths. And now they are ID’ed in Classic as well.
  10. Switch to Faces and confirm the 22 additional faces as John Smith. Now both systems have identical results.

Calibrating your efforts

For searches for random people, Cloud is still the best because it requires very little training. That said, for randos, you are using a tool that does not give you any permanent results. That’s probably ok for people who you don’t really care about. Or if you plan to be on Cloud forever.

For close friends and family, you may just run the “Crossing Over” exercise. I would do it in groups: do a bunch of albums on Cloud (say seven people), then do a bunch of naming on Classic (their collections), etc.

If you are really a neat-freak or compulsive, you could use the “Crossing back” step. But Sensei is reasonably good at what it does, so the marginal effect of adding Classic results to Sensei may not be much. If you have Excire, you might use it to find pictures that look like a picture of John Smith, which will give you a third means of concurrence.

The thing to remember about face recognition is that it is miraculous but also imperfect. It has to detect a face and then it has to identify a face. It doesn’t see how you see. Efficiency works at cross-purposes to accuracy.

But it is still vastly better than trying all of this on your own.

Face-off: Apple vs. Adobe face recognition

So here is a question: what’s the best way to catalogue and tag your pictures? Is it Lightroom Classic? Lightroom Cloud? Is it Apple Photos? Is it something else? Maybe it’s a lot of things. If you are a high-volume imaging-type person, you’ve probably wondered how to deal with things like tagging people. The most macabre application, of course, is the funeral collage. But say you have tens of thousands of pictures of family members and want to print a chronological photo album. Then what? Face recognition features in software may be your best bet. From a time standpoint, they may be your only choice. The problem is that different software has different competencies.

Apple Photos

Something like Photos is designed to group pictures, more or less automatically, around people, events, dates, or geography. Think of it as your iPhone application on steroids. Photos is not big on user control. It is not even engineered to do anything with folders except display them if that’s how photos were imported.

Face recognition in Photos is incremental and behind the scenes: it only finds faces when you are not actively using the program, and over time, it batches up groups of pictures which you confirm or deny as a named person in your Faces collection. To establish your Faces collection, you have to put names on faces in a frame where faces have been detected. This tends to mean that face recognition proceeds by which faces the user thinks are most important. As it should be.

Unlike Lightroom, Photos does not presume that detected faces are unique. It applies a threshold such that if it detects Faces A, B, C, and D, and they are close enough, they are treated as the same (unnamed) person. As such, naming one person can have the unintended effect of tagging a bunch of false matches. Either way, you can error correct by right-clicking the ones you see that are wrong.

My assessment of Photos is that it is not suitable as a face-recognition tool if you have hundreds of thousands of images, for several reasons:

  • Its catalogs are gigantic, even if you use “referenced” images. Photos loves it some big previews, no matter what you do. For scale, my referenced Photos library is 250gb where my entire Lightroom Classic library folder is 40gb (both excluding original image files – so Photos sucks up 6x the space).
  • The face recognition process appears to be mostly (if not completely local), it runs in spare processor cycles, and in my experience, can cause kernel panic. Hand-in-hand with this is the fact that you can never actually turn Photos off. It’s part of MacOS.
  • There does not appear to be any indication that Photos actually writes metadata to files. So when you move to a new application, you’re starting from zero.
  • You can’t really use it in conjunction with a grown-up asset management system like Lightroom.

Photos is, however, good for generating hilariously off-base collections of photos (memories) with weird auto-generated titles (“Celebrate good times” with a crying baby as the cover photo). Or collections based on the date a bunch of pictures taken over decades were scanned (such as my 42,600 pictures apparently taken on December 12, 2008). I actually have no idea where these are generated. But they are funny.

I’m sure Photos is really good for those funeral collages, though.

Lightroom Classic (LrC)

Something like Lightroom Classic (LrC) is designed around manipulating, filtering, and outputting large numbers of pictures at once. This is, indeed, the killer app for handling large volumes of photos, and becomes a single interface for everything. It’s OK, but not great, for face recognition.

To put it mildly, LrC’s face-recognition is processor- and disk-intensive. The best way to use it is to use it on a few hundred photos at a time so that your identifications don’t swamp everything in your collection in a recalculation. LrC is good at showing you different faces all at once, as single images, so you can get cracking on identifying as many new “people” as you have patience for in one sitting.

The top level of the Faces module shows you (i) “Named People” and (ii) “Unnamed People.” You need to name at least one “Unnamed” person to start. After a while, the system will try to start putting names on “Unnamed” people. If you have a Named person named “John Doe” and are presented with an image that is “John Doe?” you can click the check box to confirm it and the X box to remove the suggestion (clicking again removes the detected face zone, such as if the system mistook a 1970s stereo for someone’s face).

Once you have done that, you can drill down on a “Named” person to see what pictures are “Confirmed” and what pictures are “Similar.” Again, to move from Similar to Confirmed requires an affirmative call. Here, you only get a check box. There is no “Not John Doe” option, which means that every possible match is shown, ranked in what LrC thinks is similarity. This is actually problematic because as you confirm more pictures, the number of “Similar” pictures rises exponentially. This puts a huge computational drag on things.

Wherever it happens, confirmation of a face’s identity is an affirmative process that is repeated for each picture (you can select several). This prevents false IDs based on grouping disparate real people into one “face,” but it also makes tagging excruciatingly repetitive. And slow. Highlighting faces to group-confirm or identify can have the “highlight” lagging far after your click. And God help you if you click six pictures and then try to type a name into one to rename all six. It works about half the time. The other half, it auto-completes with a totally unintended name. If you accidentally confirm the wrong face for a given name, you can highlight the errant thumbnail and hit Delete (this is not well documented).

Critically, the top level of the Faces module (where you see all named people as thumbnails) is the only place where the system puts a “most likely name” on unnamed people. Otherwise, looking at any particular “Named Person,” the same person – Bob – might show up as a similar for John Doe. And when you switch to Richard Roe, Bob will show up as a “similar” for him as well. This is part of the reason why people for whom you have 10 actual pictures always show up with 20,000 “similars.”

A big advantage of LrC over other solutions is that you can see and tag faces within specific folders, collections, or filmstrips. This lets you make context-sensitive decisions about who is who. For example, I am pretty sure that my kids did not exist in the 1970s. Or I might know that only 6 people are represented on a single roll of film that constitutes a folder in my library.

When a name is confirmed on a picture, that name is written as a keyword to the metadata in the library. It appears that XMP files (if you chose that option for RAW files) are written with the actual coordinates of faces in the picture, which allows some recovery if you have to rebuild a library from scratch. The important thing is that a picture is keyworded with the right names. Face zones are nice but not quite as critical in the long run because in reality, you only really care whether a picture contains John Doe or Richard Roe, not which one is which in a picture of both.

Always save your metadata to files if working with TIFFs/JPEGs/scans (Command+S) or “always write XMP” with RAW camera files. This helps keep your options open if you want to get divorced from Adobe. Or if your Lightroom library goes wheels-up and you have to rebuild from zero. There is no explanation for why this program just doesn’t write an XMP for every file. It would make things easier.

Lightroom [CC or “cloud”]

What a hot mess. The only thing that really works about Lr CC is face recognition. The rest of it is a flashy, underpowered toy that despite being “cloud” based can still consume massive amounts of hard drive space and processing power. If your photos are in the Adobe cloud, or synched from LrC, the program works with smart previews.

Adobe’s Sensei technology is a frighteningly good face-recognition system. In the People view (mutually exclusive with the Folders view), it takes all of your photos and groups them according to what it thinks is the same face (like Apple Photos). Put a name on that face, and it might ask you if this other stack over here is the same face. It is extremely fast (because it runs in the cloud). Sensei can also identify objects, and to some degree, places in photos. Naturally, the most important people in your life have the highest counts, and you can sort unnamed faces by count and work your way down. Things break down when 400 people have 15 pictures apiece, though…

The system, though, has some amazing limitations that are pretty clearly engineered in by a company that is trying to move everyone to its walled garden. Two of these four bear directly on the issue of why a hard drive – and keeping your own metadata local – is your ladder out of that walled garden.

First, metadata transfers to Lr are one-way. The program can absorb keywords applied in LrC, but not recognized faces/zones, and nothing you input in Lr can ever rain down on LrC. There is no programming-related reason that prevents metadata from flowing the other way, aside from intentionally engineering this out of being possible — so that you are eventually forced to store all your stuff in Adobe’s per-month-subscription storage space. Because paying a monthly to use programs that aren’t really being updated – like LrC – was not bad enough.

Second, you cannot force face recognition on arbitrary subsets of your library, at least very efficiently or intuitively. If you came at this program assuming that it would be like LrC, you would conclude that there is no way to do this. Instead, you have to select a group of pictures and hit Command/Control-K (for “keyword” – how intuitive…) to see the faces present in the picture or group. Lr then shows you the single picture with the face boxes – and the collection of faces in the picture on the right panel. This is great – but why is it so hard to find? You also get the impression that when you do this, the face boxes are generated on the fly. But the critical defect here is that the “named faces” that are shown as thumbnails are even smaller than the other face thumbnails in Lr.

Third, when asked to “consolidate” two faces, there is no way to flip between the two collections. This is an oversight – you are not asked to name a person based on one photo, but for some reason you are asked to make a consolidation decision that could have catastrophic consequences — based on a single fuzzy thumbnail. If in doubt, sit it out.

Finally, you can’t push face recognition data back down to LrC. So if you use LrC, you basically end up with completely separate face-recognition data sets based on the same photos. This is a big-time fail.


Well, in terms of applications you can access for a Mac right now, the options are ok – but not great. Stay tuned for Part 2, in which we look at a way to leverage LrC and LR CC against each other to speed things up.

Archivism: immortalitas vel non

Everyone in this picture is dead. The man on the left could not beat actuarial tables. The next man over, in the yellow, had a stroke. The teenage girl died of breast cancer. The boy met an industrial accident. The lady in blue was hit by a car. And the guy on the right was killed when his girlfriend’s husband came home unexpectedly.

One. Ok, so I made that all up. What I do know is that this picture is from Rio de Janiero in the spring of 1979. I know my grandfather took it. I know it’s on Ektachrome, in a Bell & Howell slide cube, in a tray of slide cubes, in a box, in my basement. And that is all I know about it.

Two. For fun, I put to a Facebook film group the question of how to deal with this — and thousands of other slides that contained no people that I (or any other living person) could identify, with little artistic or editorial merit (I could easily pull out the ones with family members, which is a small fraction). This was due to being lazy; I could have just fed these into a Nikon LS over a few weeks. I asked what lab could scan pictures like these so that I would be “done” with them, throw them out, and free up some physical space. The reaction was as expected. What? Discard originals? They are more archival than digital, so why downgrade? The reactions ranged from puzzlement to indignation.

Three. Part of the difficulty in dealing with modern photographers is the idea that every sperm is sacred (apologies to Monty Python…) and that you can never, ever dispose of a physical piece of media, no matter how worthless. I chalk this up to being an artifact of digital – people don’t edit their digital work because storage is cheap. That carries over into a feeling that one can’t dispose of any piece of film, ever, never, not ever. Also, when film is expensive, you’re throwing money away, right?!

Do these guys know that in ye olden days (meaning just 25 years ago), people tossed slides all the time? I mean, there is no rotary slide magazine that is a whole number multiple of any length of film, unless you were shooting old rolls of 20 and hit 100% of the time… and not even the Almighty shoots that many keepers. Before matrix metering, it was hard as hell to shoot slides. Ok, shoot them well.

Do they know that when you’d pick up prints from a minilab, you would put the rejects right in the trash? How about leaving those neatly scalloped four-frame strips of badly stabilized C-41 negative in an acidic paper envelope for fifteen or so years?

Do they know that when you only get one frame to come out on a roll of film, you don’t have to save all six strips of negatives? Or, if you don’t like that one frame, any of them?

Do they know people threw away test rolls all the time? Today, I was adding up some numbers and figured out that I had shot about 1,900 rolls of film in 25 years – and that I had probably pitched fifty whole rolls of test pictures.

Four. The archival film protection business had a boom in the 2000s. Granted, old vinyl photo pages were a train wreck. “Try our new polyethylene ones. They last for centuries!” There was always something new: non-acidic fixer, paper, binders, sleeves, chemicals. Your pictures will live forever. Forever, of course, was a lot shorter time when everyone smoked.

With digital imaging came “archival” inkjet paper and the thousand-year, erm, hundred-year archival, pigment-based inks. Pushed partly as a way to justify charging big money for inkjet prints perceived as less valuable than chemical prints, these new materials turned out to be a way to perpetuate prints of bad pay-to-play nudes, early Photoshop compositing abominations, and anodyne and provincial landscapes. Had this work faded faster, it would have been immolated in trash-to-energy plants before that method of waste disposal was outlawed. Now they just stuff landfills, visual interest improved occasionally by the overturned bottle of Palmolive thrown in on top of them.

Today, we worry about the longevity of digital. You could record things on Mitsui gold DVDs. Or M-Discs. Or asynchronous offsite backups. Or in the cloud. Or in a holographic data storage array in a quartz crystal when that day comes. The possibilities are endless because we are constantly coming up with new ways to hoard and new ways to pack bits into smaller spaces using more permanent materials.

Five. As John Chrysostom would have said in the 400s (or actually did say…) “all is vanity.” Somebody once said that you don’t die until the last person forgets you. Many cultures and people have taken credit for this line (I first heard it on Westworld), but like all good retransmissions (or appropriations) of someone’s culture, it gets recycled because it actually is useful.

When we think about photography and archivism, we might be solving for the wrong variable. We try to make everything last forever using blunt force. The actual problem is motivating preservation in others, not in achieving it ourselves. You might think that color film will fade in 20 years. Or black and white in 100. Or that your prints will discolor and fade. Or that JPGs will somehow be obsolete in the future and unreadable.

The real danger is not time, or technology, or the elements, or phlogiston. The real danger is that the work will fall into the hands of someone with no interest in it – or for whom the effort of understanding the work is overwhelming compared to any potential benefit. When you’re at a secondhand store looking in that shoebox at the counter (or were, in the Before Times), you always wonder what kind of philistine gets rid of family pictures. Well, it could be you. Or me (see above). Or our children. All it takes is for someone to be looking at a collection of random pictures of strangers and to give a shrug of the shoulders. Someone to decide that there is no room for one more photo album. Or no point in renewing a cloud storage subscription. Or that they need that 12tb hard drive for something else. Or they lack the decryption key to open the drive with the files (nota bene: this is coming).

Six. Things become valuable for a couple of reasons: intrinsic value and attrition. An Ansel Adams print would be valuable even if the supply was less finite. By the same token, we preserve a lot of historic buildings and cars that were poorly designed or poorly made — but are the last exponents of their age. The average person has no ability to influence this aspect of his or her photography except (a) to be brilliantly good (bonus points for the back story that includes dying young of consumption) or (b) have his or her output survive some extinction event that wipes out trillions of other images. Let’s all shoot for “brilliantly good.” Dum spiro spero.

Seven. Maybe what we should do is not fixate so much on the hoarding so much as encouraging future preservation. Is it an uncomfortable subject because it’s not something you can buy?

  • Things that are accessible are more likely to be enjoyed. That might be a printed photo album. It might be one that is shared online.
  • Label, organize, and give people a reason to save your stuff, long enough for it to become valuable (enough) to strangers. Why does this picture matter? Even banalities of everyday life can matter later. What may be an unimpressive picture of a hotel today might be the only visual representation in a future in which it has been knocked down.
  • Follow directions when processing your materials. You might be surprised at how long “non-archival” material lasts. In fact, the pictures in that shoebox in the antique store – printed on acid-containing paper and probably not properly fixed by today’s standards – are a hundred years old and have outlived the use anyone had for them.

You might find in the end that your time and money is better spent on life experiences than making the record of it last just a couple more years longer. If you do good work and give it meaning, people will find a way to preserve it.


Punching your way into film identification

So the usual has happened. You have a pile of undeveloped film. Maybe you didn’t note the processing (N, N+1, N+2) or maybe it’s bulk loaded film that has no label on the cassette (for example, you might find it very easy to confuse Ilford Pan F Plus 50 with Ultrafine Xtreme 400). Or you can’t remember what order you shot film. Of course, the difficulty is that unless you somehow identify the film canisters, you’ll mix things up. And even then, once film is out of the canister and developed, there is rarely a persistent indicator of what happened. Data backs for 35mm cameras are something of a pain, they don’t record everything, and almost all of them are going extinct in 2018. Buy a Nikon F6 that records exif data? It’s a little late in the game for that.

The solution: the $5 arts & crafts hole punch and a $5 film-leader puller

One perhaps non-obvious solution is to permanently mark the film leader. You obviously can’t do this with a pen because the writeable part of the film will get washed off in processing.

The most effective way I have found to achieve this is with craft hole punches, which come in various hole sizes (1/16, 1/8, and 1/4″ – 1.5mm, 3mm, or 6mm), as well as a variety of shapes (round, hearts, stars, diamonds). As long as you make the marks on a part of the leader that will not be discarded (so not the long thin tongue part on commercially loaded film), these will survive the development process and won’t go anywhere until you snip them off. The uses are numerous:

— Bulk-loaded film: If you punch the leaders with a distinctive mark, you can avoid mistaking one type of film for another. For example, where it is very easy to confuse bulk-loaded Ultrafine Xtreme 400 and Ilford Pan F Plus, punching the Ultrafine with a heart will help you avoid mixing things up when loading your camera.

— Processing regime: If you are going to push-process film, punching the leader with a mark (such as a star) either before or after exposure will help prevent you from mixing up your N, N+1, and N+2 films. If you need to, you can use a leader-retriever to pull the leader out and mark it after fully rewinding.

— Order the film is shot: If you can’t imprint the first frame of a roll with a data back, you can use a number of punches to signify the order in which the roll is shot. You can even do this before you shoot the film.

— Camera or lens used: no data back records focal length, and camera bodies of the same make – assuming they even have a film-gate cutout for identification – use the same cutout (for example, Konica bodies usually have a triangle notched into the edge of each frame).

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Configuring an iMac Retina 5K for photo editing: tips


If you have been clinging to an older Mac Pro and are looking at potential upgrades, here are some notes on the iMac Retina 5K that might help you understand what to expect and what to order.

Processors. If you have been sitting on an older Mac Pro, you will simply want to go for the 4-core i7 at its maximum speed. The speed of photo editing software is much more dependent on simple clock speed than multithreading, and for this reason, the 4 x i7 iMac is probably going to be a better deal than the 2013+ Mac Pro. Let’s cut to the chase: the clock speed helps with Lightroom and Photoshop, and Adobe’s fear of multithreading means that you will want to go for the highest gigahertz figure. In addition, you cannot upgrade the processor later, so it is better to spend the extra $300 now.

Memory. The best configuration out of the box is 16Gb. This uses two slots and gives you the dual-channel speed you are paying for. Then buy two more 8Gb modules for $150. Then you are done forever. Hint: a child’s suction rattle is an excellent tool for removing the memory hatch, which is held in place by many spring clips.

Graphics unit. Don’t screw around on this part. A 5K screen requires a lot of capacity. Get 4 Gb of video RAM. This is another feature that cannot be upgraded later.

Screen: the most compelling feature about the iMac for photo editing is the 27″ wide, 5,000 pixel-width screen. It is like the Retina screen on an iPhone – just radically larger. The glossy finish helps blacken blacks (though it does sometimes show reflections). There are two effects of using a screen with this resolution, First, image files viewed 1:1 have an amazing clarity that makes it look like you are looking at the scene live – or looking at a good print. Second, you will need to look at many files at 2:1 to see what is actually going on in terms of sharpness, noise, etc. The screen on the 5K cannot be used as a secondary display for another Macintosh (and for good reason – they just don’t have the muscle to drive it). The system scales programs that are not optimized for 5K and manages to make everything work quite well.

Storage: unlike your Mac Pro, which could stash 12Tb on four internal drives (or a startup drive plus 3 drives making up a RAID 5), the iMac basically has two slots for storage. One takes PCIe flash memory; the other takes a 3.5″ desktop hard drive (or 2.5″ SSD with adapter). If you order the Fusion drive, you get a 128Gb card in the first and a 1-3Tb drive in the second. The two drives are linked as one logical volume via MacOS If you order straight flash memory, you get a flash drive that is 2x-4x the size (512Gb or 1Tb) and nothing in the HD slot (in fact, you don’t even get the connection cables). The problem with both of these arrangements is that PCIe memory wears out faster than hard drives, and the Fusion drive presents two independent paths to drive failure. Further, you are not really supposed to store your documents on the same flash/SSD drive as the startup disk and applications. All of this points to some kind of external storage solution. Consider using three drives:

  • Startup drive – this is the one in the machine. This should be an SSD, no question. Startup is 10 seconds; applications load and run immediately. This should contain a skeletal admin account so that you can start up the machine without any external drives if something goes awry.
  • User directories (really, documents). For reasons related to SSD wear and tear and general contention for resources, your user files should be an external drive – and preferably a bus-powered SSD. The bus-powered part is so that it can piggyback on a UPS serving the computer; the SSD part is so that it runs really, really fast (this makes a big difference with Lightroom’s Camera Raw cache and Mac mail). For backups, plan to clone the principal, mostly-static parts of your user account to the startup drive (or even documents other than space-intensive photo, video, and media files). The Library is the big thing you need, and you can exclude from the cloning files like web caches that change. Your main user directory should also be backed up via NAS to another device. The solid choice for this is the LaCie Rugged Thunderbolt SSD. If you look on Ebay, you can grab the 512Gb SSD unit for about $300, which is a steal, since it hits 400Mb/second through its Thunderbolt interface. You can get a Pegasus J2, but they are not nearly as fast.
  • Mass Storage Option 1: main storage on RAID 5. If you are doing a ton of photo work, you are going to need some large, fast drives. You will also want them to be reliable. The conventional solution is to use a RAID 5 system, which stripes data across a number of drives and records sufficient parity information to reconstruct a missing drive. Although this is more reliable, it is no substitute for a backup. When a drive fails, it can take many hours (or even days) for the missing data to be reconstructed. A second drive failure in the meantime generally means that you’re toast. And the total failure of the file system will wipe out everything on there. Consider instead the two-drive LaCie 2Big Thunderbolt 2 in the 6Tb size – in the striped mode, it runs in the 300Mb/second range for reads and writes. There are some even faster hard-drive-based units, like the Pegasus and the LaCie 5Big Thunderbolt 2, but these are much larger units that are designed for real-time video editing. They are also 4- and 5-drive budget-breakers, at $1,000 and up.
  • Mass Storage Option 2: main storage on RAID 0; backup on a NAS. Currently, Thunderbolt runs much faster than the fastest hard drive, so RAID o (pure striping) solutions are generally the best way to take advantage of some of the speed. The difficulty is that in a simple striped set, the failure of one drive takes everything down – and there is no way to upgrade capacity, The failure mode can be addressed by keeping cloned (or Time Machine) backups. In terms of capacity, you have to offload everything and then put it back on – but if you do that, you will already have fresh copies of your data on the off-loaded drives and backup of the machine on NAS. For the backup, I went with the LaCie 5Big NAS Pro diskless, which like the Synology and Drobo competitors has an intelligent RAID selector (SimplyRaid, a rebranded Seagate system) that allows you to incrementally expand the system by replacing one drive at a time. This is a big deal, since to expand a straight RAID 5 system, you have to offload all the data and then reload it onto the new array. This is why you should not buy a unit like the 5Big Network 2 – which in addition to being much slower, does not have the same expansion possibilities. The 5Big NAS Pro can also crank 60-90Mb/second on a gigabit ethernet line, which is an important thing to consider when you are running big backups over a LAN.
  • Incidentals – for dead storage or using up spare desktop HDs, check out the Sabio DM4LH Smart Raid 4-bay USB 2.0/eSata enclosures (RAID 0, 1, 0+1, 5, JBOD, Span). If you are sticking your Mac Pro in storage, you can yank out its 3.5″ drives and drop them in these well-designed enclosures and access them in JBOD mode. While the discontinued USB 2.0 version of this unit is not blazingly fast for massive transfers, you can get it for about $50 on Ebay and Amazon. Or you could plug its much faster eSATA connector into something like an Akitio Thunderdock. For more regular access, the USB 3.0 or Thunderbolt versions will be better. For single drives, MacAlly makes an enclosure that costs $75, looks like a mini Mac Pro (as if it’s a canopic jar…), and sports USB 3.0, Firewire 800, and eSata. It runs about $100. The version that has USB 3.0 and eSATA only runs $50.

Expansion: the typical silver Mac Pro has vast expandability, typically with (5) built-in USB 2.0 ports, (2) Firewire 800 ports, and (1) Firewire 400 port. It also has 3 open PCIe slots each of which can accommodate a card with up to four additional USB or Firewire ports or an eSATA bus. When you consider that the box itself holds 4 hard drives and 2 optical drives, the number of storage devices that can be connected to a Mac Pro without a hub is simply staggering. Some things to keep in mind:

  • Thunderbolt is far, far faster than anything hooked up to an old Mac Pro. Consider consolidating on larger devices with more storage. Yes, you could stick 15 Firewire drives on a single bus, but with drive sizes and RAID devices of today, you don’t need to.
  • Thunderbolt has a smaller device total limit than Firewire, and any device connected to the chain, however adapted (USB/eSATA/FW800) counts toward the total.
  • Some devices only fit the end of a chain (or chain plus adapter) – such as small external drives and some scanners (like the Nikon LS-9000).
  • You will eventually convert everything to SSDs and more modern devices. You might do this earlier than you anticipate.
  • Not all Thunderbolt interfaces are made equally. Some that have dual Thunderbolt and USB 3.0 connections run much closer to USB 3.0 speed.

The USB 3.0 ports will be exhausted faster than you think – an external DVD burner, a CompactFlash card reader, your iPhone cord, and the connection from your uninterruptible power supply (UPS) will suck up all four ports in a heartbeat. One bonus of the iMac is an SDXC card slot in the back of the screen/main unit, and it is plugged right into the PCIe bus – making transfers to the computer much faster than any USB 3.0 card reader. That said, its location is extremely clumsy.

If you need more storage and you’re willing to live with lower speeds, you can always plug USB drives into your NAS or your wireless router.

Keyboard and mice: the Apple wireless keyboard is compact, cord free (important given the USB port issue above), far more reliable than the old, full-size Apple Bluetooth unit, and very difficult to learn if your right little finger is used to touching the right side of any Apple Extended Keyboard. Consider whether you want to keep your old keyboard. The Magic Mouse is brilliant for photo editing because the gesture-based scrolling makes it easier to drag through huge Lightroom libraries, and the square edges make it easier to feel where to right click. Aside from that, the gestures do not help with Lightroom 5 or Photoshop CS6 – which do not support them. None of Apple’s current input devices will displace your Wacom.

Networking: for moving big pictures from networked storage devices, use the Ethernet port. Wireless is nice, but experience now demonstrates that not even AC1900 runs consistently as fast as gigabit Ethernet. One day, maybe. The actual connection speed is one issue – but the bigger one is these days, your computer is not the only thing competing for bandwidth on the router. With Ethernet, the detection, connection, and configuration of printers with their own IP addresses is much, much better.

Must-have software: aside from your usual image editing programs, here are three.

  1. The current version of Carbon Copy Cloner, which can be an important backup tool. If you have huge volumes of photos and use a nondestructive editor, Time Machine is dead-wrong as a backup method. The problem lies in a few things: (1) Time Machine is really designed to work with reasonable quantities of files that are changed from day-to-day (the largest thing with which you would trust it is your Lightroom catalog); (2) a Time Machine backup that contains terabytes of photographs will take days to initiate – and your main drive might fail in the meantime; and (3) Time Machine backups get screwy every so often and have to be redone from zero, which accentuates the risk in (b). With Carbon Copy Cloner, you simply clone your image file directories to another drive, either as directories and files or as sparse disk images. And if and when disaster strikes, you don’t have to try to do a selective restore from a Time Machine disk – you simply copy the files onto a new main drive and go on your merry way (actually, you could simply point your Lightroom library at the clone and keep working while you set up a new main drive).
  2. Mac Product Key Finder Pro. Migration assistant notwithstanding, many programs need to be re-initialized, re-installed, or re-registered when they are moved from one machine to another. It is also likely that you will not want to track every single box, sticker and serial number down from your software (this is an especially acute problem when your most recent Adobe product was an upgrade, and you can’t readily find the box for the original. This program scans your computer and shows you all registration codes and serial numbers.
  3. Contacts Cleaner. This is not imaging-related, but as you are getting your computing life in order in other ways, this will help rationalize, de-duplicate and generally improve the situations with your address book as stored on your iPhone and computer.

Migration advice: one advantage of using a dual USB/Thunderbolt device for your main storage is that you can consolidate all of your photos on that device. Your various SATA and Firewire drives’ data flows through your Mac Pro into the new box, which you then unplug from USB and plug into the new machine using Thunderbolt. Use Lightroom to effect the consolidation, and when you boot up your new machine, all you have to do (at most) is point Lightroom at the new mount point for your old drive.

As for the rest, expect some issues with Apple’s Migration Assistant. As noted above, losing product registrations is the big one. But also watch your permissions. The major reason to use Migration Assistant for your user directories is that it copies the unique identifiers to the new machine; it is a big trickier just to establish a user account on the new machine using your old user name. It is a very, very slow program.

In terms of how you move the data, it seems to be best to use the $29 Thunderbolt to Firewire 800 cable, with your old machine in target mode. Note that you may not be able to mount all drives in target mode, so think hard about other ways to migrate your big data collections on drives 3 and 4. If anyone tells you that Gigabit Ethernet is faster for these transfers, it is highly likely that he has not looked at the actual speeds that each protocol delivers. Firewire 800 on its worst day is better than gigE on its better days.

The bottom line: let’s not be indirect here – if you are replacing a pre-2013 Mac Pro, you can reasonably expect that making a meaningful improvement on its capabilities can easily hit around $5K total: about $3,200 for the machine; $300 for a secondary SSD drive; $150 for the extra RAM; 600 for primary storage; $500 (plus drives) for a NAS. It is still far less than buying a new Mac Pro with similar equipment, but wow. Once the credit card bills are paid, though, the Retina 5K is a great machine.