GalleryID puts athlete names into sports photos so the archive stays searchable.
Caption with the press of a button or a shortcode from your roster, and speed it up with MatchID, our facial recognition built for the toughest environment in photography: sports. The names are written to each file.
14-day free trial · Unlimited MatchID on all plans · No per-image fees
It turns a folder of photos into an archive you can search by athlete.
CaptionID writes the athlete's name and the full caption line from a bound roster in one press. No headshots needed, just a roster from the built-in Roster Library, a file you import, or one you build yourself.
See the Roster Library →MatchID is facial recognition built for sports, where helmets and motion break ordinary tools. Drop in headshots to index a team, and jersey numbers are read during indexing. Unlimited on all plans.
How MatchID works →Names are written to the file's XMP and IPTC metadata, so photos stay searchable anywhere you send them. They read in Photo Mechanic, Lightroom, Capture One, or any program that reads metadata. Nothing depends on GalleryID still being there.
Sports photo captioning, in full →Pick the one that fits your workflow, or run both across a season.
GalleryID Desktop captions and delivers from your own computer, and nothing gets uploaded.
You keep your tools. You lose the busywork. The names write to the file, so they show up in your editing software on their own.
Upload the finals, MatchID names them, and the whole program works from the same archive.
Search their name, get their career. Comms, creative and social all work from the same named archive, mid-season.
From 200 GB, priced by storage. Storage is the only line item, so pricing doesn't need a phone call.
See Cloud pricing →Or $200/yr. Two computers on one subscription, so the laptop at the game and the desktop at home are both covered. Cancel any time before the trial bills.
See Desktop pricing →Unlimited users on all plans, because charging per seat punishes you for adding staff.
MatchID is GalleryID’s facial recognition, tuned for sports action. Consumer facial recognition is trained on people looking at the camera; MatchID was trained on sports photography, where athletes are in motion, turned away, or wearing helmets, with jersey numbers read as a second signal. It accelerates the one-press tagging you can already do from a roster, and matches it isn’t sure about wait in a review queue for your click. Because it was trained on the hardest conditions in photography, everything easier is covered too.
Yes for MatchID, no for everything else. MatchID is facial recognition, so it needs indexed headshots to match against. Without headshots you can still add names to photos quickly by tagging from a roster with CaptionID, using a button press or a shortcode. The name and the full caption line write to the metadata together.
Two ways. Upload your own roster file, or pull one from the roster feed, which covers NCAA Division I, II and III and ten pro leagues. Either way you tag and caption manually from it with a button press or a shortcode, and no headshots are involved. A roster binds to a folder, so you’re tagging against the right team without picking it each time.
Both caption athletes and write the names to each file. Desktop runs on your Mac or PC and is built to name your files locally and deliver them. Cloud is the hosted, searchable archive: upload the finals, search by athlete, and deliver through galleries, share links, and the store. Many photographers run both, and a photo named in Desktop carries its names into Cloud.
No. MatchID is unlimited on all plans. There aren’t any credits, per-image fees, or add-ons to unlock, so you can run it across a full gallery without watching a meter. On GalleryID Cloud, storage is the only line item. On GalleryID Desktop, one price covers two computers.
Yes. GalleryID Cloud includes unlimited users on all plans, because charging per seat punishes you for adding staff. Communications, creative and social can work from the same named archive while the season is still going, and folder permissions and groups control who sees what. GalleryID Desktop is one subscription that covers two computers.
It can, but it doesn’t have to. Names and captions write to the file in standard XMP and IPTC metadata, so they read wherever the file goes next, in any program that reads metadata, including GalleryID Desktop, Photo Mechanic, Lightroom, and Capture One. Your existing code sets keep working too. No forced switch.
Yes. MatchID reads the visible faces and reads the jersey numbers, so helmet sports are covered. Helmets can obstruct the face, and camera angles and lighting can reduce effectiveness, so uncertain matches wait in the review queue.
Because review is part of the job, and the queue is built to make it fast. Auto-tag applies only above the confidence threshold, and even a correct match deserves a look: you decide who belongs in the delivery. Most photographers caption in the same pass. The queue speeds up review and captioning; it doesn’t replace the need for them.
The work does. Photos never leave your computer, captioning runs locally, and MatchID indexes and matches against headshots on your own machine. The Catalog indexes whole drives, so you can browse and search that archive by name with the drives unplugged. The license does check in periodically, so the app isn’t built to run disconnected indefinitely.
The names are already in your files, so anything you’ve downloaded or delivered keeps them. They’re written in standard XMP and IPTC metadata, which reads in any program that reads metadata, so nothing is trapped in GalleryID. For GalleryID Cloud, cancelling starts a 30 day grace period where you keep full access to reactivate or export your archive. The specifics are in our terms.
Yes. Both Cloud and Desktop offer a 14-day free trial with a card on file. Cloud starts at $20/mo for 200 GB. Desktop is $20/mo or $200/yr, two computers included.
Working sports photographers, on the same deadline you are. GalleryID came out of years on the sidelines and years alongside teams, schools and athletic departments, watching the same problems show up season after season. We trained our own model because off-the-shelf facial recognition doesn’t work well for sports, and anything the model isn’t sure about waits in a review queue rather than getting guessed at.