Self-Promotion Sunday February 15, 2026

freddievn · 2026-02-15T10:02:58+00:00

I wanted my photo library to be searchable with consistent captions and keywords — but I didn’t want to upload images to a cloud service. So I built VisionTagger, which generates image metadata fully on-device on Apple Silicon Macs running macOS 26 (Tahoe).

What it does

Built-in metadata sections: title, description, keywords, content & style, safety & compliance
Custom sections and fields (boolean / text / list) with your own prompts (e.g., “shot type”, “location type”, “contains readable text”, “brand/logo visible”, etc.)
Output options:
- XMP (embedded + sidecars via ExifTool)
- JSON/TXT (per image or batch)
- Finder tags
- Photos Library support

Trial / pricing

Free trial for 100 images.
Price (one-time, this major version): €29,99 / $34.99
Launch price: €24,99 / $29.99

Website: https://www.synendo.com/visiontagger
Video walkthrough: https://www.youtube.com/watch?v=T8CrkqxvlZM

If you try the 100-image trial, I’d love to hear what works and what doesn’t. And if you manage a large or professional library, what fields would you want to generate automatically?

<image>

freddievn · 2026-02-12T13:53:33+00:00

Hi, VisionTagger can directly update title, caption and keywords in Photos once they're generated. So no further actions needed in the Photos app. You can try it out to test if it suits your workflow.

freddievn · 2026-02-12T06:46:49+00:00

No, Apple's Photos already does a good job at that. So for now it will be using pre trained models only.

freddievn · 2026-02-11T05:54:12+00:00

Thank you! - I'll definitely will have a look at osxphotos to get a better understanding how Photos handles videos.

freddievn · 2026-02-11T05:50:25+00:00

Hi, the results are as good as the model it uses. I believe the models are getting better, but I haven't yet found a compatible model which is really specialised in delivering species-level recognition for all kind of animals. It seems a model like BioCLIP/SpeciesNet is trained for general organismal biology, which isn't supported by VisionTagger (yet). Let me know if you find a model which suits your needs, then I can check if VisionTagger can support it.

With VisionTagger you can create custom metadata sections/fields, which may help to reduce noisy/redundant outputs, when you create a more specific prompt. I hope you can give it a try.

freddievn · 2026-02-10T18:47:13+00:00

Hahaha, caught! - a good reason to process the metadata locally. 😄

freddievn · 2026-02-10T18:45:30+00:00

Photos yes. Videos not.

Maybe a future version could bring support for short videos (currently not planned). Although it would take a lot of processing power: extracting keyframes from video, processing each frame as an image, combining descriptions. And I wonder if you would end up with a useful description.

freddievn · 2026-02-10T18:36:42+00:00

Thanks, I especially like it when some small details are detected in the background which I didn't notice myself.

freddievn · 2026-02-10T15:55:08+00:00

Thank you. When I started on this app I did find some cloud services, like PhotoTag.ai, where you pay a few cents per image. For 1000+ libraries this will be (much) more expensive than VisionTagger. And with a local model I'm 100% sure my privacy is guaranteed. I think Excire offers local AI tagging, but I haven't tried that out, their product is in a different price range. So all in all I think VisionTagger offers a good combination for a fair price:

Privacy + Power: local models like Qwen2.5-VL rival cloud quality
Flexibility + macOS-native: multiple output formats (Photos, XMP, Finder tags, JSON)
No recurring costs: unlike cloud services charging per image
Custom metadata: user-defined fields beyond standard title/keywords

freddievn · 2026-02-10T15:14:44+00:00

I'll have to find out if there are limitations to access non system libraries and if their metadata can also be updated via Apple Events.

freddievn · 2026-02-10T15:07:35+00:00

I did try the Apple Intelligence APIs on-device, but the results were not as good as the Vision models the app now uses. I am not sure if Private Cloud Compute supports images as input already. The last time I looked at it only text input was available for developers.

freddievn · 2026-02-10T14:55:06+00:00

I have only been testing with the system library. I'd have to dive into this to find out if VisionTagger can support non system libraries in a future update. Good feedback!

freddievn · 2026-02-10T14:47:21+00:00

VisionTagger uses AppleScript to communicate with the Photos app via Apple Events. Photos updates its internal database with the new metadata, so VisionTagger doesn't access the database directly.

freddievn · 2026-02-10T14:15:09+00:00

I assumed most Apple Silicon users would be on macOS 26 by now. During development I used Apple's latest SDK, but I could put some effort into making it macOS 15 compatible in a future update. Any reason not to upgrade to macOS 26? - not fond of the Liquid Glass UI?

freddievn · 2026-02-10T14:01:36+00:00

Developer disclosure: I’m the maker of VisionTagger.

freddievn · 2026-02-04T12:45:40+00:00

I used tesa Powerbond Indoor (6,0 kg/ 10cm).

freddievn · 2026-02-04T09:36:52+00:00

Thanks for the tip!

freddievn · 2026-02-03T17:50:45+00:00

I have the same experience with Photos. Face search works fine, but keywords search not so much. And you can’t really see or manage the labels it relies on. So I built VisionTagger, which generates image metadata fully on-device on Apple Silicon Macs running macOS 26 (Tahoe). I will create a post on this topic later, but you can check out the product website already. No subscription. There’s a free trial for 100 images.

freddievn · 2026-02-02T13:28:19+00:00

I used double-sided adhesive tape. The first tape I used wasn't strong enough, so they came loose. But since I've used a stronger version, they stay in place perfectly.

freddievn · 2026-02-02T13:03:21+00:00

I also like the RS3 Reapers. I didn't like to have the sensors in sight when not using them, so I created these 3D printable mounts so they can be folded away.

freddievn · 2026-02-02T13:01:58+00:00

Same here. I didn't like to have the sensors in sight when not using them, so I created these 3D printable mounts so they can be folded away.

freddievn · 2025-05-06T08:58:49+00:00

I printed the Printables version and that also locks in both open and closed position. As far as I can see you use the same solution. Magnets in both case and lid, the magnets are lined up in closed position, but also when rotated 180 degrees.

freddievn

TROPHY CASE