pixelpeeper.com

PixelPeeper reads Lightroom edits in two different ways depending on what the file contains. If the photo still has its embedded XMP metadata, PixelPeeper recovers the actual saved adjustments — exposure, contrast, highlights, shadows, tone curve, and color mixer values — and can export them as an XMP preset. If that metadata is missing, it falls back to Look Match, a machine-learning estimate based on how the photo looks. The first path gives you real settings; the second gives you a starting point, not a recovery.

The two paths, side by side

The distinction matters because only one of these tells you what the photographer actually did.

Path 1: Recovering embedded edits

When a photo contains Lightroom metadata, PixelPeeper surfaces the saved adjustments rather than guessing. The sample photos on the site show what this looks like in practice — for example, a Sony ILCE-7M2 shot at 55.0 mm, f/2.0, 1/100, ISO 200 with embedded edits of Exposure +0.40, Contrast 0, Highlights 0, Shadows 0, and color mixer values of Red −10, Green +26, Blue +13.

The reported items include:

• Camera settings — body, focal length, aperture, shutter speed, ISO
• Lightroom edits — Exposure, Contrast, Highlights, Shadows
• Tone curve — RGB curve adjustments
• Color mixer — Hue shifts per color channel (Red, Orange, Green, Blue)

You can open a full inspector for each photo and download the settings as an XMP preset to load into Lightroom and explore yourself.

Why the metadata is there in the first place

Lightroom can write your adjustments into the exported file's XMP data. When that happens, the edit information travels with the image. PixelPeeper reads from that embedded XMP data — it isn't reverse-engineering the pixels to find your sliders. This is why the recovered values are exact when present, and why they're simply unavailable when the export stripped or omitted that data.

Path 2: Look Match when edits are missing

Not every photo carries edit metadata. When it doesn't, PixelPeeper offers Look Match: a custom machine-learning model that suggests Lightroom adjustments based on the photo's appearance.

Two things to keep in mind:

• These are estimates, not recovered settings. The model is inferring a plausible set of adjustments from the visual result.
• Results vary by photo. A clean, well-lit image may yield a more usable starting point than a heavily stylized or low-quality one.

Treat Look Match as a way to explore a similar look, not as a claim about what the original photographer did.

Using PixelPeeper with an AI assistant

PixelPeeper can be connected to Claude or ChatGPT. In the example conversation shown on the site, a user asks the assistant to show how a photo was edited; the assistant calls PixelPeeper and returns a photo report covering camera settings, Lightroom edits, and a color palette, then explains that the soft, matte look comes largely from the tone curve and selective color adjustments — lifted blacks and airy highlights, with the curve lifting the black point from 0 to 50.

This is useful when you want the settings interpreted in plain language rather than just listed.

What to check before trusting a result

• Did the file keep its edit metadata? If yes, you're seeing recovered settings. If no, you're seeing a Look Match estimate.
• Does the photo match your intent? Look Match estimates are appearance-based, so a similar-looking photo with different underlying edits can produce different suggestions.
• Do you need the preset or just the idea? Embedded edits can be downloaded as an XMP preset; Look Match gives you adjustments to try, not a recovered file.

PixelPeeper Premium is listed at $49 for 12 months, with no automatic renewal.

PixelPeeper can be connected to Claude or ChatGPT so you can ask about a photo's camera settings and embedded Lightroom edits in plain language, then get a report covering camera settings, Lightroom edits, and a color palette. This works best when the photo actually contains embedded XMP edit metadata — if it doesn't, PixelPeeper's Look Match estimate is the fallback, and you should treat those results as suggestions rather than recovered settings.

What the connection actually gives you

Once PixelPeeper is connected to your AI assistant, the assistant can call it on your behalf. According to PixelPeeper's own example conversation, the flow looks like this:

• You ask something like "Use PixelPeeper to show me how this photo was edited."
• The assistant calls PixelPeeper, which returns a photo report.
• The report contains camera settings, Lightroom edits, and a color palette, with a link to explore the photo's settings in more detail.

In the sample exchange, the assistant explains that a soft, matte look "comes largely from the tone curve and selective color adjustments" — lifted blacks, airy highlights — and notes the curve lifts the black point from 0 to 50. That level of explanation is the point: you're not just reading numbers, you're getting the reasoning behind the look.

Step-by-step: connecting and using it

1. Open PixelPeeper's AI connection option. The site has a "Connect your AI assistant" entry point under its "Use PixelPeeper with your AI tools" section. Use that to start the connection.
2. Connect Claude or ChatGPT. PixelPeeper states it can be brought into either assistant. Follow the connection flow from that page.
3. Give the assistant a photo to analyze. Ask it to use PixelPeeper on a specific image — for example, "Use PixelPeeper to show me how this photo was edited."
4. Read the photo report. You should get camera settings, Lightroom edits, and a color palette, plus a link to explore the settings further.
5. Ask follow-up questions. Because the assistant has the report, you can ask how a specific look was achieved, or how to try similar edits on your own photos.

Expected result: a plain-language explanation tied to real values from the file (for example, exposure, contrast, tone curve, and color mixer hue shifts), not a generic editing lecture.

What you can ask once connected

PixelPeeper lists three intended uses for the AI connection:

• Ask how a specific look was achieved.
• Understand the camera settings and embedded Lightroom edits behind a photo.
• Explore how to try similar edits on your own photos.

A useful follow-up pattern is to take one reported adjustment and ask for a starting point on your own image — for instance, if the report shows a lifted black point and reduced highlights, ask what to change first in your own edit.

Embedded edits vs. Look Match: know which one you're getting

This distinction matters when you're interpreting the AI's answer.

If the assistant reports real adjustment values, the photo had embedded metadata. If it describes a suggested look instead, you're in Look Match territory — useful for inspiration, but don't treat it as what the photographer actually did.

Common snags

• No edits in the file. If the photo has no embedded Lightroom metadata, there's nothing to recover. PixelPeeper's own guidance is to try Look Match in that case, and to expect variation between photos.
• Expecting exact recovery from Look Match. PixelPeeper explicitly labels these as estimates. If you need the real settings, you need a file that carries them.
• Skipping the follow-up. The report is a starting point. The value comes from asking the assistant to explain or adapt what it found.

Cost and access

PixelPeeper Premium is listed at $49 for 12 months, with no automatic renewal. The site's description does not state whether the AI assistant connection requires Premium, so check the connection page itself before assuming it's included in a free tier.

PixelPeeper Premium costs $49 for 12 months, and it does not renew automatically. That single fact answers the two most common questions about the plan: the price is a one-time annual charge, and you won't be billed again when the year ends unless you choose to buy it again. Whether it's worth it depends on how often you inspect photos, export XMP presets, or use Look Match — the free parts of the site may already cover occasional use.

What PixelPeeper does

PixelPeeper reads the story behind a photo. Its core promise is "See the settings behind the photo," and it works on two levels:

• Camera settings — focal length, aperture, shutter speed, and ISO. The site's own samples show this plainly, e.g. a Sony ILCE-7M2 shot at 55.0 mm · f/2.0 · 1/100 · ISO 200.
• Embedded Lightroom edits — when a photo's file contains Lightroom metadata, PixelPeeper recovers the saved adjustments, from exposure and contrast to tone curves and color mixer values. You can then download those settings as an XMP preset to open in Lightroom.

The sample data on the site shows what "recovered" edits look like in practice: one photo carries Exposure +0.40, Contrast 0, and color mixer values like Green +26 and Blue +13; another shows Exposure -0.45, Contrast +7, Highlights -25, Shadows +33. These are read from the photo's embedded XMP data — not guessed.

Embedded edits vs. Look Match

This distinction matters most when deciding whether you need Premium, because it tells you what the tool can and cannot do.

If a photo has no edit metadata in the file, PixelPeeper offers Look Match as a starting point for exploring a similar look. The site is explicit that these are estimates and that results vary — so treat Look Match as inspiration, not a reconstruction of what the original photographer did.

Using PixelPeeper with AI assistants

PixelPeeper can be connected to Claude or ChatGPT. In the example conversation shown on the site, a user asks the assistant to show how a photo was edited; the assistant uses PixelPeeper and returns a report covering camera settings, Lightroom edits, and a color palette, then explains that the soft, matte look comes largely from the tone curve and selective color adjustments — lifted blacks and airy highlights, with the curve lifting the black point from 0 to 50.

This is a workflow point rather than a pricing point, but it's relevant to value: if you already work inside an AI assistant, connecting PixelPeeper lets you ask about a look in plain language instead of reading raw adjustment values yourself.

Who the $49 plan suits

The plan is a reasonable fit if you:

• Inspect photos regularly enough that per-use limits or missing features would interrupt your workflow
• Want to download XMP presets from recovered Lightroom edits and study them in Lightroom
• Rely on Look Match for photos that carry no edit metadata
• Want PixelPeeper available inside Claude or ChatGPT as part of your research process

It's probably not necessary if you only occasionally want to check a camera's settings or look at one photo's edits. The site exposes camera settings and embedded Lightroom edits in its samples and full inspector views, so start there and see whether the free experience answers your actual questions before paying.

How the billing works

• Price: $49 for 12 months.
• Renewal: No automatic renewal. The plan does not auto-charge when the term ends.
• What that means practically: You pay once for a year of access. If you want another year, you buy again; if you don't, nothing happens to your payment method.

Because there's no auto-renewal, the usual "cancel before the renewal date" concern doesn't apply — there's no recurring charge to cancel. The trade-off is the reverse: if you want to keep access, you have to remember to repurchase rather than relying on a subscription to continue.

A quick way to decide

1. Open a few photos you care about and check whether they show embedded Lightroom edits or only camera settings.
2. If the photos you study usually carry edit metadata, test whether the recovered adjustments and XMP export are useful to you.
3. If they usually don't, try Look Match and judge whether the estimates are close enough to be a useful starting point.
4. If either path is something you'd use repeatedly over the next 12 months, $49 with no auto-renewal is a low-commitment way to get full access. If not, the free views are likely enough.

Look Match is PixelPeeper's fallback feature for photos that don't contain embedded Lightroom edit metadata. Instead of reading saved adjustments out of the file, it uses a custom machine-learning model to suggest Lightroom adjustments based on how the photo looks. The key thing to understand before using it: Look Match returns estimates, not recovered settings, and results vary by photo. Use it when you want a starting point for exploring a similar look, not when you need the photographer's actual edit values.

How Look Match differs from embedded metadata

PixelPeeper has two ways of telling you how a photo was edited, and they are not interchangeable.

The embedded path is the reliable one. PixelPeeper's own examples show what that looks like in practice — for instance a Sony ILCE-7M2 shot at 55.0 mm, f/2.0, 1/100, ISO 200 with embedded edits of Exposure +0.40, Contrast 0, and color mixer hue shifts of Red -10, Green +26, Blue +13. Those numbers came out of the file. Look Match numbers do not.

When to use Look Match

Reach for Look Match in these situations:

• The photo has no Lightroom edits in the file. This is the primary trigger. PixelPeeper states plainly: "No edits in the file? Try a Look Match."
• You're reverse-engineering a look, not a preset. If you want to understand why an image feels soft, matte, or airy, Look Match gives you a direction to experiment in.
• You're working with a JPEG or an export that stripped the edit data. Once metadata is gone, embedded recovery isn't possible, and estimation is the only remaining option.
• You want a starting point before editing your own photos. The suggested adjustments are meant to be explored and adapted, not applied blindly.

When not to use it

Skip Look Match if any of the following applies:

• You need the photographer's real settings. Look Match cannot recover what isn't there. If the file has embedded XMP, use the embedded inspector instead — it's the accurate path.
• You're comparing two photos and need consistent, reproducible numbers. Estimates vary by photo, so they aren't a stable basis for comparison.
• You plan to publish the values as fact. They are suggestions, and PixelPeeper labels them as such.

What you actually get and what to do with it

Look Match outputs suggested Lightroom adjustments — exposure, contrast, tone curve, color mixer style values — based on the model's read of the image. Treat the output as a hypothesis:

1. Open the photo in PixelPeeper and check whether embedded Lightroom edits are present.
2. If they are, use the embedded inspector and download the settings as an XMP preset.
3. If they aren't, run Look Match and read the suggested adjustments.
4. Apply them in Lightroom as a starting point, then adjust to taste against your own image.
5. Expect variation — a different photo of a similar scene may produce different suggestions.

A note on the AI assistant route

PixelPeeper can also be connected to Claude or ChatGPT, which lets you ask how a specific look was achieved and get the camera settings, embedded Lightroom edits, and color palette in one report. That route is most useful when embedded metadata exists, since the assistant is reporting on what's in the file. When metadata is missing, the assistant is working from the same estimation logic as Look Match, so the same caveat applies: estimates, not recovered settings.

Bottom line

Use Look Match when a photo has no embedded Lightroom edits and you want an informed starting point for a similar look. Use the embedded metadata inspector when the edits are actually in the file and you need the real values. The two features answer different questions, and only one of them can tell you what the photographer actually did.

PixelPeeper is a web tool that reads the camera settings and embedded Lightroom edits stored inside a photo file, so you can see how an image was shot and edited. It works best when the photo still contains its original XMP metadata. If that metadata is missing, PixelPeeper offers a Look Match estimate as a starting point instead of recovered settings.

What PixelPeeper reads from a photo

When a photo contains embedded Lightroom metadata, PixelPeeper surfaces the saved adjustments rather than guessing. Based on the site's samples, the inspector can show:

• Camera settings — camera model, focal length, aperture, shutter speed, and ISO (for example: Sony ILCE-7M2, 55.0 mm, f/2.0, 1/100, ISO 200).
• Lightroom edits — Exposure, Contrast, Highlights, Shadows.
• Tone curve — the RGB curve, including lifted black points.
• Color mixer — Hue adjustments per color channel (Red, Orange, Green, Blue).

Each sample links to a full inspector, so you can open a photo and see the complete breakdown rather than a summary.

The two ways it handles a photo

The distinction matters: embedded metadata is recovered from the file, while Look Match is an estimate. PixelPeeper states plainly that Look Match results are estimates, not recovered settings, and that results vary by photo.

Turning what you find into a preset

If PixelPeeper reads embedded Lightroom edits, you can download those settings as an XMP preset and open it in Lightroom to explore on your own images. This is the main path from "how was this edited?" to "let me try it myself."

For Look Match results, treat the output as a starting point for a similar look rather than a faithful copy of the original edit.

Using PixelPeeper with AI assistants

PixelPeeper can be connected to Claude or ChatGPT. In that setup you can ask how a specific look was achieved, have the assistant pull the camera settings and embedded Lightroom edits behind a photo, or explore how to try similar edits on your own shots. The site shows an example conversation where the assistant returns a photo report covering camera settings, Lightroom edits, and a color palette.

Pricing

PixelPeeper Premium is listed at $49 for 12 months, with no automatic renewal. The site does not state that the core inspection features are free, so check what the free experience covers before relying on it for regular use.

When PixelPeeper is the right tool

• You found a photo whose look you want to understand and the file still has its Lightroom metadata.
• You want a concrete, exportable preset rather than a visual guess.
• You are comparing several photos and want to see how their edits differ across exposure, tone curve, and color mixer values.

If the photo has been stripped of metadata (common after export or social media upload), expect Look Match estimates instead of exact settings, and plan to refine them by eye.