Image Metadata & EXIF Extractor — Camera, GPS, Size

Point it at an image URL and get back everything the file knows about itself: dimensions and format, the camera and lens that took it, ISO / shutter / aperture / focal length, the capture date, and the GPS coordinates if they are still embedded.

No API key, no upload step, no account. $0.003 per image analysed — anything that is not a readable image is recorded and not charged.

The one people actually need: does this photo leak where it was taken?

Phone and camera photos carry GPS in EXIF, and most tools silently pass it through. Every record has a plain hasGps boolean, and when it is true you also get the coordinates and an openstreetmap.org link so you can see the location rather than decode a decimal.

Run it over a folder of images before they go on a website, a listing, or a profile.

Input

{ "url": "https://example.com/photo.jpg" }

Bulk:

{ "urls": ["https://example.com/a.jpg", "https://example.com/b.png"], "maxImages": 50 }

Field	Type	Notes
url	string	One direct image link.
urls	string[]	Up to 50 per run.
maxImages	integer	1–50, default 25.
includeRawExif	boolean	Adds every tag in the file, not just the common ones. Verbose; default false.

Supported: JPEG, PNG, WebP, GIF, TIFF, HEIC, AVIF, BMP and other common containers. EXIF itself exists mainly in JPEG/TIFF/HEIC.

Output

{
  "ok": true,
  "url": "https://example.com/photo.jpg",
  "format": "jpg",
  "width": 640,
  "height": 480,
  "megapixels": 0.31,
  "aspectRatio": "4:3",
  "bytes": 161713,
  "orientation": "Horizontal (normal)",
  "hasExif": true,
  "hasGps": true,
  "camera":  { "make": "NIKON", "model": "COOLPIX P6000", "lens": null, "software": "Nikon Transfer 1.1 W" },
  "capture": { "dateTaken": "2008-10-22T16:28:39.000Z", "iso": 64, "fNumber": 5.9,
               "exposureSeconds": 0.0133, "shutter": "1/75", "focalLengthMm": 24,
               "flash": "Flash did not fire, compulsory flash mode" },
  "gps": { "latitude": 43.4674, "longitude": 11.8851,
           "mapUrl": "https://www.openstreetmap.org/?mlat=43.4674&mlon=11.8851#map=15/43.4674/11.8851" }
}

What it gets right

• Dimensions come from the container, not from EXIF. Most web images have no EXIF at all — a PNG from a design tool, anything a social platform re-encoded. Those still return width, height, format and size, with hasExif: false. "No EXIF" is a true answer, not an error.
• Shutter speed is given both ways. EXIF stores 0.0133; every camera displays 1/75. You get exposureSeconds and shutter.
• Aspect ratio stays readable. 640×480 reduces to 4:3. An odd crop that would reduce to 3871:2579 is returned as 1.5:1 instead, because the exact fraction tells you nothing.
• orientation is EXIF's own label ("Horizontal (normal)"), not a number of degrees — the field is named so it cannot be mistaken for one.
• A non-image is honest about it. An HTML error page served at a .jpg URL produces ok: false with a reason, and is not charged.

Pricing

$0.003 per image analysed. No start fee. Failed fetches and non-images are recorded free.

Limits

• 50 images per run, 20 MB per image, 25 s fetch timeout each.
• Reads metadata only. It does not resize, convert, or strip EXIF — to convert formats see Image Converter.
• GPS is only present if the camera recorded it and nothing has stripped it since. Absence is not proof the photo has no location history.

FAQ

Do I need an API key? No.

Can it strip the GPS data it finds? No — this one reports. Stripping changes the file, which is a different job.

Are my images stored? The bytes are fetched, parsed in memory, and discarded. Only the metadata record goes to your own run's dataset.

Why does a photo from Instagram/Twitter show no EXIF? Those platforms re-encode uploads and drop metadata. That is the platform, not this Actor.

Changelog

• 0.1 (2026-09-10) — first release. Dimensions, format, camera, lens, exposure, capture date, GPS with map link, optional full raw EXIF block.

Who uses it

• Privacy reviewers checking whether user-uploaded photos still leak GPS coordinates
• Journalists and OSINT researchers reading capture date and camera model from images in a story
• Photographers auditing which lens and settings were used across a portfolio
• Marketplace moderators checking listing photos for capture dates that do not match the claim
• Developers reading image dimensions and format before deciding how to resize