Upload a photo.
No metadata needed.
AI finds the location.
Photo Location Finder
AI-powered location review from visual evidence. Upload an image and Oceanir reads the visual clues — architecture, road markings, signs, terrain — to estimate where it may have been taken. No GPS metadata required. Works on screenshots, messaging app images, and social media photos.
How the photo location finder works
Upload your photo
Drop any image into the interface. Street-level photos, dashcam frames, social media screenshots, and messaging app images all work. No GPS or EXIF metadata required — if the metadata was stripped, that is fine.
AI analyzes visual clues
The Orca engine reads geographic signals directly from the pixels: road markings, architectural style, signage, vegetation, terrain, and commercial context. It matches these signals against millions of geotagged reference images to estimate the location.
Review ranked results
You get ranked location candidates with confidence scores, interactive map evidence, and street-level comparisons. Results appear in under 30 seconds. You verify the match and make the final call.
What the AI analyzes in your photo
Architecture
Building materials, roof shapes, window proportions, and facade styles encode regional construction traditions. Colonial stone, Mediterranean stucco, Victorian brick — each narrows the search to a specific part of the world.
Road markings
Lane lines, crosswalk patterns, curb profiles, and road surface materials follow national and regional standards. A dashed yellow center line reads differently than a solid white one.
Signs and text
Traffic sign shapes, colors, fonts, and mounting styles follow country-specific standards. Street name formats, language on storefronts, and posted regulations provide direct geographic evidence.
Vegetation
Tree species, ground cover, soil color, and landscape patterns constrain latitude, climate zone, and biome. Palm trees narrow differently than birch forests. Red soil reads differently than grey asphalt.
Commercial signage
Store names, brand logos, advertising formats, and pricing currencies provide direct evidence of country, city, and sometimes the exact neighborhood where a photo was taken.
Utility infrastructure
Power line styles, pole designs, transformer placements, cable routing, and street lighting fixtures vary by country and utility provider. These background details are some of the most reliable geographic signals.
No metadata required
Every major social media platform — Instagram, Twitter/X, Facebook, WhatsApp, Signal, Telegram — strips EXIF and GPS metadata from photos on upload. That means traditional metadata-based image location finders return nothing for the vast majority of photos shared online.
Oceanir does not rely on EXIF data. The AI performs pure visual analysis: reading architectural styles, road marking conventions, signage languages, terrain features, vegetation patterns, and hundreds of other geographic signals embedded in the pixels themselves.
This makes visual analysis fundamentally more reliable than metadata extraction. Metadata can be stripped, spoofed, or absent. The geography in a photo cannot be removed — the roads, buildings, signs, and terrain are always there. Oceanir reads them directly, making it an effective image location finder even when every other method fails.
Supported regions
The photo location finder covers cities across the United States, United Kingdom, France, Portugal, Spain, and Nigeria. Coverage is densest in urban and suburban environments where visual infrastructure — road markings, signage, architectural patterns — provides the strongest geographic signals.
Beyond city-level coverage, the Orca Recall engine can estimate locations worldwide by matching visual features against millions of geotagged reference images. Rural areas and regions with less distinctive infrastructure may produce broader estimates (region or country level rather than street level).
Check where a photo may have been taken
Free to try. No credit card. Upload a photo and get location results in under 30 seconds.
Start analyzingCommon questions
Oceanir's photo location finder uses computer vision to analyze the visual content of an image — not its metadata. The AI reads road markings, architectural styles, signage, vegetation, terrain, and dozens of other geographic signals embedded in the pixels themselves. Social media platforms strip GPS and EXIF data on upload, so visual analysis is the only reliable method for most images shared online.
The photo location finder works best with outdoor images that contain visible infrastructure: streets, buildings, signs, storefronts, or distinctive terrain. JPG, PNG, and WebP formats are all supported. You can also extract a still frame from a video. Indoor photos, extreme close-ups, and nighttime shots with limited detail are harder to locate because they contain fewer geographic clues.
Oceanir's Orca 2.1 model achieves 32.2% accuracy at 1 km and 64.3% at 25 km on the Im2GPS3k benchmark — the highest published scores among visual geolocation systems. Accuracy varies based on the visual richness of the image and the density of reference data in that region.
Yes. Free to try, no credit card required. Each image analysis uses one credit. API access has no monthly fee and uses prepaid credits. Paid plans include Starter for occasional D3, Pro for individual verification workflows, Unit for shared workspaces, and sales-led Agency and Enterprise plans.
Yes. Screenshots, re-saved images, and compressed photos all work. Metadata is destroyed by these processes, but the geographic signals in the image — road styles, architecture, vegetation — survive compression and re-encoding. Oceanir reads the scene, not the file metadata.
Oceanir covers 103+ cities across the United States, United Kingdom, France, Portugal, Spain, and Nigeria, with additional global coverage through its Orca Recall engine. The model performs best in urban and suburban environments with dense visual infrastructure.