We are seeking to develop an advanced API that can analyze images and deduce their geographical location. This API would employ a combination of techniques:

• EXIF Data Analysis: Initially, the API would examine the EXIF data of the image for GPS coordinates. If available, this would provide the most accurate location information. But still needed to be verified (indoors vs outdoors)
• AI and External APIs for Location Recognition: In cases where EXIF data is lacking or incomplete, the API would use AI to analyze visual cues in the image. It would cross-reference these cues with known locations from databases like Google Street View api, Openai Clip or CogVLM? This approach could identify specific landmarks, architectural styles, or other unique features that pinpoint a location.
• Natural Feature Analysis: If the above methods are insufficient, the API would analyze natural features in the image, such as vegetation, tree types, or geological formations, to make educated guesses about the region or climate zone depicted.
• Output with Accuracy Estimation: The API would provide the estimated latitude and longitude of the image’s location, along with a confidence score and an explanation for its conclusion (e.g., "EXIF data: 100% accuracy" or "Architectural style suggests Rome, Italy: 70% accuracy").

Two other APIs just released similar functionality (we can share if interested and overview how they work with ) here is an overview of how one of them works: https://www.digitaldigging.org/p/the-dawn-of-ai-powered-geolocation
• CLIP is good option, but would training CogVLM on Google Street View be better?

Open to suggestions, but looking to build this now. Thanks

Posted On: January 22, 2024 21:14 UTC
Category: AI Integration
Skills:API

Country: United States

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