Baselight

4K Benchmark Images

High-resolution street-view images across 6 continents for evaluating image-base

@kaggle.jameswicker5_4k_benchmark_images

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About this Dataset

4K Benchmark Images

The 4K Global Geolocation Benchmark is a curated dataset of 4,000+ street-view images collected from diverse locations around the world, designed to evaluate the performance of AI models in predicting geographic coordinates from visual input alone.

๐Ÿ“Œ Key Features:

๐ŸŒ Global Coverage: Images sampled across 6 continents (excluding Antarctica)

๐Ÿ“ท Street-Level Perspective: Ideal for visual geolocation tasks using VLMs like CLIP, BLIP-2, LLaVA, and GeoCLIP

๐Ÿ“ Embedded Coordinates: Latitude and longitude are encoded in the filenames for easy parsing

๐Ÿงช Benchmark-Ready: Widely used to evaluate models like GPT-4o, Claude 4, and other multimodal geolocation systems

This dataset has been used in various projects and academic benchmarks to test zero-shot, few-shot, and prompt-based geolocation reasoning. It's ideal for:

Vision-language geolocation research

Haversine error evaluation and distance scoring

GeoGuessr-style model training and inference

๐Ÿ’ก Use alongside language models or embeddings to predict location from scene content such as architecture, vegetation, road signs, and climate.

Tables

Balanced 4000 Image Subset

@kaggle.jameswicker5_4k_benchmark_images.balanced_4000_image_subset
  • 422.67 KB
  • 4002 rows
  • 6 columns
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CREATE TABLE balanced_4000_image_subset (
  "image_name" VARCHAR,
  "lat" DOUBLE,
  "lon" DOUBLE,
  "folder_path" VARCHAR,
  "continent" VARCHAR,
  "full_path" VARCHAR
);

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