How accurate is GeoAxis at finding image locations?

GeoAxis provides meter-level accuracy using advanced AI algorithms. Our HyperVision™ technology achieves within 10-meter accuracy and works even with challenging images including low-light, low-resolution, and partial views.

Does GeoAxis need GPS or EXIF data to find the location of an image?

No. GeoAxis uses AI-powered visual analysis to determine the location of any image — no GPS metadata or EXIF data required. Our AI analyzes landmarks, terrain, vegetation, architecture, and other visual cues to pinpoint where a photo was taken.

How fast can GeoAxis find an image location?

GeoAxis delivers results in seconds. Simply upload any image and our AI instantly analyzes it to identify the precise location — no manual work or technical expertise needed.

What is HyperVision™ technology?

HyperVision™ is GeoAxis's enterprise-grade AI image location intelligence platform offering custom city deployments, enhanced accuracy within 10 meters, and priority support for mission-critical applications.

v1.0 — api.geoaxis.ai

Documentation

Geolocate any image with a single API call. Upload a photo, get GPS coordinates back.

pip install pygeoaxis

Getting Started

The GeoAxis API lets you upload any image and get back its geographic location. Two search modes are available:

Global Search

AI analyzes visual clues to locate the image anywhere in the world.

City Search

Matches against a city's indexed database — fast, sub-300ms results.

Base URL: https://api.geoaxis.ai

Installation

Install the official Python wrapper from PyPI:

terminal

pip install pygeoaxis

Or use the API directly with any HTTP client — requests, fetch, curl, etc. No SDK required.

Python SDK Usage

python

from pygeoaxis import GeoAxis

# Initialize with your API key
client = GeoAxis(token="<your_api_key>")

# The SDK wraps the REST API — see below for endpoints

Requirements

Python 3.6+
A GeoAxis account with an active Pro or Business subscription
Your API key (from Dashboard → Settings)

Authentication

All protected endpoints require your API key in the Authorization header:

Authorization: Bearer <your_api_key>

Getting Your API Key

Sign in at geoaxis.ai/login
Subscribe to a Pro or Business plan at geoaxis.ai/pricing
Open your Dashboard
Click your avatar (bottom-left) → "API Key"
Click "Reveal" to see your key, then "Copy"

Using Your Key

python

import requests

API_KEY = "<your_api_key>"

# Pass in every request:
headers = {"Authorization": f"Bearer {API_KEY}"}

javascript

const API_KEY = "<your_api_key>";

// Pass in every request:
headers: { "Authorization": `Bearer ${API_KEY}` }

Keep your key secret. Never expose it in client-side code or public repositories.

Quick Start

Geolocate an image in 4 lines of Python:

python

import requests, base64

API_KEY = "<your_api_key>"
image = base64.b64encode(open("photo.jpg", "rb").read()).decode()

res = requests.post(
    "https://api.geoaxis.ai/api/search",
    headers={"Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json"},
    json={"image_base64": image, "global": True}
)

loc = res.json()["location"]
print(f"{loc['location_name']}, {loc['country']}")
print(f"Coordinates: ({loc['lat']}, {loc['lng']})")
print(f"Confidence: {loc['confidence']:.0%}")

output

Paris, France
Coordinates: (48.8566, 2.3522)
Confidence: 85%

POST /api/search — Global

Search anywhere in the world. Our AI analyzes visual clues — signs, architecture, vegetation, terrain — to predict the location.

Parameter	Type	Required	Description
image	file	Yes	Image file (multipart upload)
global	string	Yes	Must be "true"
context	string	No	Hint to narrow search, e.g. "somewhere in Europe"

Python (file upload)

python

import requests

res = requests.post(
    "https://api.geoaxis.ai/api/search",
    headers={"Authorization": f"Bearer {API_KEY}"},
    files={"image": open("photo.jpg", "rb")},
    data={"global": "true", "context": "looks like Southeast Asia"},
)

loc = res.json()["location"]
print(f"{loc['location_name']}, {loc['country']}")
print(f"({loc['lat']}, {loc['lng']}) ± {loc['radius_km']}km")
print(f"Confidence: {loc['confidence']:.0%}")
print(f"Analysis: {loc['analysis_summary']}")
print(f"Key clues: {', '.join(loc['key_indicators'])}")

JavaScript

javascript

const formData = new FormData();
formData.append("image", fileInput.files[0]);
formData.append("global", "true");
formData.append("context", "European city");

const res = await fetch("https://api.geoaxis.ai/api/search", {
  method: "POST",
  headers: { "Authorization": `Bearer ${API_KEY}` },
  body: formData,
});

const { location } = await res.json();
console.log(`${location.location_name}, ${location.country}`);
console.log(`Confidence: ${(location.confidence * 100).toFixed(0)}%`);

Response

json

{
  "success": true,
  "search_type": "global",
  "location": {
    "lat": 48.8566,
    "lng": 2.3522,
    "radius_km": 5.0,
    "radius_meters": 5000,
    "confidence": 0.85,
    "location_name": "Paris",
    "country": "France",
    "analysis_summary": "Eiffel Tower visible, Haussmann architecture...",
    "key_indicators": ["Eiffel Tower", "French street signs", "Haussmann buildings"]
  }
}

POST /api/search — City

Search against a specific city's indexed database for fast, precise matching — sub-300ms response times.

Parameter	Type	Required	Description
image	file	Yes	Image file (multipart upload)
city_path	string	Yes	City index path, e.g. "US/Texas/Dallas"
k	integer	No	Number of results (default: 10)

Python

python

import requests

res = requests.post(
    "https://api.geoaxis.ai/api/search",
    headers={"Authorization": f"Bearer {API_KEY}"},
    files={"image": ("photo.jpg", open("photo.jpg", "rb"), "image/jpeg")},
    data={"city_path": "US/Texas/Dallas", "k": "5"},
)

data = res.json()
for r in data["results"]:
    print(f"  lat={r['lat']}, lng={r['lng']}, score={r['score']}")

Response

json

{
  "success": true,
  "search_type": "city",
  "city_path": "US/Texas/Dallas",
  "results": [
    { "lat": 32.7767, "lng": -96.7970, "score": 0.95 },
    { "lat": 32.7800, "lng": -96.8010, "score": 0.89 }
  ],
  "total": 2,
  "timing": {
    "feature_extraction_ms": 245.3,
    "index_search_ms": 18.7,
    "total_ms": 264.0
  }
}

GET /api/locations

List all available indexed cities you can search against. Use this to populate a city selector in your UI.

bash

curl https://api.geoaxis.ai/api/locations \
  -H "Authorization: Bearer <your_api_key>"

python

res = requests.get(
    "https://api.geoaxis.ai/api/locations",
    headers={"Authorization": f"Bearer {API_KEY}"},
)
cities = res.json()["locations"]
for city in cities:
    print(city["path"])  # e.g. "US/Texas/Dallas"

GET /api/health

Check if the server is ready. No authentication required.

bash

curl https://api.geoaxis.ai/api/health

json

{
  "status": "ok",
  "model_loaded": true,
  "device": "cuda",
  "indexes_loaded": 17,
  "total_vectors": 95640224,
  "queue": { "queue_length": 0, "active": 0, "total_processed": 5678 }
}

Base64 JSON Mode

Instead of multipart file upload, you can send the image as a base64-encoded string in a JSON body. This is useful when you already have the image in memory or as a data URI.

Parameter	Type	Required	Description
image_base64	string	Yes	Base64-encoded image (raw or data URI)
format	string	No	Image format: jpg, png, webp (default: jpg)
global	boolean	No	true for global search
city_path	string	No*	Required if global is not true
context	string	No	Hint for global search
k	integer	No	Number of results (default: 10)

Python

python

import requests, base64

image_b64 = base64.b64encode(open("photo.jpg", "rb").read()).decode()

# Global search
res = requests.post(
    "https://api.geoaxis.ai/api/search",
    headers={
        "Authorization": f"Bearer {API_KEY}",
        "Content-Type": "application/json",
    },
    json={
        "image_base64": image_b64,
        "format": "jpg",
        "global": True,
        "context": "somewhere in Asia",
    },
)
print(res.json()["location"])

JavaScript (Browser)

javascript

// Convert file input to base64 and send as JSON
const file = fileInput.files[0];
const reader = new FileReader();

reader.onload = async () => {
  const res = await fetch("https://api.geoaxis.ai/api/search", {
    method: "POST",
    headers: {
      "Authorization": `Bearer ${API_KEY}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({
      image_base64: reader.result,  // data:image/jpeg;base64,... works
      global: true,
    }),
  });
  const { location } = await res.json();
  console.log(location);
};

reader.readAsDataURL(file);

Node.js

javascript

const fs = require("fs");

const imageBase64 = fs.readFileSync("photo.jpg").toString("base64");

const res = await fetch("https://api.geoaxis.ai/api/search", {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${API_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    image_base64: imageBase64,
    format: "jpg",
    city_path: "US/Texas/Dallas",
    k: 5,
  }),
});
console.log(await res.json());

Rate Limits

Requests per user	1 every 10 seconds
Max image size	16 MB
Accepted formats	PNG, JPG, JPEG, HEIC, BMP, WebP
Max queue depth	50 concurrent requests

When rate limited you receive 429:

json

{ "error": "Rate limited. Try again in 7s.", "retry_after": 8 }

Error Codes

Code	Meaning	When
400	Bad Request	Missing image, invalid format, missing city_path
401	Unauthorized	Missing or invalid API key
403	Forbidden	No active subscription
404	Not Found	City not indexed
413	Too Large	Image exceeds 16 MB
429	Rate Limited	> 1 request per 10s
503	Unavailable	Model loading or queue full (50 max)

cURL Examples

bash

# Health check (no auth)
curl https://api.geoaxis.ai/api/health

# List available cities
curl https://api.geoaxis.ai/api/locations \
  -H "Authorization: Bearer <your_api_key>"

# Global search (file upload)
curl -X POST https://api.geoaxis.ai/api/search \
  -H "Authorization: Bearer <your_api_key>" \
  -F "image=@photo.jpg" \
  -F "global=true" \
  -F "context=European city"

# City search (file upload)
curl -X POST https://api.geoaxis.ai/api/search \
  -H "Authorization: Bearer <your_api_key>" \
  -F "image=@photo.jpg" \
  -F "city_path=US/Texas/Dallas" \
  -F "k=10"

# Global search (base64 JSON)
curl -X POST https://api.geoaxis.ai/api/search \
  -H "Authorization: Bearer <your_api_key>" \
  -H "Content-Type: application/json" \
  -d "{
    \"image_base64\": \"$(base64 -w0 photo.jpg)\",
    \"global\": true,
    \"context\": \"somewhere in Europe\"
  }"

Need help? contact@geoaxis.ai

pygeoaxis on PyPI · GitHub

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AI-powered image location intelligence with HyperVision™ technology

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