Roboflow Universe API
Overview
Roboflow Universe gives you access to thousands of pre-trained computer vision models and datasets through a simple REST API. You can use it to run object detection, image classification, and segmentation on your own images without training a model from scratch. It is ideal for beginners who want to add AI vision capabilities to their apps quickly.
Beginner Tip
Start by browsing Roboflow Universe at universe.roboflow.com to find a model trained on your target objects — using a pre-trained model saves days of work. Always send images as base64-encoded strings or URLs, and check the model version number in your API calls.
Available Data
Example Response
{
"route": "Line 1",
"origin": "Station A",
"destination": "Station B",
"departure": "08:30",
"arrival": "09:15",
"status": "On Time",
"delays_min": 0
} Field Reference
predictions List of detected objects, each with class label and bounding box. predictions[].class The label of the detected object (e.g., cat, car). predictions[].confidence Detection confidence score from 0 to 1; higher means more certain. predictions[].x X-coordinate of the bounding box center in pixels. predictions[].y Y-coordinate of the bounding box center in pixels. predictions[].width Width of the bounding box in pixels. Implementation Example
const url = "https://universe.roboflow.com/";
// Replace headers or query params with the values required by this API.
const response = await fetch(url, {
headers: {
"X-API-Key": "YOUR_API_KEY"
}
});
if (!response.ok) throw new Error(`Request failed: ${response.status}`);
const data = await response.json();
console.log(data); What Can You Build?
Note: These code examples are AI-generated and unverified. Always refer to the official API documentation for accurate usage.
Common Errors & Troubleshooting
Matrix Score Breakdown
Partially tested on Apr 5, 2026
Technical Specifications
Related Tags
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