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Universe Search

Search Roboflow Universe for public projects and models from Python.

Roboflow Universe is the public catalog of community-shared projects, datasets, and models. The Python SDK exposes a low-level adapter you can use to search Universe programmatically.

from roboflow.adapters import rfapi

results = rfapi.search_universe(
    "vehicles",
    api_key="YOUR_API_KEY",
    project_type="object-detection",  # optional
    limit=12,
    page=1,
)

for project in results.get("results", []):
    print(project["workspace"], project["project"], project["name"])

Parameters

  • query (str, positional) - search term.

  • api_key (str, kw-only) - your Roboflow API key. Required for Universe rate limits.

  • project_type (str, kw-only, optional) - filter by project type. One of object-detection, classification, instance-segmentation, semantic-segmentation, keypoint-detection.

  • limit (int, kw-only, default 12) - page size.

  • page (int, kw-only, default 1) - 1-indexed page number.

Response

The function returns the JSON response body verbatim. Each result entry includes the workspace slug, project slug, project name, type, image count, and (for trained models) version metadata you can plug straight into Roboflow().workspace(...).project(...).version(...).model.predict().

Each result also includes thumbnail and annotationThumbnail fields (both nullable strings). thumbnail is a URL to the project's thumbnail image, and annotationThumbnail is a URL to a sample annotated image from the project. Either field is null when the corresponding data is unavailable.

Run a Universe model directly

Once you've found a model with search_universe, run inference on it the same way you would your own model:

See Run a Model on an Image for details on predict() across task types.

CLI equivalent

See Universe Search (CLI).

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