roboflow

What it is and what it does

Roboflow is the official Python client for the Roboflow computer vision platform. It bridges your local Python environment and Roboflow's hosted infrastructure, letting you programmatically manage projects, upload datasets with annotations, trigger model training, and run inference on trained models. The package abstracts the Roboflow API behind a workspace-project-version hierarchy that mirrors the web interface, so you work with familiar concepts: create a project, upload images and annotations in standard formats (YOLO, COCO, Pascal VOC), train a model, and deploy it for inference.

The package ships with 21 runtime dependencies covering image processing (opencv-python-headless, Pillow, numpy), visualization (matplotlib), CLI tools (typer, click), and HTTP utilities (requests, urllib3). A lightweight roboflow-slim variant strips out image processing for serverless or embedded contexts. It is actively maintained, recently released, and has no known security vulnerabilities.

Use it for:

• Upload a local dataset to Roboflow and trigger training of an object detection model without leaving Python
• Run inference on images using a trained model hosted on Roboflow or self-hosted via Roboflow Inference
• Create and manage multiple computer vision projects programmatically, organizing datasets by annotation type
• Search for images across your workspace by class or tag and export matching results as a ready-to-use dataset
• Deploy custom model weights (e.g., YOLOv10) to a Roboflow version for inference via the API

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Roboflow is a Python client for the Roboflow computer vision platform, enabling you to create projects, upload datasets and images, train vision models, and run inference on models hosted on Roboflow or self-hosted via Roboflow Inference.

Yes. Roboflow is actively maintained, has low install friction, permissive licensing, and no known vulnerabilities. Install it if you are already using Roboflow's platform and want to automate project and model management from Python. If you are not yet a Roboflow user or prefer a self-contained, offline computer vision workflow, you may not need it. The roboflow-slim variant makes it practical for lightweight deployments.

Install

roboflow on PyPI

pip install roboflow

uv add roboflow

poetry add roboflow

Installing roboflow

Before you install

Install friction is low; the package is a pure Python wheel with no compiled dependencies. Maintenance is active, with a recent release 22 days ago and steady commits. The 21 runtime dependencies include heavy libraries like opencv-python-headless, numpy, and matplotlib, but a lightweight roboflow-slim variant is available for environments where image processing is not needed.

License in practice

Licensed under Apache Software License (permissive), which allows commercial use, modification, and distribution with minimal restrictions—no notable licensing concerns for most use cases.

Quickstart

pip install roboflow

import roboflow

rf = roboflow.Roboflow(api_key="YOUR_API_KEY")
workspace = rf.workspace()
project = workspace.create_project(
    project_name="My Project",
    project_type="object-detection"
)
predictions = project.version(1).models()[0].predict("image.jpg", hosted=True).json()

Requires Python 3.10 or higher. API key from Roboflow account needed for authentication. Full install (~400MB) includes heavy dependencies; use roboflow-slim for lightweight environments.

Verify before relying

• Whether the package works offline or requires persistent network connectivity to Roboflow servers
• Performance characteristics and latency for inference on large batches of images
• Compatibility with specific model formats beyond those mentioned (yolov5, yolov8, yolov10)

Package facts

Evidence: roboflow-1.4.0-py3-none-any.whl

Tags

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