rfdetr
RF-DETR
Decision gist · record as of 2026-08-14
Yes. RF-DETR is actively maintained, recently released, has no security vulnerabilities, and offers strong accuracy-latency tradeoffs for object detection and segmentation. The Apache 2.0 base license is permissive. Install friction is low. The main consideration is Python 3.10+ requirement and PyTorch dependency; if your environment already supports those, this is a solid choice for real-time vision tasks.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- Torch and torchvision must be installed; GPU support is optional but recommended for real-time performance.
- Installation is straightforward via pip with low friction.
License · maintenance · safety
Apache License 2.0 (permissive) — The base rfdetr package and standard models are Apache 2.0 licensed, permitting commercial and private use. Premium models (RF-DETR-XL/2XL) use PML 1.0, which may have different terms—verify licensing for those components if you plan to use them.
last release 2026-08-11 (3 days) · last repo commit 2026-08-14 · 8,972 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 525,564 downloads/mo, #6,185 on PyPI
Alternatives
Verify before relying
pip install rfdetr
import rfdetr
model = rfdetr.load_model('rf-detr-s')
results = model.predict(image_path='photo.jpg')- Whether keypoint detection is production-ready or still in preview as stated in the description
- Specific hardware requirements or recommended GPU types for real-time inference targets
- Whether the package includes pre-trained model weights or if they must be downloaded separately
What it is and what it does
RF-DETR is a production-ready computer vision library for detecting objects, segmenting instances, and detecting keypoints in images using a transformer architecture. It wraps a DINOv2 vision transformer backbone and provides a unified API across all three tasks. The library is built by Roboflow and includes benchmarked model sizes (N, S, M, L) under Apache 2.0, plus larger variants (XL, 2XL) under PML 1.0.
The package is designed for developers building real-time vision applications who need strong accuracy-latency tradeoffs. It depends on PyTorch, torchvision, transformers, numpy, and several utility libraries (requests, tqdm, pydantic, supervision, pyDeprecate). The library is actively maintained, recently released, and has no known security vulnerabilities.
Use it for
- Build real-time object detection systems for robotics or autonomous systems using the lightweight N/S/M model variants.
- Perform instance segmentation on images or video streams where you need both bounding boxes and pixel-level masks.
- Integrate keypoint detection (preview) into pose estimation or human activity recognition pipelines.
- Benchmark detection accuracy against other SOTA models using the published COCO and RF100-VL results.
- Deploy models with neural architecture search to optimize for your specific dataset and hardware constraints.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
RF-DETR is actively maintained, recently released, has no security vulnerabilities, and offers strong accuracy-latency tradeoffs for object detection and segmentation. The Apache 2.0 base license is permissive. Install friction is low. The main consideration is Python 3.10+ requirement and PyTorch dependency; if your environment already supports those, this is a solid choice for real-time vision tasks.
Install
rfdetr on PyPI
Before you install
Installation is straightforward via pip with low friction. The package is actively maintained with a recent release (3 days old) and strong repository activity (8972 stars). It requires Python 3.10 or later and depends on established libraries like torch, torchvision, transformers, and numpy.
Requires Python 3.10 or later. Torch and torchvision must be installed; GPU support is optional but recommended for real-time performance.
License in practice
The base rfdetr package and standard models are Apache 2.0 licensed, permitting commercial and private use. Premium models (RF-DETR-XL/2XL) use PML 1.0, which may have different terms—verify licensing for those components if you plan to use them.
Quickstart
pip install rfdetr
import rfdetr
model = rfdetr.load_model('rf-detr-s')
results = model.predict(image_path='photo.jpg')Verify before relying
- Whether keypoint detection is production-ready or still in preview as stated in the description
- Specific hardware requirements or recommended GPU types for real-time inference targets
- Whether the package includes pre-trained model weights or if they must be downloaded separately
Package facts
| License | Apache License 2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 9 packagesrequestsnumpytorchtorchvisiontqdmtransformerspydanticsupervisionpyDeprecate |
| Maintenance | Actively maintained 3 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 525,564 / month, #6,185 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersIntended Audience :: EducationIntended Audience :: Science/ResearchLicense :: OSI Approved :: Apache Software LicenseOperating System :: MacOSOperating System :: POSIXOperating System :: UnixProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Topic :: Scientific/EngineeringTopic :: Scientific/Engineering :: Artificial IntelligenceTopic :: Software DevelopmentTyping :: Typed |
Evidence: rfdetr-1.9.2-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “object detection transformer”
- rfdetrRF-DETR is a transformer-based object detection, instance…
- spacy-transformersIntegrates pretrained transformer models (BERT, RoBERTa, XLNet,…
- detoxifyDetoxify classifies text comments for toxic content using pre-trained…
Give your agent the search over MCP, or paste the wish link into any chat.
More Software Development packages
Provides backported and experimental type hints for Python 3.9+, allowing use of newer typing features on older Python versions and enabling early experimentation with type system PEPs before they enter the standard library.
NumPy provides an N-dimensional array object and a comprehensive suite of mathematical, linear algebra, Fourier transform, and random number functions for scientific computing in Python.
FastAPI is a Python web framework for building REST APIs using type hints, with automatic request validation, serialization, and interactive API documentation.
Provides a way to document function parameters, class attributes, return types, and variables inline using Python's `Annotated` type hint syntax instead of traditional docstrings.
Typer builds command-line applications from Python functions using type hints, automatically generating help text, argument parsing, and shell completion.
Install it if you are building CLIs in Python.
Distlib provides low-level packaging utilities for building, distributing, and managing Python software—including metadata handling, version specifiers, wheel support, script installation, and dependency resolution.
See also rf100vl · sahi · mmdet · groundingdino-py · vit-pytorch · segmentation-models-pytorch · pytorchcv · ultralytics · inference-models · icevision