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VisionUltralytics

Ultralytics YOLO

YOLO models for real-time object detection and vision.

Category
Vision
Pricing
FREEMIUM
Source
Open core
Platforms
CLIAPI
Models
Self-contained (on-device)
Verified
Jun 8, 2026

The open-source PyTorch framework behind the YOLO (You Only Look Once) family of vision models. One unified API covers object detection, instance and semantic segmentation, image classification, pose estimation, and oriented bounding boxes, with both a CLI and a Python interface. The 2026 flagship, YOLO26, is an end-to-end, NMS-free architecture tuned for edge and low-power deployment.

Capabilities 3

What it actually does — grouped by capability family.

  • Fine-tuning / training (primary capability)
  • Object detection (primary capability)
  • Image classification (secondary capability)

Pros & cons

  • Real-time inference on edge and GPU
  • One API for detect/segment/pose/track
  • Large community + many pretrained models
  • Self-hostable, runs fully offline
  • AGPL-3.0 — commercial use needs a paid license
  • Training larger models needs real GPUs
  • Docs sprawl across YOLO versions

Tags

View all Vision
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    Annotation tooling, auto-labelling, hosted training, and edge deployment for computer-vision projects. Strong default when you're shipping a custom vision model rather than reaching for a multimodal LLM.

    End-to-end vision MLOps
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    • annotation
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    DICOM/NIfTI/point-cloud support
    Enterprise pricing, no free tier
    • data-annotation
    • training-data
    • computer-vision
    • medical-imaging
    • +1
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    Voxel51

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    FiftyOne — open-source vision data platform.

    A toolkit for exploring, debugging, and curating vision datasets. Strong story for finding model failure modes, balancing classes, and tracking experiment drift across visual data at scale.

    Open-source FiftyOne core
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    • open-source
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    • python
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    Supervisely

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    All-in-one computer vision platform to curate, label, and train models.

    A unified computer vision platform covering data curation, annotation, model training, and deployment across images, video, 3D point clouds, and medical imagery. AI-assisted labeling, experiment tracking, and a large catalog of installable apps make it customizable for most CV workflows. Free for researchers and small teams; Pro and self-hostable Enterprise editions for companies.

    Images, video, 3D point cloud, DICOM
    Broad platform has a learning curve
    • computer-vision
    • data-annotation
    • labeling
    • model-training
    • +1