Computer Vision
Roboflow
Train and deploy custom vision models from photos
Freemium - from FreeRuns in the cloud
Pricing
Freemium - from Free
Free
Platforms
Web
Hosted app
Category
Computer Vision
58 tools
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Last updated
Sep 23
Listing updated
Best for
Label and version image datasets
Annotate with boxes or masks, track dataset versions, and manage review before a single training run starts.
Pricing checked Sep 2026
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About Roboflow
Roboflow is an end-to-end platform for custom computer vision: teams upload images, annotate them with bounding boxes or segmentation masks, augment the dataset, then train detection, classification, or segmentation models and deploy them through a hosted API, edge devices, or SDKs. Shared workspaces, version-controlled datasets, and annotation review make it usable by real teams rather than solo hobbyists.
The open-source side is substantial: the Supervision library for video processing and support for exporting to formats other frameworks consume. Deployment spans cloud APIs, NVIDIA Jetson, Raspberry Pi, and webcams through Roboflow Inference. A free public tier covers small projects, with paid plans scaling by usage. It suits product teams, students, and enterprises shipping vision features; researchers pushing novel architectures will still train with PyTorch directly.
- Covers the full loop: annotation, training, evaluation, and deployment
- Strong free tier for public projects and students
- Runs on many devices and cameras, plus a hosted API fallback
- Active open-source ecosystem, including the Supervision library
- Training very large or experimental models still requires your own stack
- Pricing on private projects scales with usage and needs monitoring
- Annotation at serious volume still costs real human hours
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See categoryPrograms that detect, classify, and interpret visual data, from pretrained labeling APIs you can call this afternoon to annotation and training platforms for custom models. Listings flag deployment targets (cloud, edge, on-prem), accuracy baselines, and data-privacy posture.