Roboflow vs Scale
Brad DwyerPublished Jul 5, 2020
Roboflow and Scale serve different stages of the computer vision pipeline: Scale and similar services (LabelBox, SuperAnnotate, SageMaker Ground Truth) handle outsourced annotation, while Roboflow takes over after labeling to manage preprocessing, augmentation, dataset versioning, and training integrations. Roboflow imports annotations directly from most of these services, and its Pro tier can pull SageMaker Ground Truth manifests from S3, making it straightforward to combine an external labeling vendor with Roboflow's dataset tooling without committing to any one vendor's ecosystem.
A question we often get is "How is Roboflow different from Scale?" The truth is, Roboflow works great in conjunction with outsourced labeling services like Scale, LabelBox, SuperAnnotate, Amazon SageMaker Ground Truth, and Mechanical Turk.
We support importing your annotations directly from many of their APIs and Roboflow's Pro tier can even import SageMaker Ground Truth manifest files directly from an S3 bucket so you can have Amazon annotate your images and use them in your own training infrastructure or on another cloud platform. (Plus, if you're a startup, Roboflow can help you use your AWS credits for labeling and annotation jobs!)
In fact, if you're still evaluating which labeling provider is right for you, Roboflow is the easiest way to test out multiple options. And, since we work seamlessly with all of the most popular tools, its also the best way to avoid vendor lock-in. Our dataset visualization and quality control tools can also help you evaluate the quality of different labeling vendors.
Roboflow picks up where labeling stops off. Whether you're annotating images yourself with tools like CVAT, LabelMe, VoTT and LabelImg or have contracted with someone else to outsource your labeling, Roboflow makes using those labeled images in your preferred training pipeline a breeze.
Want us to show you how our labeling integrations work? Contact our sales team and we'll be happy to give you a demo.
