If deployment is the magic of computer vision, then the act of training a model is the proverbial wave of that wand. Training a computer vision model is the process by which a computer learns to detect specific objects within images - put simply (and more elegantly), it’s how we automate human sight.
Until today, most machine learning experts have created (and are actively using) training pipelines that are patched together as a combination of one-off services, custom developed tools, and open source software. These frameworks are undoubtedly impressive, but here at Roboflow, we’ve built something that allows anyone - not just machine learning experts - to create and deploy their own computer vision models.
Roboflow Train provides a hassle-free way to scale up GPU training on any custom dataset - we even have code-free integrations with external pipelines like AWS Rekognition, Microsoft Azure, and Google's AutoML.
Why Roboflow Train?
Roboflow Train is an automated machine learning solution that our customers can use to transform any dataset into a trained computer vision model, ready for deployment. There are a number of benefits of Roboflow Train, a few of which we’ve outlined below - but please contact us directly if you’d like to give this feature a test-drive. We’ll add some training credits to your account and can even schedule a formal demonstration to show you around.
Improved Model Performance
In the machine learning process, there are (traditionally) many distinct technologies that are attached to one another, and they can get pretty complicated to keep in-line. When these systems are not implemented carefully, it can manifest in poor model performance - often in very subtle ways.
Roboflow Train eliminates the guesswork and fine-tuning associated with managing these dependencies; we offer a battle-tested machine learning pipeline that is used by thousands of developers to create high performing, production-ready computer vision models.
With Roboflow Train, you don’t have to hire an expensive team of machine learning experts - you can use computer vision with the engineering resources you already have, and apply the valuable time of your experts to differentiated places where it’s truly needed.
Kick off a train with a single click - we’ll do the rest. In this way, Roboflow Train enables users to abstract away the complexities of the training process, and in just a few hours, your model will be ready for deployment.
Trained models can be used anywhere, not only within your Roboflow account - there are all kinds of deployment destinations available to our users, including hosted web inference and on-device deployment, like NVIDIA Jetsons, OAK devices, or even a web browser.
Training in Roboflow enables our customers to use “Active Learning,” whereby low-confidence inference data is pushed back into Roboflow to be annotated, augmented, and re-trained. The more you use your model, the better it gets - and in this way, you can build a lasting competitive advantage with your data moat.
Transfer Learning allows models inside your account to learn iteratively by starting from the previous model checkpoint each time you train, jumpstarting its learning with knowledge generalized from other datasets it has previously seen.
Model Assisted Labeling (Label Assist)
Label Assist is an automatic annotation option helps you (and your team) cut the time it takes to label and annotate your images in half by using the output of your trained model as a starting point for annotation. It is as cool as it sounds, check out the demo.
Continuity of Institutional Knowledge
Even if your computer vision team loses a key member, everyone else will still have access to the trained models, datasets and source images inside Roboflow. You won’t lose the process and institutional knowledge to replicate and improve your models. Keeping everything under one roof will save your team time, resources and (hopefully) a bit of hair pigmentation.
Many of our customers are not computer vision or machine learning experts - they’re domain experts in their fields, ranging from manufacturing to botany, healthcare to natural resources. Leveraging Roboflow Train is an intuitive and seamless way to create high-performance computer vision models that solve real-world problems, and you don’t need to be (or even hire) a machine learning expert to make it happen.