Roboflow organizes, prepares, and improves your image and annotation training data. Build a higher quality computer vision model on your dataset quickly. Today, Roboflow supports object detection and classification models.
Developers use Roboflow so they can focus on their domain problems instead of wrangling boilerplate computer vision infrastructure code.
Like teams and other individuals, you might use Roboflow to:
Annotate images or upload existing annotations
See if labels are in-frame (and one-click correct them if they are not)
Preprocess images: resizing, grayscale, auto-orientation, contrast adjustments
Augment images to increase your training data: flip, rotate, brighten / darken, crop, shear, blur, and add random noise
Generate annotation formats like TFRecords, CreateML and Turi Create, and custom YOLOv3 implementations (flat text files or Darknet)
Share version-controlled datasets with your team
Easily use data across models built in Tensorflow, PyTorch, fast.ai, Keras, and more
Train models in one click with Microsoft Azure
Consider our Getting Started Guide for more.