Overview
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, not boilerplate computer vision infrastructure code.
Teams and individuals use Roboflow to, e.g.:
Convert VOC XML annotations to COCO JSON annotations (and vice versa)
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)
Version datasets and share them with their team
Share datasets across your organization
Easily use data across models built in Tensorflow, PyTorch, fast.ai, Keras, and more.
Obtain and share public datasets
One-click train models with Microsoft Azure
Consider our Getting Started Guide for more.