Overview

About
Roboflow provides all of the tools you need to convert raw images into a custom trained computer vision model and deploy it for use in your applications. 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
​Convert existing VOC XML annotations to COCO JSON 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)
​Quickly assess your dataset quality​
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​
​Deploy models as an infinitely scalable API, to an edge device, or to a web browser.
​Obtain and share public datasets​
Consider our Getting Started Guide for more.

Quick Start

Last modified 7mo ago

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