Product Updates

28 Oct 2020 • 2 min read

Train Test Split Guide and Overview

SUMMARY Splitting a dataset into training, validation, and test sets is a core practice for detecting overfitting and ensuring a computer vision model generalizes beyond its training examples. Roboflow defaults to a 70/20/10 split at upload time but gives you direct control: you can assign individual image batches

12 Oct 2020 • 2 min read

Introducing an Improved Shear Augmentation

Today, we introduce a new and improved shear augmentation. We'll walk through some details on the change, as well as some intuition and results backing up our reasoning.

27 Sep 2020 • 3 min read

Introducing Grayscale and Hue/Saturation Augmentations

SUMMARY Roboflow has added three color-based augmentation options, grayscale, hue, and saturation, to help models generalize to objects that appear under different lighting conditions or in varied color environments. Grayscale augmentation randomly converts a configurable percentage of training images to single-channel output, reducing the model's reliance

2 Sep 2020 • 2 min read

Explore Images, Annotations, and Metadata Easier

SUMMARY Roboflow's updated image preview interface lets users view annotations full-screen, toggle individual annotation groups on and off by hovering, and surface image metadata including the original filename, camera used, modification date, and which split the image belongs to. For dataset versions with augmentations applied, the preview

21 Aug 2020 • 3 min read

The crazy story of how we got our .com domain

For almost a year, Roboflow (our computer vision dataset management tool) has lived at roboflow.ai. It's served us well but we have always lusted after the dot com. No longer! We managed to acquire roboflow.com from the giant German company that owned it since 2001. The

3 Aug 2020 • 5 min read

Ontology Management for Computer Vision

SUMMARY Choosing class names at the start of a computer vision project and then needing to change them later is one of the most time-consuming parts of iterating on a dataset. This post covers practical ontology management strategies: labeling at the most specific level possible so classes can be

29 Jul 2020 • 2 min read

Advanced Augmentations in Roboflow

SUMMARY Roboflow added two augmentations to its platform, Mosaic and Cutout, that were central to accuracy gains in recent detection model research. Mosaic combines four training images into one, simulating random crops, mixing classes that rarely appear together, and varying object counts per image. Cutout overlays randomly placed black boxes

23 Jul 2020 • 1 min read

Roboflow can now ingest video!

SUMMARY Roboflow now accepts video file uploads directly, removing the manual step of extracting frames with command-line tools. Users select a sample rate to pull a subset of frames from the video, then annotate those frames using Roboflow's integrated labeling tools or by outsourcing the job in

7 Jul 2020 • 4 min read

Introducing Class Label Remapping and Omission

With Roboflow Pro, you can now remap and omit class labels within Roboflow as a preprocessing step for your dataset version. Class management is a powerful tool to get the most out of your training data and your hard earned class label annotations.

27 May 2020 • 3 min read

Introducing An Even Better Way to Preview Image Preprocessing and Augmentation

SUMMARY Roboflow's revamped preprocessing and augmentation previews let you see exactly what each step does to your images before committing to a pipeline, replacing guesswork and boilerplate transformation code with a visual interface. The update covers choices like aspect-ratio-preserving resize strategies (padding, crop, reflect) and the

24 May 2020 • 3 min read

Thermal Infrared Dataset for Object Detection

SUMMARY Thermal infrared cameras detect surface temperature rather than reflected light, which makes them useful for detecting people and objects in darkness, smoke, or other low-visibility conditions where RGB cameras fail. Roboflow released a free 203-image thermal dataset of people and dogs, captured with a Seek Compact XR

29 Apr 2020 • 4 min read

Breaking Down Roboflow's Health Check Dimension Insights

SUMMARY Resizing images for computer vision is not a simple stretch-to-fill operation: aspect ratio distortion, small image outliers, and extreme width-to-height ratios all affect what a model can learn. Roboflow's Dimension Insights tool, part of the Dataset Health Check, visualizes every image in a

28 Apr 2020 • 1 min read

Introducing the Roboflow Model Library

SUMMARY The Roboflow Model Library brings together 7 open source object detection models and 3 classification models in one place, each accessible via GitHub, a downloadable Jupyter notebook, or Google Colab with free GPU access. All notebooks integrate directly with Roboflow, so datasets uploaded and annotated on the platform can

30 Mar 2020 • 1 min read

Introducing Image Preprocessing and Augmentation Previews

SUMMARY Choosing augmentation settings without previewing the result means iterating blind, generating dataset versions only to discover the brightness shift was too aggressive or the rotation too extreme. Roboflow added preprocessing and augmentation previews so you can hover over an image in the dataset builder and see exactly how each

18 Mar 2020 • 3 min read

Introducing Bounding Box Level Augmentations

SUMMARY Standard image augmentation applies transforms to the entire frame, but bounding box level augmentation applies transforms only to the pixels inside each labeled bounding box, letting you vary brightness, blur, or other properties of a target object independently from its background. This technique, drawn from a 2019 Google research

27 Jan 2020 • 2 min read

Introducing Public Datasets

SUMMARY Getting access to clean, labeled data is one of the hardest parts of starting a computer vision project. Roboflow Public Datasets (public.roboflow.com) addresses this by hosting free, downloadable datasets covering domains from board games to aerial drone imagery, each available in formats including VOC XML, COCO JSON,