Product Updates

2 Jun 2021 • 1 min read

Roboflow Changelog: June 2021

Each month, we publish a list of recent features and additions to the Roboflow suite of products. The previous month's update is here. In May there has been a bevy of backend changes to support a huge user-facing release coming next month. The most noticeable updates this

5 May 2021 • 8 min read

How to Train and Deploy Custom Models to Your OAK

In this blog, we'll walk through the Roboflow custom model deployment process to the OAK and show just how seamless it can be.

5 May 2021 • 3 min read

Partnering with Luxonis and OpenCV for Seamless Deployment to OpenCV AI Kit

SUMMARY Roboflow and Luxonis have partnered to let users train a custom computer vision model and deploy it to the OAK-1 or OAK-D via a Docker container, eliminating the manual steps of model format conversion to OpenVINO and dependency setup that previously caused silent accuracy regressions. After training

4 May 2021 • 1 min read

Roboflow Changelog: May 2021

The changelog is our compendium of monthly updates. If you want to take a walk down memory lane, you can being your trip back in time with last month's edition. In April, our major product efforts centered around launching our brand new user interface. This redesign of our

18 Apr 2021 • 2 min read

Roboflow's new User Interface

SUMMARY Roboflow's redesigned interface reorganizes the end-to-end computer vision workflow around four clearer stages. Datasets are now called Projects to reflect that they hold images, annotations, versions, and models together. Upload and Annotate have dedicated spots in the sidebar, dataset version generation is now a sequential

4 Apr 2021 • 7 min read

How to Use Roboflow with IBM Visual Recognition (IBM Watson vs Roboflow)

SUMMARY IBM shut down IBM Visual Recognition in 2021, leaving teams mid-project and needing a path forward. This post walks through two methods for exporting data out of IBM Visual Recognition and IBM Cloud Annotations, then compares what to look for in a replacement platform, covering annotation speed, active

1 Apr 2021 • 1 min read

Roboflow Changelog: April 2021

Each month we bring you the high level bullet-points of improvements and additions to Roboflow. If you missed it, last month's changelog is here. In March we were focused on expanding Roboflow's inference capabilities with the release of on-device NVIDIA Jetson support, our open

22 Mar 2021 • 2 min read

Video Inference with Roboflow

SUMMARY Running a Roboflow model on video works by splitting the footage into individual frames, sending each frame through the model for predictions, then stitching the annotated frames back into a video. Roboflow provides an open source shell script that handles all three steps, so you can visualize detection output

11 Mar 2021 • 3 min read

Introducing Roboflow Support for NVIDIA Jetson

SUMMARY Roboflow Inference supports the full NVIDIA Jetson family, letting teams deploy custom-trained computer vision models to edge devices using three Docker commands, with GPU acceleration enabled by default and speeds up to 15 frames per second on the Jetson Xavier NX. The on-device inference server maintains API

5 Mar 2021 • 1 min read

Roboflow Changelog: March 2021

The monthly changelog showcases improvements in Roboflow over the past month. You can find the previous changelog here. In February, we had a major focus on reinforcing our foundation; after several months of rapid feature expansion we spent a considerable amount of time fixing bugs, improving infrastructure, and preparing for

20 Feb 2021 • 3 min read

Introducing Upload Batches, the Unannotated Queue, and Mark as Null

SUMMARY Roboflow introduced three annotation workflow features to help teams manage iterative dataset collection: Upload Batches automatically groups each new image upload so teams can divide labeling work without merging separate datasets; the Unannotated Queue makes it easy to track exactly which images still need labels; and Mark as Null

3 Feb 2021 • 2 min read

Roboflow Changelog: February 2021

Welcome to our monthly roundup post of new features and enhancements. You can find the previous changelog here. The biggest new features released this month were transfer learning and Label Assist. Roboflow Organize * Announced teams for all (now teams of up to 3 people can collaborate on the Starter Plan

25 Jan 2021 • 2 min read

Launch: Model Assisted Labeling

SUMMARY Roboflow Label Assist cuts annotation time by using your already-trained Roboflow models to pre-populate bounding boxes on new images, so annotators spend time only correcting errors rather than drawing every label from scratch. Public model support starting with 80 Microsoft COCO classes is included free on the

17 Jan 2021 • 2 min read

Teams for All: Create Free Teams on Roboflow

SUMMARY Roboflow now offers free teams, letting groups of three or fewer collaborate on datasets, annotation, and model deployment within a single shared workspace using individual API keys per account. Team members can share any dataset they own, annotate images together, and manage uploads and inference without sharing credentials. Larger

6 Jan 2021 • 3 min read

Using the Upload API to Collect Images from the Wild

SUMMARY Production computer vision models degrade without a feedback loop that continuously surfaces real-world edge cases. The Roboflow Upload API lets you pipe images directly from deployed applications into a Roboflow dataset, so failures users encounter in the field can be flagged, labeled, and folded back into the next

4 Jan 2021 • 2 min read

Introducing the Object Count Histogram

We are excited to announce the introduction of object count histograms, now available in the Roboflow dataset health check.

3 Jan 2021 • 2 min read

Roboflow Changelog: January 2021

Welcome to our monthly changelog where we catalog our recent feature additions and improvements. If you missed it, you can find last month's changelog here. This month we launched Roboflow Annotate, an integrated image annotation tool included in all Roboflow plans. In the first few weeks, over 1500

28 Dec 2020 • 2 min read

Get a Hosted API for your Object Detection Model

SUMMARY After training a custom object detection model, the hardest part is often deploying it without managing servers that sit idle or buckle under load. Roboflow Infer addresses this by training a model on your labeled dataset and immediately exposing it as a hosted API that scales with demand, so

8 Dec 2020 • 2 min read

Introducing Roboflow Annotate

SUMMARY Roboflow Annotate is a self-serve image annotation tool built directly into the Roboflow platform, removing the friction of managing a separate labeling tool outside your pipeline. The integrated design supports team collaboration from a single source of truth and makes it straightforward to jump in and out of

6 Dec 2020 • 2 min read

Share Your Datasets with the Computer Vision Community

SUMMARY Roboflow offers to publicly host community-contributed computer vision datasets, making them discoverable to tens of thousands of developers and automatically indexed by Google Dataset Search. Hosted datasets are available for download in every major annotation format, including Pascal VOC XML, COCO JSON, and TFRecords, with no conversion work

4 Dec 2020 • 1 min read

Roboflow Changelog: December 2020

Welcome to the first of our monthly changelogs, where we will be cataloging our recent feature additions and improvements. Roboflow Organize * Added ability to rebalance train/test split * Clarified pro plan features in-app * Sped up thumbnail generation * Added image upload by URL to the upload API * Paginated the image

20 Nov 2020 • 2 min read

Revamping Train, Validation, Test, Split Management

Splitting data into train, validation, and test splits is essential to building good computer vision models. Today, we are announcing in-app changes to Roboflow that make it even easier to manage your train test splits as you are working through the computer vision workflow.

8 Nov 2020 • 3 min read

Hands on with the Roboflow Infer Web Application Interface Builder

SUMMARY After training a model with Roboflow Train, the Example Web App gives an immediate browser-based interface to test predictions: upload an image or provide a URL, adjust confidence thresholds and bounding box overlap, filter classes, and view results as an annotated image or raw JSON. Because the app

3 Nov 2020 • 3 min read

Evaluating Object Detection Models with mAP by Class

SUMMARY Overall mAP scores can mask weak spots in a multi-class object detection model: a 98% aggregate hides the fact that one class is dragging performance down. Roboflow Train addresses this by surfacing per-class mAP on both the validation and training sets after every training run, so you