Roboflow Blog

12 Feb 2021 • 4 min read

Liquid Neural Networks in Computer Vision

Excitement is building in the artificial intelligence community around MIT's recent release of liquid neural networks. The breakthroughs that Hasani and team have made are incredible. In this post, we will discuss the new liquid neural networks and what they might mean for the vision field.

8 Feb 2021 • 4 min read

Using Computer Vision to Help Win $1 Million in Mountain Dew's Big Game Contest

Last night during Super Bowl LV, Mountain Dew ran an ad featuring John Cena riding through a Mountain Dew-themed amusement park. Bottles are scattered all over the scene: neon signs on buildings, in fun house mirrors, and flying out of the car trunk. At the end of the ad, John

8 Feb 2021 • 7 min read

How to Train and Deploy a License Plate Detector to the Luxonis OAK

In this post, we will leverage Roboflow and the Luxonis OAK to train and deploy a custom license plate model to your OAK device.

8 Feb 2021 • 4 min read

Using Computer Vision to Make Card Grading Faster and Cheaper

This blog post is a guest post by James Nitsch, a mobile developer (Android) with WillowTree Apps living in Charlottesville, VA. He's passionate about do-it-yourself hardware projects, 3D printing, and machine learning & computer vision. He's happily employed but always loves collaborating and tackling innovative or

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

31 Jan 2021 • 3 min read

Using Computer Vision to Win at Duck Hunt

Can we use object detection to automate identifying moving objects on a screen? Abhinav Mandava leverages Roboflow to create an aimbot (which automates aiming and firing for the player) for Duck Hunt.

26 Jan 2021 • 10 min read

Using Unity Perception to train an object detection model with synthetically generated images

Collecting images and annotating them with high-quality labels can be an expensive and time-consuming process. The promise of generating synthetic data to reduce the burden is alluring. In the past we have covered techniques such as augmentation, context synthesis, and model assisted labeling to improve the process. In this post,

25 Jan 2021 • 3 min read

Computer Vision Use Cases in Healthcare and Medicine

Computer vision technology continues to expand its use cases in healthcare and medicine. In this post, we will touch on some exciting example use cases for vision in healthcare and medicine and provide some resources on getting started applying vision to these problems.

25 Jan 2021 • 1 min read

Launch: Model Assisted Labeling

Use Roboflow Trained Models to Annotate Data One of the most time-consuming parts of the computer vision workflow is curating a high-quality dataset. When we launched Roboflow Annotate last month we aimed to streamline this process by launching an easy to use image annotation tool built right into your computer

19 Jan 2021 • 3 min read

Using Computer Vision to Detect Package Deliveries

This post is a guest post written by Brian Egge. Brian works in finance, though this is a personal project. Many households are getting more packages delivered than ever before. In my neighborhood the delivery drivers don’t ring the doorbell or announce they’ve dropped a package off. Many

17 Jan 2021 • 2 min read

Teams for All: Create Free Teams on Roboflow

Machine learning is a team sport, and getting a computer vision model to production is no exception. All parts of the process are improved with a team: collecting data from multiple sources; annotating data with colleagues; sharing versioned datasets; and using deployed models. We're pleased to introduce free

13 Jan 2021 • 4 min read

A Primer on Transfer Learning

Transfer learning is a machine learning (ML) technique where knowledge gained during training a set of problems can be used to solve other related problems. It’s very similar to the concept of reusing code in computer programming, except instead of sharing code between different applications or software projects, we’

12 Jan 2021 • 2 min read

Announcing Roboflow’s Seed Round

Computer vision is a generational technology. Like the PC, internet, and mobile phones, computer vision’s impact will reshape every industry. In transportation, for example, the advent of machine vision gives rise to self-driving cars, rewiring how we navigate the world around us. Manufacturing companies are finding and reducing visual

8 Jan 2021 • 5 min read

How to Try CLIP: OpenAI's Zero-Shot Image Classifier

Earlier this week, OpenAI dropped a bomb on the computer vision world.

6 Jan 2021 • 3 min read

Using the Upload API to Collect Images from the Wild

The key to production quality machine learning models is continuous iteration and improvement. The first step is getting a model that is "good enough" for your first version. But once you deploy to the real world you'll invariably find edge cases that confuse your model. Collecting

6 Jan 2021 • 4 min read

Using Public Datasets to Improve your Computer Vision Models

Ok, so you've trained a model and it's not doing as well as you'd hoped. Now what? You could experiment with augmentation, try a different architecture, or check your training data for errors. But what if those all fail? Oftentimes, the single most impactful

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.

4 Jan 2021 • 5 min read

Using Computer Vision to Boost Cities' Efficiency by Reallocating Police Resources

The below post is a guest post written by data scientist Joseph Rosenblum. He is using computer vision to make cities more efficient and decrease the bias in traffic-related policing. (He is open to new opportunities!) Municipalities today are cash-strapped, with $360 billion in losses expected between 2020 and 2022

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 • 5 min read

Football, Kaggle, Roboflow: Using Computer Vision to Tackle Helmet Safety

If you're searching for a dataset to use or are looking to improve your data science modeling skills, Kaggle is a great resource for free data and for competitions. For example, there's currently an open Kaggle competition detecting American football helmet impacts (crashes) in which you

28 Dec 2020 • 2 min read

Get a Hosted API for your Object Detection Model

Roboflow provides tools for labeling, organizing, and training a computer vision model. Once you finish running one of the Jupyter notebooks from our Computer Vision tutorials you can download a weights file optimized for making predictions on your custom dataset. The Current State of Affairs But what next? How do

25 Dec 2020 • 3 min read

How To Annotate Images with Your Team Using Roboflow

Dataset annotation is better with teams: you can move more quickly, keep everyone on the same page, track annotation progress, and easier provide examples of what the ultimate dataset should look like. In this post, we'll walkthrough an example workflow of annotating data with your team using Roboflow

21 Dec 2020 • 4 min read

Tackling the Internet of Things with Roboflow: Object Detection Apps on Android

Joo chan Kim, PhD student, is developing an object detection application for Android devices that can identify specific IoT sensors by using a custom detection model.

15 Dec 2020 • 5 min read

How to Train Scaled-YOLOv4 to Detect Custom Objects

Object detection technology advances with the release of Scaled-YOLOv4. This blog is written to help you apply Scaled-YOLOv4 to your custom object detection task, to detect any object in the world, given the right training data.