Greatest Hits

Roboflow and Ultralytics Partner to Streamline YOLOv5 MLOps

We're proud to share that Roboflow has entered into a partnership agreement with Ultralytics, the creators of YOLOv5, and that Roboflow is now the official dataset management and annotation tool

OpenAI's CLIP is the most important advancement in computer vision this year

CLIP is a gigantic leap forward, bringing many of the recent developments from the realm of natural language processing into the mainstream of computer vision: unsupervised learning, transformers, and multimodality

Roboflow Universe: the Computer Vision Community

We’re excited to introduce Roboflow Universe, the new hub for computer vision datasets and pre-trained models.

Active Learning Tips: How to Continuously Improve Your Production Model

You've built your first model and plan to get it deployed to production. Now what? Like any software, the computer vision model needs to be continuously improved for potential edge

Experimenting with CLIP+VQGAN to Create AI Generated Art

Earlier this year, OpenAI announced a powerful art-creation model called DALL-E. Their model hasn't yet been released but it has captured the imagination of a generation of hackers, artists, and

How We Built Paint.wtf, an AI Game with 150,000+ Submissions that Judges Your Art

Paint.wtf is an online game that uses AI to score user-submitted digital drawings to zany prompts like, "Draw a giraffe in the arctic" or "Draw a bumblebee loves capitalism.

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

The Ultimate Guide to Object Detection

Object detection is a computer vision technology that localizes and identifies objects in an image. Due to object detection's versatility, object detection has emerged in the last few years as

Seven Tips for Labeling Images for Computer Vision

Creating a high quality dataset for computer vision is essential to having strong model performance. In addition to collecting images that are as similar to your deployed conditions as possible,

Introduction to Computer Vision

After reading this post, you should have a good understanding of computer vision without a strong technical background and you should know the steps needed to solve a computer vision problem.

Glossary of Common Computer Vision Terms

Computer Vision (and Machine Learning in general) is one of those fields that can seem hard to approach because there are so many industry-specific words (or common words used in novel ways) that it can feel a bit like you're trying to learn a new language when you're trying to get started.

The Train, Validation, Test Split and Why You Need It

At Roboflow, we often get asked, what is the train, validation, test split and why do I need it? The motivation is quite simple: you should separate you data into train, validation, and test splits to prevent your model from overfitting and to accurately evaluate your model. T

Tackling the Small Object Problem in Object Detection

Detecting small objects is one of the most challenging and important problems in computer vision. In this post, we will discuss some of the strategies we have developed at Roboflow

Benchmarking the Major Cloud Vision AutoML Tools

Until now, there has been little independent research published on the performance of AutoML tools - (both relative to each other and against state of the art open source models)

How to Train YOLOv5 On a Custom Dataset

The YOLO family of object detection models grows ever stronger with the introduction of YOLOv5 by Ultralytics. In this post, we will walk through how you can train YOLOv5 to

How to Train YOLOv4 on a Custom Dataset

In this tutorial, we walkthrough how to train YOLOv4 Darknet for state-of-the-art object detection on your own dataset, with varying number of classes. Train YOLOv4 on a custom dataset with

What is Mean Average Precision (mAP) in Object Detection?

What is mean average precision? How do we calculate mAP?

A popular self-driving car dataset is missing labels for hundreds of pedestrians

And that's a problem that is extremely dangerous. Machine learning, the process of teaching computer algorithms to perform new tasks by example, is poised to transform industries from agriculture to