• 5 min read
How to Train a Custom TensorFlow Lite Object Detection Model
Learn how to train a custom TensorFlow Lite object detection model with a custom dataset.
• 3 min read
Using Computer Vision to Find Brands in YouTube Videos
Over 500 hours of video are being uploaded to YouTube (speaking of which.. have you subscribed to our channel yet?) every minute*. Making sense of that sea of video content creates valuable opportunities. For brands, knowing when and where they're being mentioned means identifying their share-of-voice, marketing to
• 14 min read
Deploy A Custom Model to the Luxonis OAK - A Quickstart Guide
This guide will take you the long distance from unlabeled images to a working computer vision model deployed and inferencing live at 15FPS on the affordable and scalable Luxonis OpenCV AI Kit (OAK) device.
• 3 min read
Reducing Traffic with Computer Vision
How Transport for Cairo is Improving Commuting for Millions with Computer Vision
Reducing traffic in well-planned cities where bus routes are well-mapped, subways are running on a predictable cadence, and lanes are well-marked is a significant undertaking.
Now consider improving traffic without predictable routes, maps, and regular modes of transit.
• 7 min read
PP-YOLO Surpasses YOLOv4 - State of the Art Object Detection Techniques
Baidu publishes PP-YOLO and pushes the state of the art in object detection research by building on top of YOLOv3, the PaddlePaddle deep learning framework, and cutting edge computer vision research.
• 5 min read
Ontology Management for Computer Vision
As their projects mature and dataset sizes grow, most teams wrestle with their workflow. Slicing and dicing data is more of an art than a science and you will want to experiment with what works best for your problem over time (and, in fact, you will probably go through this
• 8 min read
How to Train an EfficientNet Model with a Custom Dataset
Learn how to train an EfficientNet model with a custom dataset.
• 2 min read
Advanced Augmentations in Roboflow
Roboflow Pro now supports Cutout and Mosaic.
Recent research has shown there is still plenty of room to grow model performance through augmenting our training data. Roboflow has written extensively about data augmentation and has highlighted some of the recent advances that have made new models like YOLOv4 and YOLOv5
• 14 min read
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)
• 6 min read
VoTT for Image Annotation and Labeling
A guide on using VoTT to label your own computer vision dataset.
• 1 min read
Roboflow can now ingest video!
One of the most common questions we get is "How can I use computer vision object detection models with video?" The answer is simple: you treat each frame as an image.
But, in practice, that has been quite cumbersome. It's meant fumbling around with command line
• 6 min read
Improving Infrastructure Asset Management with Computer Vision
The below post is a lightly edited guest post from Result! Data, a Netherlands-based consultancy providing leading digital services.
The Roboflow team thanks Gerard Mol (Managing Partner) and Brand Hop (Chief Data Science) for their contributions. View their original post on detecting road signs with computer vision.
Introduction
Result! Data
• 9 min read
Retail Store Item Detection using YOLOv5
Guest post by Roboflow user, Shayan Ali Bhatti, who used Roboflow to train an object detection model to identify items in grocery stores.
Reposted with permission. Original content here.
In this article, I present an application of the latest version of popular deep learning algorithm YOLO i.e. YOLOv5, to
• 8 min read
How to Train a TensorFlow 2 Object Detection Model
Learn how to train a TensorFlow 2 object detection model on a custom dataset.
• 3 min read
The TensorFlow 2 Object Detection Library is Here
The TensorFlow Object Detection API has been upgraded to TensorFlow 2.0. We discuss here what the new library means for computer vision developers and why we are so excited about the new TensorFlow 2.0 Object Detection library!
Furthermore, we are excited to announce Roboflow's model library
• 3 min read
What are Anchor Boxes in Object Detection?
Learn what anchor boxes are and why they are used in object detection.
• 5 min read
Convert Supervisely Annotations in Two Minutes
In this post, we walk through how to download data from Supervise.ly and convert Supervise.ly annotations to YOLO Darknet format specifically, and more generally convert Supervisely JSON to any other object detection annotation format for use in any of your custom computer vision models.
This guide is imperative
• 3 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.
• 1 min read
Roboflow vs Scale
A question we often get is "How is Roboflow different from Scale?" The truth is, Roboflow works great in conjunction with outsourced labeling services like Scale, LabelBox, SuperAnnotate, Amazon SageMaker Ground Truth, and Mechanical Turk.
We support importing your annotations directly from many of their APIs and Roboflow&
• 3 min read
How AI Acts as a Human Rights Watchdog for the Maasai People
The Maasai are an indigenous ethnic group in modern Kenya and northern Tanzania, tracing routes to the Great Rift Valley in East Africa as early as the 15th century. Roughly two million Maasai people retain rich cultural traditions, including leading a semi-nomadic life and subsisting predominantly on their cattle, which
• 6 min read
Train a YOLOv4-tiny Model on a Custom Dataset
Learn how to train a YOLOv4-tiny model on a custom dataset.
• 14 min read
What is YOLOv5? A Guide for Beginners.
In this article, we discuss what is new in YOLOv5, how the model compares to YOLO v4, and the architecture of the new v5 model.
• 6 min read
Improving Uno with Computer Vision (Plus the Dataset so You Can Too)
You've likely been playing Uno wrong all of your life.
It's a simple game, right? Rid your hand of all your cards first, and you're the victor.
In fact, Uno is a multi-stage game where players accumulate points across multiple hands. The first player
• 6 min read
Creating BoardBoss: A Mobile Application that Improves Boggle
How Making an iOS Application Inspired Roboflow
Before the Roboflow team was making tools for improving how developers apply computer vision to their problems, we were making our own computer vision applications. One of those applications, Magic Sudoku, even won Product Hunt's Augmented Reality App of the Year.
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