Roboflow Blog

Education

What is Object Detection? The Ultimate Guide.

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

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.

A Primer on Transfer Learning

Transfer learning [https://blog.roboflow.com/what-is-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.

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

The below post is a guest post written by data scientist Joseph Rosenblum [https://www.linkedin.com/in/joseph-rosenblum/]. He is using computer vision to make cities more efficient and

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 [https://www.kaggle.com/] is a great resource for free data

5 Strategies for Handling Unbalanced Classes

Suppose you're trying to teach an alien – like one of the crewmates from the wildly popular game Among Us [http://www.innersloth.com/gameAmongUs.php] – to tell the difference between

Scaled-YOLOv4 is Now the Best Model for Object Detection

(based on Microsoft COCO benchmarks) The object detection space remains white hot with the recent publication of Scaled-YOLOv4 [https://arxiv.org/abs/2011.08036], establishing a new state of the

How to Run Jupyter Notebooks on an Apple M1 Mac

You've probably heard a lot about the MacBook that contains the new Apple M1 chip. Quick summary: It's fast. Like, really fast. You, a data scientist or related tech professional,

How to Label Images for Computer Vision Models

This guide walks through tactics to ensure your dataset is as high quality as possible for computer vision tasks.

What is Computer Vision and Machine Vision? A Guide for Beginners

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.

What is Active Learning?

Machine learning algorithms are exceptionally data-hungry, requiring thousands – if not millions – of examples to make informed decisions. Providing high quality training data for our algorithms to learn is an expensive

Google Researchers Say Underspecification is Ruining Your Model Performance. Here's Five Ways to Fix That.

We read that Google underspecification paper so you don't have to.

Bringing Street Murals to Life with Computer Vision

In Bedford–Stuyvesant, Brooklyn [https://en.wikipedia.org/wiki/Bedford%E2%80%93Stuyvesant,_Brooklyn] (BedStuy), Yuri Fukuda regularly walks by a mural that showcases prominent female leaders. Since October 2005,

YOLOv4 - Ten Tactics to Build a Better Model

The YOLO v4 repository is currently one of the best places to train a custom object detector, and the capabilities of the Darknet repository are vast. In this post, we discuss and implement ten advanced tactics in YOLO v4 so you can build the best object detection model from your custom dataset.

Evaluating Object Detection Models with mAP by Class

When evaluating an object detection model in computer vision, mean average precision [https://blog.roboflow.com/mean-average-precision/] is the most commonly cited metric for assessing performance. Remember, mean average precision

How to Use the Detectron2 Model Zoo (for Object Detection)

Detectron2 is Facebook's open source library for implementing state-of-the-art computer vision techniques in PyTorch. Facebook introduced Detectron2 [https://ai.facebook.com/blog/-detectron2-a-pytorch-based-modular-object-detection-library-/] in October 2019 as a complete rewrite

How This Fulbright Scholar is Using Computer Vision to Protect Endangered Species

The below post is by Kasim Rafiq [https://twitter.com/Kasim21], a conservationist, Fulbright Scholar, and National Geographic Explorer studying at UC Santa Cruz. Kasim holds a PhD in Wildlife

Train Test Split Guide and Overview

In order to ensure our models are generalizing well (rather than memorizing training data), it is best practice to create a train, test split. [https://blog.roboflow.com/train-test-split/] That

Luxonis OAK-D - Deploy a Custom Object Detection Model with Depth

We are pretty excited about the Luxonis OpenCV AI Kit (OAK-D) device at Roboflow, and we're not alone. Our excitement has naturally led us to create another tutorial on how to train and deploy a custom object detection model leveraging Roboflow and DepthAI, to the edge, with depth, faster.

Behind the Design of an Augmented Reality Board Game App

During the summer of 2019, I received a Facebook message from Roboflow co-founder Brad Dwyer [https://twitter.com/braddwyer] asking me if I wanted to design a new mobile app

How to Save and Load Model Weights in Google Colab

Google Colab [https://colab.research.google.com/] is Google's hosted Jupyter Notebook product that provides a free compute environment, including GPU and TPU [https://blog.roboflow.com/glossary/]. Colab comes

Using Computer Vision to Help Deaf and Hard of Hearing Communities

The below post is a lightly edited guest post by David Lee, a data scientist using computer vision to boost tech accessibility for communities that need it. David has open

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.

How Tesla Teaches Cars to Stop

Creating successful computer vision models requires handling an ever growing set of edge cases. At the 2020 Conference on Computer Vision and Pattern Recognition (CVPR), Tesla's Senior Director of AI,

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.