Roboflow Blog

Computer Vision

Track and Count Objects Using YOLOv8

Counting moving objects is one of the most popular use cases in computer vision. It is used, among other things, in traffic analysis and as part of the automation of manufacturing processes. That is why understanding how to do it well is crucial for any CV engineer.

How to Deploy a YOLOv8 Model Using Roboflow and Repl.it

In this guide, we walk through how to train and deploy a YOLOv8 model using Roboflow, Google Colab, and Repl.it.

Narrate the Contents of a Room with Computer Vision

In this guide, learn how to use text-to-speech with computer vision models to narrate the objects in a room.

What is a Neural Network? A Deep Dive.

In this article, we discuss what a neural network is and walk through the most common network architectures.

How to Blur a Bounding Box in Python

Consider a scenario where you are building a model to detect cars on a street. If a car is parked on a street designated with no parking, you want to

How to Draw a Bounding Box for Computer Vision with Python

In this post, we discuss how to use the cv2 library to draw and fill a bounding box in Python.

How to Draw a Bounding Box Prediction Label with Python

In this article, we show how to use the cv2 library to draw bounding box prediction labels in Python.

Collective Communication in Distributed Systems with PyTorch

The full code for this article is on GitHub Today, we will explore the use of PyTorch's distributed collective communication feature. When working with multiple GPUs, it is necessary to

What is an Activation Function? A Complete Guide.

In this article, we discuss what an activation function is, why they are used, and what types of activation functions are commonly used.

What is YOLOv8? The Ultimate Guide.

The field of computer vision advances with the newest release of YOLOv8, setting a new state of the art for object detection and instance segmentation.

How to Train YOLOv8 Object Detection on a Custom Dataset

In this article, we walk through how to train a YOLOv8 object detection model using a custom dataset.

Roboflow Collaborates with Intel to Deliver Next Generation Computer Vision Pipeline for Enterprises

Roboflow joined the Intel Disruptor Initiative to push the limits of innovation in real-world computer vision applications. Roboflow and Intel are working together to democratize access to computer vision by

What is Zero Shot Learning in Computer Vision?

In this article, we discuss what zero-shot learning is, how it works, and when zero-shot learning is and is not useful.

Launch: Version, Export, and Train Models in the Roboflow Python Package

In this article, we discuss the new version, export, and train model features in the Roboflow pip package.

How Artificial Intelligence is Influencing Video Production

In this article, learn how Artificial Intelligence is and could create more powerful tools for the video production industry to use.

HPU vs GPU - Benchmarking the Frontier of AI Hardware

When you are training machine learning models, it is essential to pick hardware that optimizes your models performance relative to cost. In training, the name of the game is speed per epoch – how fast can your hardware run the calculations it needs to train your model on your data.

Launch: Use Universe Models for Label Assist and Training

In this guide, learn how to use public models on Roboflow Universe to assist you with labeling and to speed up the process of building an accurate model.

How to Train YOLOv7 Instance Segmentation on a Custom Dataset

In this article, we're going to walk through how to detect concrete cracks using instance segmentation.

AWS Ice Lake Comparison: Benchmarks and Insights

Historically, GPUs have been the go-to for computer vision training, providing excellent performance for training different model types. But, GPU-optimized computing is not your only option for running computer vision

What is Semi-Supervised Learning? A Guide for Beginners.

In this post, we discuss what semi-supervised learning is and walk through the techniques used in semi-supervised learning.

Computer Vision Assisted Structural Damage Inspection Using Drones

In this post, Timothy Malche walks through how to inspect structural damage with computer vision and drones.

Launch: Roboflow Integration with Ultralytics HUB

Ultralytics, the creators of YOLOv5, and Roboflow now support an integration making it easier to import YOLOv5 models from HUB to Roboflow, export datasets to Ultralytics HUB from Roboflow, and

Track Football Players with Computer Vision

In this post, we use a YOLOv5 detection model and state-of-the-art tracker ByteTRACK to track football players.

Studying Links Between Litter and Socio-Economic Factors with Computer Vision

In this post, we talk about a report that studies links between litter and socio-economic factors with help from computer vision.

How to Create Segmentation Masks with Roboflow

In this guide, you will learn how to create segmentation masks with the results of a computer vision model hosted on Roboflow.