Learn more about the role that our design team plays in Roboflow's mission to democratize access to computer vision.| Roboflow Blog
Accurate data labeling is essential for training machine learning models. This guide explores top data labeling platforms, key features to consider, and pros and cons so you can choose the right tool for building better AI.| Roboflow Blog
Learn how to build a real-time, privacy-preserving gaze tracker using MediaPipe FaceMesh and TensorFlow.js.| Roboflow Blog
Object detection has entered a new era in 2025. Next-generation models are combining transformer efficiency and real-time speed to power breakthroughs in automation, robotics, and visual intelligence across every industry. See the best models.| Roboflow Blog
YOLO26 brings faster CPU inference, small-object accuracy, and edge optimization to the YOLO family. See how it stacks up against today’s leading computer vision models.| Roboflow Blog
Modern manufacturing runs on precision, and computer vision is redefining what’s possible on the factory floor. See how AI-powered inspection systems detect and act on defects in real time.| Roboflow Blog
Learn how to integrate Roboflow Batch Processing with AWS S3 to run large-scale image inference efficiently. This step-by-step guide shows how to process 100k+ images at a lower cost.| Roboflow Blog
Learn how to integrate Roboflow Batch Processing with Azure Blub Storage to run large-scale image inference efficiently. This step-by-step guide shows how to process 100k+ images at a lower cost.| Roboflow Blog
Learn how to integrate Roboflow Batch Processing with Google Cloud Storage to run large-scale image inference efficiently. This step-by-step guide shows how to process 100k+ images at a lower cost.| Roboflow Blog
We go hands-on with the NVIDIA DGX Spark, a "supercomputer" built for local AI development, and test a real-time computer vision project.| Roboflow Blog
Learn Python object detection step-by-step using Roboflow Inference. Run RF-DETR and fine-tuned models from Roboflow Universe on images and videos with ease.| Roboflow Blog
Instance segmentation lets AI models identify and outline each object in an image with pixel-perfect precision. In this tutorial, learn how to label segmentation data, and train a high-accuracy RF-DETR model.| Roboflow Blog
This blog explores the top code editors for developing, testing, and deploying Vision AI projects. It covers Visual Studio Code, Cursor, Colab, Jupyter, and PyCharm, explaining their key features, pros, and cons.| Roboflow Blog
Vision-Language Models are getting smaller, faster, and smarter - no cloud required. In this guide, we explore the best local VLMs you can run on your own hardware, from Llama 3.2 Vision to SmolVLM2, and show how to deploy them efficiently with Roboflow Inference.| Roboflow Blog
Learn how to use RF-DETR, Roboflow’s state-of-the-art real-time object detection model, to build a workflow that identifies, tracks, and labels objects across video frames with high accuracy and efficiency.| Roboflow Blog
Learn what a VLM is and how to use VLMs in Roboflow Workflows to perform various vision tasks.| Roboflow Blog
Learn how Meta Research's new Segment Anything Model works to achieve high performance on image segmentation tasks.| Roboflow Blog
Learn how to use Florence-2 in Roboflow Workflows for zero-shot object detection, OCR, and more.| Roboflow Blog
The computer vision research community benchmarks new models and enhancements to existing models to test model performance. Benchmarking happens using standard datasets which can be used across models. With this approach, the efficacy of various models can be compared, in general, to show how one model is more or less| Roboflow Blog
Learn how to take a dataset from Voxel51 into Roboflow, train an RF-DETR model, and deploy it to the cloud, private servers, or edge devices. This step-by-step guide walks you through dataset conversion, model training, workflow testing, and real-world integration.| Roboflow Blog
Explore six tips on how to effectively use YOLO-World to identify objects in images.| Roboflow Blog
YOLO-NAS is the latest state-of-the-art real-time object detection model. Learn how to train YOLO-NAS on your custom data.| Roboflow Blog
Learn what zero-shot object detection is, applications for zero-shot object detection, and how to get started with Grounding DINO, a zero-shot model.| Roboflow Blog
In this comprehensive tutorial, discover how to speed up your image annotation process using Grounding DINO and Segment Anything Model. Learn how to convert object detection datasets into instance segmentation datasets, and use these models to automatically annotate your images.| Roboflow Blog
Autodistill is a new ecosystem of packages that enable you to distill knowledge from large vision models into smaller, edge-ready models.| Roboflow Blog
With this project, we integrate real-time feedback and computer vision to develop a hand-washing steps-tracking system using a Python application and a Roboflow-trained model.| Roboflow Blog
Roboflow eliminates boilerplate code when building object detection models. Get started with an example.| Roboflow Blog
YOLOv3 [https://models.roboflow.ai/object-detection/yolo-v3-pytorch] is known to be an incredibly performant, state-of-the-art model architecture: fast, accurate, and reliable. So how does the "new kid on the block," EfficientDet [https://blog.roboflow.com/breaking-down-efficientdet/], compare? Without spoilers, we were surprised by these results. NOTE: YOLO v5 [https://models.| Roboflow Blog
Learn what precision and recall are and why they are important in computer vision.| Roboflow Blog
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.| Roboflow Blog
Understanding image preprocessing and augmentation options is essential to making the most of your training data.| Roboflow Blog
In this article, we walk through how to train a YOLOv8 object detection model using a custom dataset.| Roboflow Blog
Use Roboflow Auto Label to automatically label images for use in training fine-tuned models.| Roboflow Blog
In this guide, we discuss how OCR is used in manufacturing and how you can apply OCR in a manufacturing facility.| Roboflow Blog
Learn how to build a manual assembly quality assurance system to ensure products are properly assembled.| Roboflow Blog
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.| Roboflow Blog
What is mean average precision? How do we calculate mAP?| Roboflow Blog
Today we are releasing RF-DETR, a state-of-the-art real-time object detection model. Learn more about how RF-DETR works and how to use the model.| Roboflow Blog
Explore alternatives to GPT-4 Vision with Large Multimodal Models such as Qwen-VL and CogVLM, and fine-tuned detection models.| Roboflow Blog
In this guide, we share our first impressions testing LLaVA-1.5.| Roboflow Blog
In this guide, we talk about what image classification is and what problems you can solve with image classification.| Roboflow Blog
Roboflow Workflows lets you build computer vision applications in a web editor and deploy them on your own hardware.| Roboflow Blog
Learn how to train a ResNet-50 model for image classification.| Roboflow Blog
Learn what OCR data extraction is and what models you can use to programmatically read the contents of images.| Roboflow Blog
Learn about computer vision and how you can use it to solve problems.| Roboflow Blog
Learn about the latest advancements in AI helping automotive manufacturers modernize their factories and improve productivity.| Roboflow Blog
In this article, we discuss what a neural network is and walk through the most common network architectures.| Roboflow Blog
When you deploy a computer vision model, you may want to have a dedicated server, or several servers, to which you can route requests to your vision model. This is ideal for workflows where you are processing images from a client (i.e. a web application), recorded videos, and more.| Roboflow Blog
End-to-end tutorial for detecting and counting objects on a conveyor belt using computer vision.| Roboflow Blog
In this guide, we discuss what a confusion matrix is and how to use them to evaluate the performance of a computer vision model.| Roboflow Blog
Learn about the history of the YOLO family of objec tdetection models, extensively used across a wide range of object detection tasks.| Roboflow Blog
Ball tracking is crucial for AI systems to analyze sports effectively, but it's challenging due to factors like the ball's small size, high velocity, complex backgrounds, similar-looking objects, and varying lighting. This tutorial will teach you how to overcome these challenges.| Roboflow Blog
In this guide, we discuss what object detection is, how it works, how to label and augment data for object detection models, and more.| Roboflow Blog
Florence-2 is a lightweight vision-language model open-sourced by Microsoft under the MIT license.| Roboflow Blog
Learn what GPT-4o is, how it differs from previous models, evaluate its performance, and use cases for GPT-4o.| Roboflow Blog
Learn what OpenCV is, what you can do with OpenCV, how OpenCV performs on various tasks when run on CPU vs. GPU, and more.| Roboflow Blog
There are several quality checks that need to be run on coffee beans before they are packaged and ready for delivery. A professional taster will “cup” coffee to ensure it meets a given taste profile. The color of the coffee beans may be checked using a photometer to ensure the| Roboflow Blog
See how nine different OCR models compare for scene text recognition across industrial domains.| Roboflow Blog
Learn how to monitor retail queues to identify when customers have been waiting for too long.| Roboflow Blog
Learn how to train a YOLOv9 model on a custom dataset.| Roboflow Blog
In this guide, we evaluate Google's Gemini LMM against several computer vision tasks, from OCR to VQA to zero-shot object detection.| Roboflow Blog
Learn how to use computer vision in your data analytics pipelines.| Roboflow Blog
In this guide, we walk through how to deploy computer vision models (i.e. YOLOv8) offline using Roboflow Inference.| Roboflow Blog
In this guide, we share findings experimenting with GPT-4 with Vision, released by OpenAI in September 2023.| Roboflow Blog
