Object Detection

Comparing Custom Models to Google Cloud Vision API

In this guide, we go over how to evaluate object detection models on Roboflow Universe versus Google Cloud Vision.

Roboflow Video Inference with Custom Annotators

Performing real-time video inference is crucial for many applications like autonomous vehicles, security systems, logistics, and more. However, setting up a robust video inference pipeline can be time consuming. You

Introducing the Roboflow Logistics Pre-trained Object Detection Model

Starting a machine learning model from zero is computationally expensive and time-consuming. Pre-trained models solve this by offering a jump-start: they come with learned features from extensive training on large

Enhancing Child Safety with Computer Vision

This article was contributed to the Roboflow blog by Abirami Vina. Introduction Child safety is a priority for parents and caregivers, an issue society takes seriously. While traditional safety measures

Using Computer Vision to Improve Railway Safety

In this guide, we show how to use computer vision to identify hazardous situations on railways for use in building safety systems.

Improving Vision Model Performance Using Roboflow & Tenyks

This is a guest post with Jose Gabriel Islas Montero (ML Engineer and Evangelist at Tenyks), and Dmitry Kazhdan (CTO & Co-Founder at Tenyks) Introduction When improving an object detection model,

Using Computer Vision for Online Exam Proctoring

This article was contributed to the Roboflow blog by Abirami Vina. Introduction Digital transformation is a common practice in various fields, including education. There has been a significant shift towards

How to Use Computer Vision to Monitor Inventory

Real-time insights extracted from video streams can drastically improve efficiency for how industries operate. One high-impact application of this is in inventory management. Whether you’re a factory manager looking

How to Reduce Dataset Size Without Losing Accuracy

We're often told that data is the backbone that drives the development of powerful and robust models.  And that's certainly true – data is the raw material that we feed into

Using Stable Diffusion and SAM to Modify Image Contents Zero Shot

Introduction Recent breakthroughs in large language models (LLMs) and foundation computer vision models have unlocked new interfaces and methods for editing images or videos. You may have heard of inpainting,

A LLaMa 2, Midjourney & Autodistill Computer Vision Pipeline

Combine the use of Midjourney, Autodistill, LLaMa 2 and Roboflow to create a object detection model without data collection or labeling.

How to Use Computer Vision for Environment Monitoring

This article was contributed to the Roboflow blog by Abirami Vina. Measuring changes to our environment is an important part of understanding progress made toward a more sustainable world. Historically,

Build a Chess Game Recorder with Computer Vision

This article was contributed to the Roboflow blog by the team at A1H1. Introduction The project of making an automated chess game recorder started after finding out that a chess

Improve Accuracy: Polygon Annotations for Object Detection

In this blog post, we will explore how you can improve your object detection model performance by converting your bounding box annotations to polygon annotations. We will also discuss the

How to Use Generative AI to Augment Computer Vision Data

Dive deep into Kopikat.co, a tool for generative data augmentation created by OpenCV.ai to improve the quality of datasets.

How to Train DETR on a Custom Dataset

DETR stands out from traditional object detection models due to its unique architecture and approach. Unlike other models that rely on anchor boxes or region proposal networks, DETR formulates object

How to Deploy YOLOv8 Using Intel's OpenVINO and Amazon SageMaker

Introduction In this post we will walk through the process of deploying a YOLOv8 model (ONNX format) to an Amazon SageMaker endpoint for serving inference requests, leveraging OpenVino as the

Automated Computer Vision Inspection of Physical Pipelines

In this guide, we show how to identify various types of pipeline defects using computer vision.

How to Train YOLO-NAS on a Custom Dataset

YOLO-NAS is the latest state-of-the-art real-time object detection model. Learn how to train YOLO-NAS on your custom data.

Zero-Shot Image Annotation with Grounding DINO and SAM - A Notebook Tutorial

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.

Synthetic Data Generation with NVIDIA and Roboflow

Learn how to build computer vision models that leverage synthetic data using NVIDIA Omniverse and Roboflow.

Grounding DINO : SOTA Zero-Shot Object Detection

Most object detection models are trained to identify a narrow predetermined collection of classes. Zero-shot detectors like Grounding DINO want to break this status quo by making it possible to detect new objects without re-training a model.

How to Code Non-Maximum Suppression (NMS) in Plain NumPy

Double Detection in Computer Vision If you’ve been working with object detection long enough, you’ve undoubtedly encountered the problem of double detection. For some reason, the model detects

Building a Computer Vision Assisted Pill Inspection System

The article below was contributed by Timothy Malche, an assistant professor in the Department of Computer Applications at Manipal University Jaipur. Pill Inspection System Overview This project creates a system

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.