Model Deployment

8 Mar 2023 • 4 min read

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

SUMMARY Double detection, where an object detection model fires multiple overlapping bounding boxes on the same object, is a common issue that breaks downstream analytics like counting and tracking. Non-Maximum Suppression (NMS) resolves this by computing Intersection over Union (IoU) across all predicted boxes and discarding lower-confidence duplicates

3 Feb 2023 • 6 min read

Deploy Models from Roboflow with the Luxonis DepthAI SDK

The new Luxonis DepthAI SDK Roboflow Integration gives users the option to deploy Roboflow models to OAK devices with more functionality and out-of-the-box options for customization of inferences.

19 Jan 2023 • 8 min read

How to Deploy a YOLOv8 Model to a Raspberry Pi

In this article, you'll learn how to deploy a YOLOv8 model onto a Raspberry Pi.

15 Dec 2022 • 8 min read

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.

9 Dec 2022 • 4 min read

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.

18 Nov 2022 • 5 min read

Using Computer Vision to Save Sea Lions

SUMMARY Steller sea lion numbers in Alaska's western Aleutian Islands have dropped 94% over 30 years, and NOAA researchers studying the cause generate thousands of remote camera images that must be reviewed manually. A computer vision tool called Steller Sight automates the triage step, classifying each image as

17 Nov 2022 • 4 min read

Use Docker to Deploy Computer Vision Models

SUMMARY Deploying a computer vision model involves far more than training it: managing Python packages, CUDA versions, system-level dependencies, and hardware differences all create friction before a single inference runs in production. Docker addresses this by packaging an application and all its dependencies into a portable container image, which

26 Oct 2022 • 4 min read

Launch: Semantic Segmentation for Labeling, Training, Deployment

SUMMARY Semantic segmentation assigns a class label to every pixel in an image, making it useful for tasks where per-pixel precision matters: road and sidewalk mapping from aerial imagery, crack detection in infrastructure, defect identification in manufacturing, and medical image analysis. Roboflow now supports semantic segmentation end-to-end,

8 Aug 2022 • 4 min read

How to Use Object Detection to Trigger Automated Email Alerts

Learn how to trigger automated email alerts when an object detection model identifies the location of an object.

3 Aug 2022 • 4 min read

Use Raspberry Pi and Luxonis OAK to Deploy Vision Models in Robotics

Learn how to use the Raspberry Pi and Luxonis OAK to run computer vision models for robotics projects.

1 Aug 2022 • 4 min read

How to Deploy YOLOv7 to a Jetson Nano

We'll be creating a dataset, training a YOLOv7 computer vision model, and deploying it to a Jetson Nano to perform real-time object detection.

19 Jul 2022 • 4 min read

Deploy a Computer Vision Model: A How-To Guide

SUMMARY The Roboflow Deploy tab centralizes the options for getting a trained computer vision model into use without writing boilerplate for each target: it supports drag-and-drop inference on images and video files, live webcam inference in the browser, URL-based inference, and copy-paste code snippets for the

30 Jun 2022 • 3 min read

Launch: Roboflow Native iOS SDK

Constrained bandwith? Left without the option to extend production data beyond your local network or corporate firewall? In need of real-time inference speeds on the edge? The Roboflow Mobile iOS SDK is a great option if you are developing an iOS application.

19 May 2022 • 4 min read

Launch: Roboflow OAK pip package

roboflowoak pip package lets you natively interface with your Roboflow workspace through Python scripts and deploy to an OAK device.

2 Apr 2022 • 10 min read

How to Deploy Computer Vision Models: Best Practices

In this guide, we walk through the fundamentals of deploying vision models and the questions you should evaluate when deciding how to deploy a model.

27 Sep 2021 • 2 min read

Deploying Computer Vision Models as Mircroservices

SUMMARY Deploying a computer vision model as a microservice keeps vision logic isolated from application code, which matters because models often require specific versions of Python, CUDA, or specialized hardware that you do not want to force on the rest of your stack. The microservice pattern also handles bursty workloads

9 Sep 2021 • 3 min read

What is TensorRT?

SUMMARY TensorRT is NVIDIA's inference optimization framework, built to run machine learning models as fast as possible on NVIDIA GPU hardware via CUDA cores. To use it, you typically train in PyTorch or TensorFlow and then convert your model to TensorRT format. This post covers the CUDA vs

6 Sep 2021 • 3 min read

How to Implement Object Tracking for Computer Vision

This post is a comprehensive guide on how to implement object tracking with your object detection model to track your custom objects

30 Aug 2021 • 1 min read

What is Amazon Rekognition?

SUMMARY Amazon Rekognition is an off-the-shelf computer vision API that detects and classifies a fixed set of common objects (furniture, plants, and similar generic categories) from images sent via HTTP. It works well for those predefined categories, but if your application needs to detect domain-specific objects not

16 Aug 2021 • 1 min read

What is CoreML?

SUMMARY CoreML is Apple's on-device machine learning inference framework, designed to run models efficiently on iPhones and other Apple hardware by routing computation through Apple's Neural Engine for lower latency and reduced power draw. Models are stored as .mlmodel files and can be created with

12 Jul 2021 • 11 min read

How AI Protects My Garden from Rabbits

Rabbits were eating all of my vegetables. I decided to take a stand and implement a computer vision enabled system to automatically spook them away from my garden.

21 Jun 2021 • 3 min read

What Is the JAX Deep Learning Framework?

You've probably heard of TensorFlow and PyTorch, and maybe you've even heard of MXNet - but there is a new kid on the block of machine learning frameworks - Google's JAX.

14 Jun 2021 • 7 min read

Building vs. Buying a Computer Vision Platform

SUMMARY Building a computer vision pipeline in-house requires stitching together image upload, annotation, dataset versioning, training, deployment, and active learning, and the result is typically fragile, hard to maintain, and difficult to debug when components break. This post examines seven recurring problems teams encounter when building their own infrastructure,

27 May 2021 • 6 min read

License Plate Detection and OCR on an NVIDIA Jetson

In this blog, we discuss how to train and deploy a custom license plate detection model to the NVIDIA Jetson. While we focus on the detection of license plates in particular, this guide also provides an end-to-end guide on deploying custom computer vision models to your NVIDIA Jetson on the edge.