Getting Started

30 May 2021 • 6 min read

What Does "End to End" Really Mean?

SUMMARY Building a working computer vision model once required stitching together custom pipelines, cloud services, and ML expertise. Roboflow closes that loop by covering every stage from raw image upload through annotation, dataset versioning, model training, and deployment to a hosted API endpoint, then feeds inference results back as training

22 Mar 2021 • 2 min read

Video Inference with Roboflow

SUMMARY Running a Roboflow model on video works by splitting the footage into individual frames, sending each frame through the model for predictions, then stitching the annotated frames back into a video. Roboflow provides an open source shell script that handles all three steps, so you can visualize detection output

21 Mar 2021 • 4 min read

Danger Monitoring for Cyclists using Raspberry Pi and Object Detection

SUMMARY This project builds a low-cost cyclist danger monitor using a Raspberry Pi 4, a Google Coral TPU stick for faster inference, and an LED traffic light that warns the rider when cars or bicycles are detected in proximity. The model was trained on three datasets totaling over 6,

1 Mar 2021 • 3 min read

5 Emerging Trends in Computer Vision Applications from OpenCV's AI Competition

SUMMARY Reviewing over 200 project proposals submitted to the 2021 OpenCV AI Competition, five application patterns stand out across the more than 1,200 competing teams: assisting the visually impaired with spatial awareness, improving workplace safety by identifying hazardous zones, monitoring COVID protocol compliance, and tracking animal health and conservation

25 Jan 2021 • 3 min read

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.

25 Dec 2020 • 3 min read

How To Annotate Images with Your Team Using Roboflow

SUMMARY Splitting annotation work across a team in Roboflow involves creating one dataset per annotator, sharing each dataset with the full team so everyone can see examples from colleagues, and then merging the individually labeled datasets into a single combined dataset once all images are labeled. This workflow keeps annotation

15 Dec 2020 • 6 min read

How to Train Scaled-YOLOv4 to Detect Custom Objects

Object detection technology advances with the release of Scaled-YOLOv4. This blog is written to help you apply Scaled-YOLOv4 to your custom object detection task, to detect any object in the world, given the right training data.

8 Dec 2020 • 2 min read

Introducing Roboflow Annotate

SUMMARY Roboflow Annotate is a self-serve image annotation tool built directly into the Roboflow platform, removing the friction of managing a separate labeling tool outside your pipeline. The integrated design supports team collaboration from a single source of truth and makes it straightforward to jump in and out of

30 Nov 2020 • 6 min read

How to Run Jupyter Notebooks on an Apple M1 Mac

Learn how to run Jupyter Notebooks on Apple M1 Macbooks.

5 Oct 2020 • 24 min read

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.

2 Oct 2020 • 4 min read

What is a Label Map?

In this post, we will demystify the label map by discussing the role that it plays in the computer vision annotation process. Then we will get hands on with some real life examples using a label map.

25 Sep 2020 • 4 min read

Getting Started with VGG Image Annotator for Object Detection Tutorial

SUMMARY VGG Image Annotator (VIA) is a free, browser-based labeling tool built by Oxford University researchers that supports bounding box and polygon annotations for object detection datasets. This tutorial covers the full workflow: creating a project, loading images, drawing annotations, assigning class labels, and exporting data, then converting the

22 Aug 2020 • 8 min read

How to Train a Custom Mobile Object Detection Model (with YOLOv4 Tiny and TensorFlow Lite)

Learn how to train a custom mobile object detection model with YOLOv4 tiny and TensorFlow Lite.

12 Aug 2020 • 14 min read

Deploy A Custom Model to the Luxonis OAK - A Quickstart Guide

This guide will take you the long distance from unlabeled images to a working computer vision model deployed and inferencing live at 15FPS on the affordable and scalable Luxonis OpenCV AI Kit (OAK) device.

28 Jul 2020 • 14 min read

Benchmarking the Major Cloud Vision AutoML Tools

Until now, there has been little independent research published on the performance of AutoML tools - (both relative to each other and against state of the art open source models)

27 Jul 2020 • 6 min read

VoTT for Image Annotation and Labeling

A guide on using VoTT to label your own computer vision dataset.

5 Jul 2020 • 1 min read

Roboflow vs Scale

SUMMARY Roboflow and Scale serve different stages of the computer vision pipeline: Scale and similar services (LabelBox, SuperAnnotate, SageMaker Ground Truth) handle outsourced annotation, while Roboflow takes over after labeling to manage preprocessing, augmentation, dataset versioning, and training integrations. Roboflow imports annotations directly from most of these services, and its

29 Jun 2020 • 15 min read

What is YOLOv5? A Guide for Beginners.

In this article, we discuss what is new in YOLOv5, how the model compares to YOLO v4, and the architecture of the new v5 model.