Blog

Kelly M.

Kelly has a background in both software engineering and data science and is a Developer Advocate at Roboflow.

Latest Posts by Kelly M.

Launch: Instance Segmentation Project Training and Inference

19 May 2022 • 1 min read

Launch: Instance Segmentation Project Training and Inference

What Is Instance Segmentation? Instance segmentation, also known as image segmentation, is the computer vision task of recognizing objects in images along with their associated shape. In other words, it is the outline of a given object. It also includes a bounding box surrounding the object in addition to its

How to Train a YOLOv5 Oriented Bounding Box Model

11 May 2022 • 3 min read

How to Train a YOLOv5 Oriented Bounding Box Model

Learn how to train a YOLOv5 Oriented Bounding Box (OBB) object detection model.

cinco de mayo multi-label classification

5 May 2022 • 3 min read

Cinco de Mayo, Beer and Taco Dataset with Multi-Label Classification

Happy Cinco de Mayo! In honor of the holiday, we created and trained a multi-label classification dataset to detect some favorite edibles used to celebrate the holiday here in the United States. Because we know it’s not just about tacos and beer, we also want to briefly share a

Building a U.S. License Plate Detection Model And Sharing It On Roboflow Universe

8 Mar 2022 • 5 min read

Building a U.S. License Plate Detection Model And Sharing It On Roboflow Universe

The newest project featured on Roboflow Universe is a U.S. License Plate dataset and model with images collected from Google images and around Central Florida parks. This dataset and model can be used for cases like: 1. Police work 2. Toll roads 3. Bank drive-throughs 4. Fast food drive

How To Avoid Bias In Computer Vision Models

14 Feb 2022 • 5 min read

How To Avoid Bias In Computer Vision Models

There are two different ways to think about algorithmic bias, and they are complementary to one another. The first being the social and ethical side, and second being the more technical side, how we detect it, and mitigate it. Today we’re going to dive into the technical side of

How to Train Computer Vision Models on Aerial Imagery

7 Feb 2022 • 7 min read

How to Train Computer Vision Models on Aerial Imagery

Aerial imagery are images taken from aircrafts like drones, planes, and helicopters. With these images we can train a model to detect objects like fires, buildings, solar panels, rooftops, maritime search and rescue, and more. A good use case example is when maritime search and rescue (SAR) teams search for

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