Blog

Jacob Solawetz

Founding Engineer @ Roboflow - ascending the 1/loss

Latest Posts by Jacob Solawetz

Scaled-YOLOv4 is Now the Best Model for Object Detection

3 Dec 2020 • 8 min read

Scaled-YOLOv4 is Now the Best Model for Object Detection

(based on Microsoft COCO benchmarks) The object detection space remains white hot with the recent publication of Scaled-YOLOv4 [https://arxiv.org/abs/2011.08036], establishing a new state of the art in object detection [https://blog.roboflow.com/object-detection/]. Looking to train a Scaled-YOLOv4 model? Skip this post and jump

Revamping Train, Validation, Test, Split Management

20 Nov 2020 • 2 min read

Revamping Train, Validation, Test, Split Management

Splitting data into train, validation, and test splits is essential to building good computer vision models. Today, we are announcing in-app changes to Roboflow that make it even easier to manage your train test splits as you are working through the computer vision workflow.

YOLOv4 - Ten Tactics to Build a Better Model

13 Nov 2020 • 5 min read

YOLOv4 - Ten Tactics to Build a Better Model

The YOLO v4 repository is currently one of the best places to train a custom object detector, and the capabilities of the Darknet repository are vast. In this post, we discuss and implement ten advanced tactics in YOLO v4 so you can build the best object detection model from your custom dataset.

Occlusion Techniques in Computer Vision

6 Nov 2020 • 4 min read

Occlusion Techniques in Computer Vision

Computer vision models learn to model a task from a training set, however, like all deep learning models, they are prone to overfit the data they have been shown, making poor inferences in the wild. Computer vision models, like all machine learning models [https://blog.roboflow.com/computer-vision-model-tradeoff/], tend overfit

Luxonis OAK-D - Deploy a Custom Object Detection Model with Depth

26 Oct 2020 • 6 min read

Luxonis OAK-D - Deploy a Custom Object Detection Model with Depth

We are pretty excited about the Luxonis OpenCV AI Kit (OAK-D) device at Roboflow, and we're not alone. Our excitement has naturally led us to create another tutorial on how to train and deploy a custom object detection model leveraging Roboflow and DepthAI, to the edge, with depth, faster.

An Introduction to the COCO Dataset

18 Oct 2020 • 7 min read

An Introduction to the COCO Dataset

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

Introducing an Improved Shear Augmentation

12 Oct 2020 • 2 min read

Introducing an Improved Shear Augmentation

Today, we introduce a new and improved shear augmentation. We'll walk through some details on the change, as well as some intuition and results backing up our reasoning.

Glossary of Common Computer Vision Terms

5 Oct 2020 • 23 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.

What is a Label Map?

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.

Getting Started with VGG Image Annotator for Object Detection Tutorial

25 Sep 2020 • 3 min read

Getting Started with VGG Image Annotator for Object Detection Tutorial

Annotating your images is easy using the free, open source VGG Image Annotator. In this post we will walk through the steps necessary to get up and running with the VGG Image Annotator so you can quickly, and efficiently label your computer vision dataset for object detection [https://blog.roboflow.

Deploy YOLOv5 to Jetson Xavier NX at 30FPS

10 Sep 2020 • 3 min read

Deploy YOLOv5 to Jetson Xavier NX at 30FPS

Learn how to deploy a YOLOv5 model to a Jetson Xavier NX edge device.

Train, Validation, Test Split for Machine Learning

4 Sep 2020 • 6 min read

Train, Validation, Test Split for Machine Learning

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.

Use Resnet34 for Image Classification

3 Sep 2020 • 7 min read

Use Resnet34 for Image Classification

Can a computer tell the difference between a dandelion and a daisy? In this post we put these philosophical musings aside, and dive into the the code necessary to find the answer. We walk through the steps necessary to train a custom image classification model from the Resnet34 backbone using

Fast.ai v2 Released - What's New?

28 Aug 2020 • 4 min read

Fast.ai v2 Released - What's New?

Fastai, the popular deep learning framework and MOOC releases fastai v2 with new improvements to the fastai library, a new online machine learning course, and new helper repositories. fastai's layered architecture (cite [https://www.mdpi.com/2078-2489/11/2/108/htm])In this post, we will dive into

How to Train a Custom TensorFlow Lite Object Detection Model

17 Aug 2020 • 5 min read

How to Train a Custom TensorFlow Lite Object Detection Model

Learn how to train a custom TensorFlow Lite object detection model with a custom dataset.

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

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.

PP-YOLO Surpasses YOLOv4 - State of the Art Object Detection Techniques

3 Aug 2020 • 7 min read

PP-YOLO Surpasses YOLOv4 - State of the Art Object Detection Techniques

Baidu publishes PP-YOLO and pushes the state of the art in object detection research by building on top of YOLOv3, the PaddlePaddle deep learning framework, and cutting edge computer vision research.

How to Train an EfficientNet Model with a Custom Dataset

30 Jul 2020 • 8 min read

How to Train an EfficientNet Model with a Custom Dataset

Learn how to train an EfficientNet model with a custom dataset.

Benchmarking the Major Cloud Vision AutoML Tools

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)

VoTT for Image Annotation and Labeling

27 Jul 2020 • 6 min read

VoTT for Image Annotation and Labeling

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

How to Train a TensorFlow 2 Object Detection Model

16 Jul 2020 • 8 min read

How to Train a TensorFlow 2 Object Detection Model

Learn how to train a TensorFlow 2 object detection model on a custom dataset.

The TensorFlow 2 Object Detection Library is Here

14 Jul 2020 • 3 min read

The TensorFlow 2 Object Detection Library is Here

The TensorFlow Object Detection API [https://roboflow.com/formats/tensorflow-object-detection-csv] has been upgraded to TensorFlow 2.0. We discuss here what the new library means for computer vision developers [https://roboflow.com] and why we are so excited about the new TensorFlow 2.0 Object Detection library! TensorFlow2 meets the

What are Anchor Boxes in Object Detection?

13 Jul 2020 • 3 min read

What are Anchor Boxes in Object Detection?

Learn what anchor boxes are and why they are used in object detection.

Convert Supervisely Annotations in Two Minutes

10 Jul 2020 • 5 min read

Convert Supervisely Annotations in Two Minutes

In this post, we walk through how to download data from Supervise.ly and convert Supervise.ly annotations [https://roboflow.com/formats/supervisely-json] to YOLO Darknet format [https://roboflow.com/formats/yolo-darknet-txt] specifically, and more generally convert Supervisely JSON [https://roboflow.com/formats/supervisely-json] to any other object detection annotation

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