Model Training

20 Sep 2021 • 1 min read

What is PyTorch?

SUMMARY PyTorch is Facebook's open-source machine learning framework, originally popularized in academic research and now widely used in production systems. It provides the foundational building blocks for deep learning across computer vision, natural language processing, and audio, and serves as the base for higher-level frameworks like

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

23 Aug 2021 • 3 min read

What is Zero Shot Object Tracking?

We are exciting to announce that you can now track objects frame over frame in video and camera stream using the Roboflow Inference API and the open source zero shot object tracking repository, without having to train a separate classifier for your object track features.

6 Aug 2021 • 3 min read

Transformers Take Over Object Detection

It seemed just like a matter of time... and now the Transformers neural networks have landed - Microsoft's DyHead achieves state of the art object detection using a Transformer backbone.

2 Aug 2021 • 7 min read

How to Train YOLOX On a Custom Dataset

The YOLO family continues to grow with the next model: YOLOX. In this post, we will walk through how you can train YOLOX to recognize object detection data for your custom use case.

2 Jul 2021 • 7 min read

How to Train YOLOR on a Custom Dataset

The YOLO family recently got a new champion - YOLOR: You Only Learn One Representation. In this post, we will walk through how you can train YOLOR to recognize object detection data for your custom use case.

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 • 6 min read

How to Train MobileNetV2 On a Custom Dataset

In this post, we will walk through how you can train MobileNetV2 to recognize image classification data for your custom use case.

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,

13 Jun 2021 • 5 min read

How to Train with Microsoft Azure Custom Vision and Roboflow

SUMMARY Teams with existing Microsoft Azure credits can route their Roboflow datasets directly into Azure Custom Vision for training by linking API keys once at the workspace level. After that connection is established, any versioned Roboflow dataset (including preprocessing and augmentation steps applied in Roboflow) can be exported to Azure

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.

17 May 2021 • 4 min read

Prompt Engineering: The Magic Words to using OpenAI's CLIP

SUMMARY OpenAI's CLIP model performs zero-shot image classification by matching text prompts to image content, but the exact wording of each prompt has a significant effect on accuracy. This post walks through that sensitivity using a rock, paper, scissors hand-sign dataset, showing how prompts like "

14 May 2021 • 10 min read

License Plate Detection and OCR using Roboflow Inference API

In this post, we’ll walk you through creating a license plate detection and OCR model using Roboflow that you can programmatically use for your own projects.

11 May 2021 • 4 min read

PP-YOLO Strikes Again - Record Object Detection at 68.9FPS

Object detection research is white hot! In the last year alone, we've seen the state of the art reached by YOLOv4, YOLOv5, PP-YOLO, and Scaled-YOLOv4. And now Baidu releases PP-YOLOv2, setting new heights in the object detection space.

5 May 2021 • 8 min read

How to Train and Deploy Custom Models to Your OAK

In this blog, we'll walk through the Roboflow custom model deployment process to the OAK and show just how seamless it can be.

3 May 2021 • 8 min read

The power of image augmentation: an experiment

SUMMARY Image augmentation increases effective training set size by applying random transformations to existing images, but knowing how much to augment and which transforms to apply depends on your dataset. This experiment tests three variables across three public datasets of different sizes (26, 196, and 665 images of packages, raccoons,

26 Apr 2021 • 3 min read

Image Augmentations for Aerial Datasets

Learn how to apply image augmentations to aerial datasets for use in training computer vision models.

11 Apr 2021 • 4 min read

How important is subject similarity for transfer learning?

SUMMARY An experiment comparing four transfer learning starting points on a mask-wearing detection dataset reveals that domain similarity matters more than pretraining scale. A checkpoint pretrained on WIDER Face (a face-focused dataset) outperformed the COCO-pretrained baseline despite COCO containing far more images and categories, while a blood-

28 Mar 2021 • 6 min read

Zero-Shot Content Moderation with OpenAI's New CLIP Model

Learn how to use the CLIP zero-shot model to moderate visual content.

20 Mar 2021 • 4 min read

What Is Embedded Machine Learning?

SUMMARY Embedded machine learning is the practice of running inference directly on microcontrollers and low-power hardware, such as a Raspberry Pi, NVIDIA Jetson, or Luxonis OAK, rather than sending data to a cloud server. Shrinking model sizes and cheaper, faster hardware have made this practical: inference requires far fewer

14 Mar 2021 • 9 min read

How We Built Paint.wtf, an AI Game with 150,000+ Submissions that Judges Your Art

SUMMARY Paint.wtf is an online drawing game built by Roboflow and Booste that uses OpenAI's CLIP model to score user submissions against absurdist text prompts, ranking drawings by how closely their image embeddings match the prompt's text embedding. GPT-2 generated the bulk of the

12 Feb 2021 • 5 min read

Liquid Neural Networks in Computer Vision

Excitement is building in the artificial intelligence community around MIT's recent release of liquid neural networks. The breakthroughs that Hasani and team have made are incredible. In this post, we will discuss the new liquid neural networks and what they might mean for the vision field.

8 Feb 2021 • 7 min read

How to Train and Deploy a License Plate Detector to the Luxonis OAK

In this post, we will leverage Roboflow and the Luxonis OAK to train and deploy a custom license plate model to your OAK device.