• 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
• 1 min read
What is Amazon Rekognition?
"ML in a Minute" is our conversational series on answering machine learning
questions. Have questions you want answered? Tweet at us
[https://www.youtube.com/watch?v=vZX0rcJl8o8&list=PLZCA39VpuaZZrOVZEu0x8EQqfQdUDzjM2&index=2]
.
What is Amazon Rekognition (in 60 Seconds or Fewer)?
Amazon's Rekognition is
• 1 min read
What is AutoML?
"ML in a Minute" is our conversational series on answering machine learning
questions. Have questions you want answered? Tweet at us
[https://www.youtube.com/watch?v=vZX0rcJl8o8&list=PLZCA39VpuaZZrOVZEu0x8EQqfQdUDzjM2&index=2]
.
What is AutoML (in 60 Seconds or Fewer)?
AutoML, "automated machine learning,"
• 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.
• 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.
• 6 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.
• 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.
• 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.
• 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.
• 7 min read
Building vs. Buying a Computer Vision Platform
“You could do what Roboflow does yourself but…why would you?”
-Jack Clark, Co-Founder of Anthropic [https://www.anthropic.com/], former Policy
Directory at OpenAI [https://openai.com/],
It’s no secret that building a computer vision model on your own is hard work.
It requires wrangling together different platforms,
• 4 min read
How to Train with Microsoft Azure Custom Vision and Roboflow
Roboflow is a tool for building robust machine learning operations pipelines for
computer vision: from collecting and organizing images, annotating, training,
deploying, and creating active learning [https://blog.roboflow.com/what-is-active-learning/]
pipelines to rapidly create improved model performance.
When it comes to the training step, developers should optimize for ease.
• 5 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.
• 4 min read
Prompt Engineering: The Magic Words to using OpenAI's CLIP
Featuring rock, paper, scissors.
OpenAI's CLIP model [https://models.roboflow.com/classification/clip]
(Contrastive Language-Image Pre-Training) is a powerful zero-shot classifier
that leverages knowledge of the English language to classify images without
having to be trained on any specific dataset.
In other words, CLIP already knows a lot
• 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.
• 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.
• 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.
• 8 min read
The power of image augmentation: an experiment
One of the amazing things about computer vision is using existing images plus
random changes to increase your effective sample size. Suppose you have one
photo containing a coffee mug. Then, copy that photo and rotate it 10 degrees
clockwise. From your point of view, you haven’t done very
• 3 min read
Image Augmentations for Aerial Datasets
Learn how to apply image augmentations to aerial datasets for use in training computer vision models.
• 4 min read
How important is subject similarity for transfer learning?
Using transfer learning
[https://blog.roboflow.com/a-primer-on-transfer-learning/] to initialize your
computer vision model from pre-trained weights rather than starting from scratch
(initializing randomly) has been shown to increase performance and decrease
training time. It makes sense, by giving your model prior knowledge about basic
concepts like lines, curves, textures,
• 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.
• 4 min read
What is Embedded Machine Learning?
Machine learning – the software discipline of mapping inputs to outputs without
explicitly programmed relationships – requires substantial computational
resources. Traditionally, this limits where machine learning models can run to
very powerful supercomputers. But this is changing.
Computation is required at two core moments in the machine learning development
lifecycle: model training
• 8 min read
How We Built Paint.wtf, an AI Game with 150,000+ Submissions that Judges Your Art
Paint.wtf is an online game that uses AI to score user-submitted digital drawings to zany prompts like, "Draw a giraffe in the arctic" or "Draw a bumblebee loves capitalism." It's Cards Against Humanity meets Microsoft Paint.
Paint.wtf became an internet sensation. In
• 4 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.
• 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.
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