Model Training

17 May 2021 • 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

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

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

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?

Using 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, and "things" it

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?

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

14 Mar 2021 • 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

12 Feb 2021 • 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.

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.

31 Jan 2021 • 3 min read

Using Computer Vision to Win at Duck Hunt

Can we use object detection to automate identifying moving objects on a screen? Abhinav Mandava leverages Roboflow to create an aimbot (which automates aiming and firing for the player) for Duck Hunt.

13 Jan 2021 • 4 min read

A Primer on Transfer Learning

Transfer learning is a machine learning (ML) technique where knowledge gained during training a set of problems can be used to solve other related problems. It’s very similar to the concept of reusing code in computer programming, except instead of sharing code between different applications or software projects, we’

8 Jan 2021 • 5 min read

How to Try CLIP: OpenAI's Zero-Shot Image Classifier

Earlier this week, OpenAI dropped a bomb on the computer vision world.

28 Dec 2020 • 5 min read

Football, Kaggle, Roboflow: Using Computer Vision to Tackle Helmet Safety

If you're searching for a dataset to use or are looking to improve your data science modeling skills, Kaggle is a great resource for free data and for competitions. For example, there's currently an open Kaggle competition detecting American football helmet impacts (crashes) in which you

15 Dec 2020 • 5 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.

15 Dec 2020 • 4 min read

Apple's M1 is up to 3.6x as fast at training machine learning models

We compared the Apple M1 chip to the Intel Core i5 chip on an object detection task using Create ML.

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

16 Nov 2020 • 6 min read

Google Researchers Say Underspecification is Ruining Your Model Performance. Here's Five Ways to Fix That.

We read that Google underspecification paper so you don't have to.

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.

28 Oct 2020 • 2 min read

Train Test Split Guide and Overview

In order to ensure our models are generalizing well (rather than memorizing training data), it is best practice to create a train, test split. That is, absent rigor, our models can easily overfit to a small subset of examples we've collected. Look no further than Tesla using computer

25 Oct 2020 • 5 min read

How to Save and Load Model Weights in Google Colab

Google Colab is Google's hosted Jupyter Notebook product that provides a free compute environment, including GPU and TPU. Colab comes "batteries included" with many popular Python packages installed, making it a choice tool for easy model experimentation. For this reason, the Roboflow Model Library includes many

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.