Model Training

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

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

SUMMARY Transfer learning lets you apply weights a model learned on one problem to a related problem, cutting training time and reducing the labeled data you need to get started. In practice this means initializing from a model already trained on a large dataset like COCO or ImageNet, then fine-

28 Dec 2020 • 6 min read

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

SUMMARY This post walks through a Kaggle competition case study focused on detecting American football helmet impacts to help researchers understand conditions that contribute to traumatic brain injury. The authors use Scaled-YOLOv4, selected for its inference speed, and use Roboflow to preprocess and augment the provided training images. A

15 Dec 2020 • 6 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 • 5 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

SUMMARY Scaled-YOLOv4 set a new state-of-the-art result for object detection on the Microsoft COCO benchmark at the time of its publication, surpassing Google's EfficientDet across both the speed and accuracy ends of the performance frontier. The model achieves this by scaling the depth, stages,

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 • 6 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

SUMMARY Splitting a dataset into training, validation, and test sets is a core practice for detecting overfitting and ensuring a computer vision model generalizes beyond its training examples. Roboflow defaults to a 70/20/10 split at upload time but gives you direct control: you can assign individual image batches

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.

24 Jun 2020 • 9 min read

How to Train Detectron2 on Custom Object Detection Data

Learn how to train a Detectron2 model on a custom object detection dataset.

13 May 2020 • 7 min read

Data Augmentation in YOLOv4

Learn how data augmentation is used in training YOLOv4 computer vision models.