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Company updates & technology articles

Improved Image Viewer for 3D Point Cloud Labeling

Improved Image Viewer for 3D Point Cloud Labeling

Camera images provide important context when labeling 3D point clouds. Our improved image viewer makes it easier to view and use camera images for accurate and efficient labeling.

Tobias
Tobias

Image to Point Cloud with Point-E

Image to Point Cloud with Point-E

Generating point clouds is time-consuming. Learn how to use OpenAI's Point-E model to quickly create point clouds from images.

Arnaud
Arnaud

Zero-shot object detection with OWL-ViT

Zero-shot object detection with OWL-ViT

Regular object detection models are trained on a fixed set of categories. With zero-shot object detection you can detect object of any category without retraining.

Bert
Bert

Fast Point Cloud Labeling with Model Predictions

Fast Point Cloud Labeling with Model Predictions

Labeling point clouds is difficult and time-consuming. Learn how to set up model-assisted labeling and use model predictions to label faster.

Tobias
Tobias

10 Lidar Datasets for Autonomous Driving

10 Lidar Datasets for Autonomous Driving

Autonomous vehicles use lidar to see the world in 3D. Get an overview of automous driving datasets and learn how to create your own.

Tobias
Tobias

Introducing Text Labeling

Introducing Text Labeling

Use our new text labeling interfaces for named entity recognition (NER) and span categorization.

Arnaud
Arnaud

Introducing Autosegment

Introducing Autosegment

Our new Autosegment tool can automatically create segmentation masks for foreground objects. Use it to speed up your labeling.

Tobias
Tobias

Panoptic Segmentation: Introduction and Datasets

Panoptic Segmentation: Introduction and Datasets

Panoptic segmentation is the combination of instance and semantic segmentation. Get an overview of the public datasets available and learn how to create your own.

Tobias
Tobias

Create a Data-Centric ML Pipeline with W&B

Create a Data-Centric ML Pipeline with W&B

Set up a versioned ML pipeline with Weights and Biases & Segments.ai to iteratively improve datasets.

Tobias
Tobias

Supercharge your Image Segmentation Labeling with Superpixels 2.0

Supercharge your Image Segmentation Labeling with Superpixels 2.0

We’ve developed an ML-powered labeling tool called *Superpixels* to make image segmentation labeling faster and more accurate.

Bert
Bert

Customizable Hotkeys and more

Customizable Hotkeys and more

You know what's even better than hotkeys? Customizable hotkeys. Many of you requested this feature, and it has now finally arrived.

Bert
Bert

Automated Labeling Workflows with Webhooks

Automated Labeling Workflows with Webhooks

Summer break or not, we keep shipping new features at Segments.ai. Our highlight for this month is the release of the new webhook functionality, which makes it even easier to set up automated labeling workflows.

Bert
Bert

Better Reviewing and QA with Issues

Better Reviewing and QA with Issues

This month, Segments.ai saw lots of improvements regarding labeling functionality, developer experience and documentation. Our highlight in this update is the release of a much-requested feature to keep track of issues.

Bert
Bert

Speed up your Image Segmentation Workflow with Model-Assisted Labeling

Speed up your Image Segmentation Workflow with Model-Assisted Labeling

Building large-scale datasets is a time-consuming endeavour, especially for tasks like image segmentation where the labels need to be very precise. This tutorial shows how you can speed up your labeling workflow for image segmentation with Segments.ai, using model training in the loop.

Bert
Bert

Deploying PyTorch on AWS Lambda

Deploying PyTorch on AWS Lambda

Deploying PyTorch models cost-efficiently in the cloud is not straightforward. We investigate how to use the PyTorch library with AWS Lambda functions by implementing an image classifier as an example.

Davy
Davy