Skip to main content

11 posts tagged with "computer vision"

View All Tags

Unsupervised anomaly detection with Anomalib in Python

· 10 min read
Anthony Cavin
Co-founder & CEO - Data, ML & Robotics Systems

Anomaly detection pipeline: a camera feeds Anomalib, which scores each frame, and ReductStore keeps every frame with its anomaly labels

Anomalib makes it relatively easy to train an anomaly detection model on your own images. But once you want to use it in production, you also need to handle inference, evaluate predictions, and keep track of the images that triggered them.

In this tutorial, we'll use anomalib to train and run an anomaly detection model in Python. Then we'll look at how to store images alongside their anomaly scores, so you can review detections and use them for future training.

How to Store Images in ROS2

· 12 min read
Anthony Cavin
Co-founder & CEO - Data, ML & Robotics Systems

 

ROS2 is widely used for building robotic systems with sensors like cameras, LiDAR, and IMUs. While it's great for communication (e.g., publishing and subscribing to topics), it lacks a built-in solution for storing large amounts of unstructured data, such as images.

Bag files are commonly used to store data in ROS2, but they aren't a good fit for long-term storage or real-time streaming. They're mainly meant for recording and replaying mission data or episodes, not for managing large volumes of unstructured data.

Addressing this challenge, this blog post will guide you through setting up ROS2 with ReductStore a high-performance storage and streaming solution optimized for unstructured, time-series data.

We will focus specifically on image data, but if you are interested in a more general overview you can read How to Store and Manage Robotic Data which covers the challenges and strategies for storing and managing robotic data in general.

For the full code example, we will be using the reduct-ros-example repository, which provides a complete implementation of the concepts discussed in this article.

Store an H.264 Camera Stream and Export It as Playable MP4

· 7 min read
Anthony Cavin
Co-founder & CEO - Data, ML & Robotics Systems

Storing an H.264 stream in ReductStore and exporting it as MP4

Your robot has a camera. You are storing what it sees as one image per frame, and that works until someone asks to watch it. Then you write a script that extracts ten thousand JPEGs from storage, sorts them by timestamp, and calls ffmpeg. You write that script again the next time anyone wants thirty seconds of footage.

Storing the encoded stream removes that step. ReductStore stores H.264 chunks as time-indexed records, and the ReductVideo extension returns an MP4 you can open in a player.