The Red Hat Ecosystem Catalog is the official source for discovering and learning more about the Red Hat Ecosystem of both Red Hat and certified third-party products and services.
We’re the world’s leading provider of enterprise open source solutions—including Linux, cloud, container, and Kubernetes. We deliver hardened solutions that make it easier for enterprises to work across platforms and environments, from the core datacenter to the network edge.
The PerceptiLabs Operator creates and maintain PerceptiLabs, a visual modeling tool for machine learning at warp speed.
PerceptiLabs visual modeling tool provides a GUI for building, training, and assessing your models, while also enabling deeper development with code. You get faster iterations and better explainability of the results.
For more information visit perceptilabs.com.
Features
Fast modeling
Make changes, debug, and tune your model through the GUI or custom code editor where every component/layer is re-programmable. Choose from multiple neural network models as well as classical AI methods.
Transparency of Model Performance and Results
Get instant feedback into your model’s performance through the visualization of the architecture, to better review and understand the results. See real-time analytics in every operation and variable, and granular previews of output from each model component.
Flexibility
Customize your environment and statistics dashboard. Use high-level abstractions or low-level code. Choose a local or cloud-based version. Execute any custom Python code or export a fully-trained TensorFlow model to perform inference in your projects.
The following information was extracted from the containerfile and other sources.
Summary | This is the free version of the backend of our modelling platform v1. |
Description | The Universal Base Image is designed and engineered to be the base layer for all of your containerized applications, middleware and utilities. This base image is freely redistributable, but Red Hat only supports Red Hat technologies through subscriptions for Red Hat products. This image is maintained by Red Hat and updated regularly. |
Provider | PerceptiLabs AB |
Maintainer | contact@perceptilabs.com |
The following information was extracted from the containerfile and other sources.
Repository name | PerceptiLabs-Modelling-Backend |
Image version | 0.11.5 |
Architecture | amd64 |
Exposed ports | ["8011/tcp" "5000/tcp"] |
User | 1001 |
Use the following instructions to get images from a Red Hat container registry using registry service account tokens. You will need to create a registry service account to use prior to completing any of the following tasks.
First, you will need to add a reference to the appropriate secret and repository to your Kubernetes pod configuration via an imagePullSecrets field.
Then, use the following from the command line or from the OpenShift Dashboard GUI interface.
Use the following command(s) from a system with podman installed
Use the following command(s) from a system with docker service installed and running
Use the following instructions to get images from a Red Hat container registry using your Red Hat login.
For best practices, it is recommended to use registry tokens when pulling content for OpenShift deployments.
Use the following command(s) from a system with podman installed
Use the following command(s) from a system with docker service installed and running