Visual Object Tagging Tool from Microsoft for labelling images and video frames, exporting annotations in formats consumed by common object detection trainers. Built and maintained by WIEWAVE for Azure Marketplace, on Ubuntu and Debian.
| Built & maintained by | WIEWAVE |
|---|---|
| Category | AI & Machine Learning |
| Operating systems | Ubuntu, Debian |
| Marketplaces | Azure Marketplace |
| Offer types | Public listing, with private offers on request |
| Marketplace | Status |
|---|---|
| Azure Marketplace | Published |
| AWS Marketplace | Available on request |
| Google Cloud Marketplace | Available on request |
Need it on another marketplace, or as a private offer for your organisation? cloud@wiewave.com
Each image follows its distribution's own provisioning model, package manager and security tooling — not one build relabelled several times.
LTS and interim releases, Minimal and Pro variants, built to Canonical's cloud-image conventions.
Stable and oldstable, with backports where a workload needs a newer runtime than the release ships.
The same four steps behind every offer we've published, including the hardening and CIS Benchmark checks every build goes through.
The distribution, licensing model and target marketplaces are agreed before anything is built.
Packer templates, Ansible provisioning and a pinned package set — then hardened, scanned and checked against the CIS Benchmark for its distribution.
Taken through each cloud's own certification pipeline before it goes live on the marketplace.
Rebuilt on the upstream security cadence and re-published, with old versions retired without breaking deployments.
If yours isn't here, ask our marketplace team directly.
GPU-ready training and inference images with drivers, CUDA and frameworks already matched to each other.
Fast online machine learning library supporting contextual bandits, reinforcement learning and large-scale linear models trained from streaming input files.
Convolutional neural network upscaler that enlarges and denoises anime-style artwork and photographs, with command line and web interfaces for batch jobs.
Self-supervised speech representation model from Meta for automatic speech recognition, packaged with PyTorch, fairseq or Transformers and pretrained checkpoints.
Gradient boosting library for regression, classification and ranking tasks, preinstalled with Python bindings and the scientific stack needed to train tree ensembles.
Pretrained autoregressive transformer model for NLP tasks such as classification and question answering, packaged with PyTorch and the Transformers library.
Open-source toolkit supplied as a preconfigured image; consult the upstream project documentation for the exact functionality, dependencies and usage of this build.
Tell us the distribution, the marketplace and the commercial model — we'll build, certify and publish it as a public listing or a private offer.
