Torchvision Dependency Graph

Torchvision is used in Python projects. image and video datasets and models for torch deep learning It has 3 direct runtime dependencies. Check its dependency graph on PyDeps to understand the full transitive dependency tree, reverse dependents, known CVEs, and license compatibility before installing.

What is Torchvision used for?

image and video datasets and models for torch deep learning

Direct dependencies

Torchvision declares 3 direct runtime dependencies, each of which is resolved and rendered as an expandable node in the graph:

Transitive dependencies

Beyond its direct dependencies, Torchvision pulls in further packages through its dependency tree. PyDeps walks the entire chain from PyPI and deps.dev so you can see every transitive (nested) dependency, expand any node on demand, and understand the full set of code that ships when you install Torchvision.

Dependency risk and maintenance

Torchvision is distributed under the BSD license. Use the vulnerability panel, powered by the OSV database, to check whether Torchvision or anything in its dependency tree has known CVEs before you ship, and review the license of every dependency to confirm compatibility with your project.

How to read the dependency graph

In the interactive graph each node is a package and each edge is a version constraint. Expand a node to load its subdependencies, switch to the dependents view to see which packages rely on Torchvision, and download Torchvision together with all of its dependencies as wheels for offline or air-gapped installs.

Related packages

PyDeps