Speech, vision & media
Kornia
Differentiable geometric vision operations that integrate directly into PyTorch pipelines.
Overview
Research summary
Kornia supplies computer vision operations that fit into tensor-based and differentiable machine-learning pipelines. Its Python modules cover image processing, geometric transformations, feature operations and augmentation, with additional models and utilities for modern vision workflows. Developers can combine these building blocks with PyTorch training or inference code while retaining access to automatic differentiation where supported.
It is useful for spatial AI, image matching, preprocessing and model experimentation rather than providing a single end-user vision application. The project includes examples and tutorials, and its library source is distributed under Apache-2.0.
Repository summary
- Stars
- 11,391
- Open issues
- Unavailable
- Last push
- 2026-10-01
- Commits, 90 days
- Unavailable
- Repository activity
- Not scored
- Version
- Unavailable
Recorded catalogue figures. View repository data and provenance →
Classification
Pricing & services
Paid services unknown
Whether the provider offers paid products or services has not been established.
Licence scope
Implementation
Recorded implementation details and interfaces for Kornia.
Implementation details
Python computer vision library built on PyTorch
- Languages
- Python
- Repository type
- source
Recorded interfaces and capabilities
Licence scope
Repository
Repository snapshots, release information and recorded maintenance signals.
Repository snapshot
- Stars
- 11,391
- Open issues
- Unavailable
- Last push
- 2026-10-01
- Commits, 90 days
- Unavailable
- Repository activity
- Not scored
- Archived
- Not recorded
Repository activity is a snapshot, not a quality or popularity ranking. It combines recent-push freshness (50%), 90-day commits (30%) and issue pressure (20%).
Maintenance and provenance
- Catalogue snapshot
- 2026-10-06
- Stars source
- Recorded fallback
- Last push source
- Recorded fallback
Documentation
Recorded references and research provenance for this entry.
Recorded sources 5
- https://www.kornia.org Project page
- https://github.com/kornia/kornia Linked repository · Research reference
- https://kornia.readthedocs.io Documentation
- https://github.com/kornia/kornia/blob/main/README.md Research reference
- https://github.com/kornia/kornia/blob/main/LICENSE Research reference
Research metadata
- Research date
- 2026-10-02
- Catalogue snapshot
- 2026-10-06