Changelog
Protege Runtime release notes
v0.15.2 - 2025-06-24
Added
- Added
protege-telemetry
(for Otel to gcm) andprotege-common
(to remove dependency from protege-runtime) as a dependency in protege-engine
v0.15.1 - 2025-06-24
Added
Allow automatically converting polygons to keypoint coordinates
v0.15.0 - 2025-06-24
Fixed
- Removed unnecessary circular dependency
v0.14.9 - 2025-06-18
Fixed
- Update the pyproject.toml to support the latest versions of protege-pipelines and protege-runtime
v0.14.8 - 2025-06-18
Added
- Add protege-lineage as a dependency in protege-engine
v0.14.7 - 2025-05-29
Added
- Add .tool-versions with python 3.11.12
Changed
- Lock dependencies versions
- Use logging instead of print in scheduler to show the last learning rate
Removed
- Deleted local models directory, all models should be consumed from protege-common
- Remove deprecated argument verbose from
torch.optim.lr_scheduler.ReduceLROnPlateau
Fixed
- Fix missing dependencies on image build
- Force image platform version to linux/amd64 as osx defaults to arm64
v0.14.6 - 2024-03-26
Added
- Internal improvements
v0.14.2
Added
-
Initial externalization of
protege-engine
fromprotege-ml
, providing core execution and prediction logic for Protege-based models. -
Training Components
- Lightning-based trainer with export, logging, and scheduler utilities.
- Dataset and manifest management tools.
-
Model Zoo
- Support for classification, detection, segmentation, and keypoint models via TorchVision and custom wrappers.
-
CLI Interface
protege-package
CLI for packaging models and artifacts.
-
Dockerized Runtimes
- CUDA-enabled training runtime via
docker/Dockerfile.vertex
. - Release-focused Docker image with direct install from source.
- CUDA-enabled training runtime via
-
CI/CD Workflow
- Unit test matrix, GitHub release automation, Python wheel + Docker publishing, and documentation syncing.