SLEAP-NN v0.0.2

Summary

This release focuses on several bug fixes and improvements across the training, inference, and CLI components of sleap-nn. It includes bug fixes for model backbones and loaders, enhancements to the configuration and CLI experience, improved robustness in multi-GPU training, and new options for device selection and tracking. Documentation and installation guides have also been updated, along with internal refactors to streamline the code consistency.

Major changes

• Backbones & Models:

  • Fixed bugs in Swin Transformer and UNet backbone filter computations.
  • Corrected weight mapping for legacy TopDown ID models.

• Inference & Tracking:

  • Removed unintended loading of pretrained weights during inference.
  • Fixed inference with suggestion frames and improved stalling handling.
  • Added option to run tracking on selected frames and video indices.
  • Added thread-safe video access to prevent backend crashes.
  • Added function to load metrics for better evaluation reporting.

• Training Pipeline:

  • Fixed bugs in the training workflow with the infinite dataloader handling.
  • Improved seeding behavior for reproducible label splits in multi-GPU setups.
  • Fixed experiment run name generation across multi-GPU workers.

• CLI & Config:

  • Introduced unified sleap-nn CLI with subcommands (train, track, eval) and more robust help injection.
  • Removed deprecated CLI commands and cleaned up legacy imports.
  • Added option to specify which devices to use, with auto-selection of GPUs based on available memory.
  • Updated sample configs and sleap-io skeleton function usage.
  • Minor parameter name and default updates for consistency with SLEAP.

• Documentation & Installation:

  • Fixed broken documentation pages and improved menu structure.
  • Updated installation instructions with CUDA support for uv-based workflows.

What's Changed

• Fix Bug for SwinT Backbone Model by @7174Andy in #304
• More robust help injection in CLI by @tom21100227 in #303
• Remove loading pretrained weights during inference pipeline by @gitttt-1234 in #305
• Remove back import in lightning module by @gitttt-1234 in #312
• Fix compute filters in unet by @gitttt-1234 in #313
• Update CLI commands by @gitttt-1234 in #314
• Update sleap-io skeleton functions usage by @gitttt-1234 in #315
• Minor updates to config parameters by @gitttt-1234 in #316
• Minor bug fixes by @gitttt-1234 in #317
• Fix Inference on SuggestionFrames by @7174Andy in #318
• Add pck to voc metrics by @gitttt-1234 in #320
• Fix bugs in training pipeline by @gitttt-1234 in #322
• Add option to specify which devices to use by @gitttt-1234 in #327
• Fix bug in infinite data loader by @gitttt-1234 in #325
• Add thread-safe video access by @gitttt-1234 in #326
• Fix bugs in docs by @gitttt-1234 in #319
• Change zmq address to port arguments by @gitttt-1234 in #328
• Add option to run tracking on select frames by @gitttt-1234 in #329
• Fix seeding in training workflow by @gitttt-1234 in #330
• Fix inference stalling by @gitttt-1234 in #331
• Make wandb artifact logging optional by @gitttt-1234 in #332
• Auto-select GPUs by @gitttt-1234 in #333
• Add function to load metrics by @gitttt-1234 in #334
• Fix experiment run name in multi-gpu training by @gitttt-1234 in #336
• Add option to pass labels and video objects by @gitttt-1234 in #337
• Fix mapping for legacy topdown id models by @gitttt-1234 in #339
• Modify uv installation docs for cuda support by @gitttt-1234 in #340
• Update sample configs by @gitttt-1234 in #338
• Bump up sleap-nn version for v0.0.2 by @gitttt-1234 in #341

Full Changelog: v0.0.1...v0.0.2