v1.1.11

⭐ Update v1.1.11: What's new?

• Fix minor bug in DataLoader causing VPRTempo to hang after inference, fixes for both CUDA and MPS environments.

What's changed?

Full Changelog: v1.1.10...v1.1.11

v1.1.10

⭐ Update v1.1.10: What's new?

• Include pixi for easier and reproducible installation of dependencies
• Fix old, large blobs in git history causing repo size to be >75MB

What's changed?

Full Changelog: v1.1.9...v1.1.10

v1.1.9

⭐ Update v1.1.9: What's new?

• Minor bug fixes for ground truth and similarity matrix generation for image skipping 🐛

What's Changed

• v1.1.9 by @AdamDHines in #19

Full Changelog: v1.1.8...v1.1.9

v1.1.8

⭐ Update v1.1.8: What's new?

• Provided support for MPS Apple Silicon 🍏
• Minor bug fixes in evaluation metrics 🐛
• New auto-downloader for pre-trained models and Nordland image subsets for easier trialling 📡

What's Changed

• 1.1.8 by @AdamDHines in #17

Full Changelog: v1.1.5...v1.1.8

v1.1.7

Fixed PyPi package bug

Had incidentally left scikit-python in and omitted matplotlib from the PyPi package.
Small fix in VPRTempo data loader to remove the shuffle argument.

v1.1.6

Updates in v1.1.6

• Modified information for the Oxford RobotCar dataset
• Removed activation layers inbetween linear feature and output layers which improves performance
• Allow users to skip the first n number of images in a dataset easier with the --skip argument
• Split .csv files for image loading into unique dataset directories, better flexibility for datasets without matching image names

What's Changed

• nn.Sequential fix by @AdamDHines in #13
• Lfs update & removal by @AdamDHines in #16

Full Changelog: v1.1.5...v1.1.6

v1.1.5

Bugs fixed in v1.1.5

• Issue with large models and CUDA, previous version loaded all models at once using CUDA memory very quickly. FIX: Models are initialized and stored on CPU after creation, moved back to CUDA when training/inferencing. This will have impact on inferencing performance since models are being moved back and forward from CPU<->GPU but this only affects very large models.

Features added in v1.1.5

• Easier installation with conda-forge packaging, can now simply install with conda install vprtempo -c conda-forge
• Added options to plot metrics, similarity matrices, and additionally output precision and recall in json file
• Modified model names so that they're clearer, also rather than model names simply being network architecture dims more information such as the datasets themselves included so multiple models with the same architecture can be trained across different datsets without overwriting them.

v1.1.4

Modify __init__ imports, change version number

v1.1.3

• Modified codebase into a singular module
• Easing module import (e.g. for blitnet, metrics, etc)
• Needed for conda-forge deployment

v1.1.2

Fixing repo structure for conda-forge release