avalanche
trajectopy-core
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| avalanche | trajectopy-core | |
|---|---|---|
| 1 | 1 | |
| 1,666 | 1 | |
| 3.2% | - | |
| 9.4 | 9.2 | |
| 10 days ago | 9 days ago | |
| Python | Python | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
avalanche
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[R] Single-task Continual/Incremental/Online/Life-Long learning.
Lastly, there are several github repo, but the most popular one is ContinualAI/avalanche, which already implement some of above algorithm, for the purpose of reproducibility i.e. can be applied to your task (probably)
trajectopy-core
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Trajectory Evaluation in Python - Update
The first, called trajectopy, stands as a full-fledged application featuring a PyQt6-based graphical user interface (GUI). This GUI-driven platform simplifies trajectory-related tasks and offers an intuitive user experience. For those desiring a more in-depth approach, there is trajectopy-core. This backend implementation without any PyQt6 dependencies provides essential functionality e.g. for computing absolute trajectory error (ATE) and relative pose error (RPE).
What are some alternatives?
evaluate - 🤗 Evaluate: A library for easily evaluating machine learning models and datasets.
torch-fidelity - High-fidelity performance metrics for generative models in PyTorch
rexmex - A general purpose recommender metrics library for fair evaluation.
datasets - 🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
py-motmetrics - :bar_chart: Benchmark multiple object trackers (MOT) in Python
pytorch-accelerated - A lightweight library designed to accelerate the process of training PyTorch models by providing a minimal, but extensible training loop which is flexible enough to handle the majority of use cases, and capable of utilizing different hardware options with no code changes required. Docs: https://pytorch-accelerated.readthedocs.io/en/latest/
trajectopy - Trajectopy - Trajectory Evaluation in Python
ZnH5MD - ZnH5MD - High Performance Interface for H5MD Trajectories