avalanche
torch-fidelity
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| avalanche | torch-fidelity | |
|---|---|---|
| 1 | 3 | |
| 1,666 | 870 | |
| 3.2% | - | |
| 9.4 | 8.1 | |
| 10 days ago | 3 months ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 or later |
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)
torch-fidelity
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[D] A better way to compute the Fréchet Inception Distance (FID)
The Fréchet Inception Distance (FID) is a widespread metric to assess the quality of the distribution of a image generative model (GAN, Stable Diffusion, etc.). The metric is not trivial to implement as one needs to compute the trace of the square root of a matrix. In all PyTorch repositories I have seen that implement the FID (https://github.com/mseitzer/pytorch-fid, https://github.com/GaParmar/clean-fid, https://github.com/toshas/torch-fidelity, ...), the authors rely on SciPy's sqrtm to compute the square root of the matrix, which is unstable and slow.
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[D] Are there any good FID and KID metrics implementations existing that are compatible with pytorch?
Try torch-fidelity : https://github.com/toshas/torch-fidelity
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How to compute Inception score for 3d GAN
You can, but two ingredients are required: a rich pretrained feature extractor for your data to replace InceptionV3 pretrained on ImageNet, and https://github.com/toshas/torch-fidelity, which can be used with custom feature extractors (also supports FID and KID).
What are some alternatives?
evaluate - 🤗 Evaluate: A library for easily evaluating machine learning models and datasets.
datasets - 🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
rexmex - A general purpose recommender metrics library for fair evaluation.
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/
pytorch-fid - Compute FID scores with PyTorch.
clean-fid - PyTorch - FID calculation with proper image resizing and quantization steps [CVPR 2022]
trajectopy - Trajectopy - Trajectory Evaluation in Python
trajectopy-core - Trajectopy - Trajectory Evaluation in Python
continuum - A clean and simple data loading library for Continual Learning