{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/8"}],"enrichment":{"capability":"Computes Fr\u00e9chet Inception Distance (FID), a metric for measuring similarity between two image datasets using PyTorch and the Inception network.","skillfed_tags":["generative-models","image-metrics","evaluation"],"use_cases":["Evaluate generative adversarial network (GAN) sample quality during training or model comparison","Measure similarity between real and synthetic image datasets for validation","Pre-compute and cache statistics from a reference dataset to benchmark multiple models against it","Compare image generation models using a standardized metric that correlates with human visual quality judgment","Use lower-dimensional Inception features when comparing datasets with fewer than 2048 images"],"what_it_does":"pytorch-fid is a PyTorch implementation of the Fr\u00e9chet Inception Distance metric, originally developed to evaluate generative model quality by measuring statistical distance between real and generated image distributions. It computes FID by fitting Gaussians to feature representations extracted from the Inception network and calculating the Fr\u00e9chet distance between them.\n\nThe package provides a command-line interface to compute FID scores between two image folders, with options to use different Inception layers (64, 192, 768, or 2048 dimensions) and GPU acceleration. It can also pre-compute and cache dataset statistics as .npz files for repeated comparisons. The weights and model match the official implementation, though results may differ slightly due to image interpolation and backend differences.","worth_installing":"Yes, if you need FID evaluation for generative models in PyTorch. The package is stable, permissively licensed, and has low install friction. However, maintenance is dormant (last release January 2023); verify current compatibility with your PyTorch version first. Results differ slightly from the original implementation, so check whether exact reproducibility matters for your use case."},"id":"pytorch-fid","links":{"html":"https://skillfed.io/packages/pytorch-fid","md":"https://skillfed.io/packages/pytorch-fid.md","pypi":"https://pypi.org/project/pytorch-fid/"},"maintenance":{"status":"dormant"},"meta":{"latest_release":"2023-01-05","license_spdx":null,"license_treatment":"permissive","name":"pytorch-fid","python_support":"supports_current","summary":"Package for calculating Frechet Inception Distance (FID) using PyTorch"},"popularity":{"monthly_downloads":153171,"position":10886,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.3.0"}