{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/7"}],"enrichment":{"capability":"Resizes images or tensors in NumPy or PyTorch with differentiable operations, supporting anti-aliasing, multiple interpolation methods, and flexible scale-factor or output-size specification.","skillfed_tags":["image-processing","differentiable-ops","abandoned"],"use_cases":["Preprocessing images for super-resolution models where consistent scale-factor and output-size handling is critical for training stability.","Downscaling high-resolution images while preserving detail through anti-aliasing, avoiding artifacts common in other resizing libraries.","Building differentiable image processing pipelines where gradients must flow through the resizing operation.","Implementing zero-shot super-resolution or other learning-based image enhancement tasks requiring precise, centered resizing.","Batch processing large tensors efficiently using convolution-based resizing when scale-factors are rational with small numerators."],"what_it_does":"ResizeRight is a tensor resizing library designed for machine learning and image enhancement tasks. It supports both NumPy and PyTorch tensors seamlessly, automatically choosing the framework based on input type, and performs fully differentiable operations suitable for training. The package addresses what the author identifies as correctness issues in existing resizers: it produces results matching MATLAB's imresize for simple cases, implements anti-aliasing for downscaling to prevent artifacts, and crucially handles the non-integer scaling case by accepting both scale-factor and output-size parameters to maintain consistency and centering.\n\nThe library offers multiple interpolation methods (cubic, linear, Lanczos, box), supports N-dimensional tensors with M-dimensional resizing, and can apply different scale-factors per dimension. For rational scale-factors with small numerators, it can use efficient convolution-based calculation. It includes flexible padding modes and allows custom interpolation methods. However, the package has been abandoned since mid-2023 with no updates or maintenance.","worth_installing":"Yes, if you need differentiable resizing with anti-aliasing and are willing to accept an abandoned package with no ongoing maintenance. The core algorithm appears sound for its stated use cases (super-resolution, image restoration), but expect no bug fixes, no compatibility updates, and no support. Suitable for research or one-off projects; risky for production systems or long-term codebases."},"id":"resize-right","links":{"html":"https://skillfed.io/packages/resize-right","md":"https://skillfed.io/packages/resize-right.md","pypi":"https://pypi.org/project/resize-right/"},"maintenance":{"status":"abandoned"},"meta":{"latest_release":"2022-05-05","license_spdx":null,"license_treatment":"permissive","name":"resize-right","python_support":"unspecified","summary":"Resize Right"},"popularity":{"monthly_downloads":198695,"position":9721,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.0.2"}