{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/2"},{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/2"},{"label":"Image Processing","url":"https://skillfed.io/packages/category/scientific-engineering-image-processing"}],"enrichment":{"capability":"kornia-rs provides low-level computer vision operations\u2014image I/O, resizing, color conversion, and video capture\u2014implemented in Rust with Python bindings for efficient, thread-safe processing.","skillfed_tags":["rust-bindings","image-io","video-processing"],"use_cases":["Load and preprocess images for deep learning training pipelines with minimal overhead.","Read and write depth maps or scientific imagery in uint16 format losslessly via PNG.","Capture video frames from cameras and process them in real time with thread safety.","Convert image formats and apply basic transformations (resize, grayscale, normalize) in batch workflows.","Integrate efficient image I/O into machine learning applications."],"what_it_does":"kornia-rs is a Rust-based computer vision library with Python bindings that handles image I/O, processing, and video capture. It reads and writes multiple image formats (JPEG via libjpeg-turbo, PNG, WebP, TIFF, and others), performs operations like resizing, cropping, rotation, color conversion, and normalization, and supports video frame capture. The library is designed for efficiency and thread safety, making it suitable for integration into machine learning pipelines and data-science workflows.\n\nThe package exposes a subset of its Rust API through Python, including a PIL-style Image class that natively supports uint16 for depth maps and scientific imagery. It includes both high-level convenience functions and lower-level encoder/decoder objects for JPEG workflows. The library is actively maintained, supports Python 3.8 through 3.13 (including the free-threaded build), and provides precompiled wheels for common platforms, reducing installation friction.","worth_installing":"Yes, if you need fast, thread-safe image I/O and basic processing in a Python environment. The Rust backend, prebuilt wheels, and support for modern Python versions make it a low-friction choice for ML pipelines. No runtime dependencies required for core functionality. Consider it especially if you work with depth maps (uint16) or need video capture; for simple image operations, alternatives may suffice."},"id":"kornia-rs","links":{"html":"https://skillfed.io/packages/kornia-rs","md":"https://skillfed.io/packages/kornia-rs.md","pypi":"https://pypi.org/project/kornia-rs/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-05-19","license_spdx":null,"license_treatment":"permissive","name":"kornia-rs","python_support":"supports_current","summary":"Low level implementations for computer vision in Rust"},"popularity":{"monthly_downloads":3212425,"position":2699,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.1.14"}