{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/3"},{"label":"Video","url":"https://skillfed.io/packages/category/multimedia-video"}],"enrichment":{"capability":"scikit-video reads, writes, and analyzes video files using FFmpeg, providing Python functions for frame extraction and video quality metrics including SSIM, PSNR, NIQE, and BRISQUE.","skillfed_tags":["video-processing","quality-metrics","computer-vision"],"use_cases":["Extract and analyze individual frames from video files for computer vision tasks.","Compute video quality metrics (SSIM, PSNR, NIQE) to compare original and processed videos.","Calculate motion vectors between consecutive frames for motion analysis.","Batch-process video datasets to generate frame-level features for machine learning.","Validate video codec and container compatibility before processing in production pipelines."],"what_it_does":"scikit-video is a Python video processing library that reads, writes, and analyzes video files by delegating I/O to FFmpeg and providing a NumPy-based interface for frame manipulation and quality metrics. It borrows conventions from scikit-image and scikit-learn, exposing functions for motion estimation and video quality assessment (SSIM, PSNR, NIQE, BRISQUE, VIIDEO, Video-BLIINDS). The library is built on numpy, scipy, and Pillow, and is actively maintained with recent releases fixing metric accuracy against reference MATLAB implementations and adding support for modern Python and NumPy versions.\n\nTypical use cases include extracting frames from video files, computing frame-level quality scores, analyzing motion between frames, and batch-processing video datasets. The package handles both local files and file-like objects, supports pathlib.Path, and can pass audio through unchanged during video processing. Recent versions removed deprecated libav/avconv support and cleaned up Python-2-era code, making it more maintainable for current environments.","worth_installing":"Yes, if you need video I/O and quality metrics in Python. The package is actively maintained, has low install friction, carries no known vulnerabilities, and uses a permissive license. The main gotcha is the hard requirement for FFmpeg on the system PATH and Python >= 3.10; verify your environment supports both before committing. Recent metric accuracy fixes mean scores from 1.2.0+ are not comparable to 1.1.x, so check whether existing benchmarks or thresholds need recalibration."},"id":"scikit-video","links":{"html":"https://skillfed.io/packages/scikit-video","md":"https://skillfed.io/packages/scikit-video.md","pypi":"https://pypi.org/project/scikit-video/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2018-09-18","license_spdx":null,"license_treatment":"permissive","name":"scikit-video","python_support":"unspecified","summary":"Video Processing in Python"},"popularity":{"monthly_downloads":1246075,"position":4164,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"1.1.11"}