sk-video
Video Processing in Python
Decision gist · record as of 2026-08-14
Yes, if you need video I/O and quality metrics in a Python environment already using numpy and scipy. Install friction is low and maintenance is active. Requires FFmpeg >= 2.8 on system PATH and Python >= 3.10. Metric implementations changed in 1.2.0 (more accurate but incomparable to 1.1.x scores); verify this does not break existing workflows. No known security vulnerabilities.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- FFmpeg >= 2.8 must be installed and on system PATH; Python >= 3.10 required.
- Low install friction; pure Python wheel with only numpy and scipy as runtime dependencies.
- Actively maintained with recent metric accuracy fixes and NumPy 2.x compatibility.
License · maintenance · safety
BSD (permissive) — BSD permissive license allows commercial and private use with minimal restrictions; attribution and license notice required in distributions.
last release 2017-12-12 (3167 days) · last repo commit 2026-07-04 · 710 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 305,163 downloads/mo, #7,796 on PyPI
Alternatives
Verify before relying
pip install scikit-video
import skvideo.io
video_data = skvideo.io.vread('video.mp4')
metadata = skvideo.io.ffprobe('video.mp4')- Whether the metric accuracy changes in 1.2.0 (NIQE, BRISQUE, VIIDEO, Video-BLIINDS) affect existing workflows or benchmarks.
- Current state of the deprecated libav/avconv backend and mediainfo support (planned removal in 1.4.0).
- Whether Pillow >= 9.0 is a runtime or optional dependency.
What it is and what it does
This package provides video I/O and analysis capabilities, wrapping FFmpeg to read and write video frames, extract metadata, and compute video quality metrics. It follows the conventions of scikit-image and scikit-learn, sitting on top of numpy and scipy for workflows already using the scientific Python stack.
The library provides frame-by-frame video access, metadata inspection, and implementations of standard quality metrics (MSE, PSNR, SSIM, MS-SSIM, NIQE, BRISQUE, VIIDEO, Video-BLIINDS, ST-RRED). Recent versions validated metric implementations against reference code and fixed divergences; the 1.1.12+ line added pathlib.Path support, URL and file-like object I/O, and audio passthrough. The project is actively maintained with ongoing compatibility work for modern NumPy and Python versions.
Use it for
- Extract frames from video files and process them with numpy and scipy for computer vision tasks.
- Compute video quality metrics (SSIM, PSNR, NIQE, BRISQUE) for compression or enhancement evaluation.
- Read video metadata and properties without decoding all frames.
- Batch process video files to generate frame sequences for machine learning pipelines.
- Validate video codec compatibility and inspect FFmpeg-supported container formats.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need video I/O and quality metrics in a Python environment already using numpy and scipy.
Install friction is low and maintenance is active. Requires FFmpeg >= 2.8 on system PATH and Python >= 3.10. Metric implementations changed in 1.2.0 (more accurate but incomparable to 1.1.x scores); verify this does not break existing workflows. No known security vulnerabilities.
Install
sk-video on PyPI
Before you install
Low install friction; pure Python wheel with only numpy and scipy as runtime dependencies. Actively maintained with recent metric accuracy fixes and NumPy 2.x compatibility. Requires FFmpeg >= 2.8 on system PATH and Python >= 3.10.
FFmpeg >= 2.8 must be installed and on system PATH; Python >= 3.10 required.
License in practice
BSD permissive license allows commercial and private use with minimal restrictions; attribution and license notice required in distributions.
Quickstart
pip install scikit-video
import skvideo.io
video_data = skvideo.io.vread('video.mp4')
metadata = skvideo.io.ffprobe('video.mp4')Verify before relying
- Whether the metric accuracy changes in 1.2.0 (NIQE, BRISQUE, VIIDEO, Video-BLIINDS) affect existing workflows or benchmarks.
- Current state of the deprecated libav/avconv backend and mediainfo support (planned removal in 1.4.0).
- Whether Pillow >= 9.0 is a runtime or optional dependency.
Package facts
| License | BSD permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesnumpyscipy |
| Maintenance | Actively maintained 3,167 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 305,163 / month, #7,796 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 3 - AlphaIntended Audience :: DevelopersIntended Audience :: Science/ResearchLicense :: OSI Approved :: BSD LicenseOperating System :: MacOSOperating System :: Microsoft :: WindowsOperating System :: POSIX :: LinuxProgramming Language :: Python :: 2.6Programming Language :: Python :: 2.7Programming Language :: Python :: 3.6Topic :: Multimedia :: VideoTopic :: Scientific/Engineering |
Evidence: sk_video-1.1.10-py2.py3-none-any.whl
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See also scikit-video · moviepy · imageio-ffmpeg · knowit · typed-ffmpeg · ffmpeg-python · ffmpeg · decord2 · decord · mediapy