scikit-video
scikit-video - Scientific Video Processing
scikit-video simplifies the complex world of video codecs and containers by providing a consistent NumPy-based interface. It allows for the calculation of motion vectors, video quality assessment (VQA), and seamless integration with the rest of the scientific Python stack.
When to Use
- Reading and writing video files in various formats (MP4, AVI, MKV) via FFmpeg.
- Extracting specific frames or segments from long videos without loading them entirely into memory.
- Calculating motion estimation (Block Matching, Optical Flow).
- Measuring video quality (PSNR, SSIM, VIF, NIQE).
- Generating video datasets for machine learning.
- Visualizing temporal changes in pixel data (e.g., scientific recordings).
- Handling raw YUV data streams.
Reference Documentation
Official docs: http://www.scikit-video.org/
GitHub: https://github.com/scikit-video/scikit-video
Search patterns: skvideo.io.vread, skvideo.io.FFmpegReader, skvideo.motion, skvideo.measure
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