jsmpeg
numexpr
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jsmpeg | numexpr | |
---|---|---|
3 | 4 | |
6,238 | 2,140 | |
- | 0.9% | |
0.0 | 8.2 | |
over 1 year ago | 28 days ago | |
JavaScript | Python | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
jsmpeg
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Making Python 100x faster with less than 100 lines of Rust
>Today, there is a Python package for everything.
The same could be said about CPAN and NPM. Yet Perl is basically dead and JavaScript isn't used for any machine learning tasks as far as I'm aware. WebAssembly did help bring a niche array of audio and video codecs to the ecosystem[1][2], something I'm yet to see from Python.
I don't use Python, but with what little exposure I've had to it at work, its overall sluggish performance and need to set up a dozen virtualenvs -- only to dockerize everything in cursed ways when deploying -- makes me wonder how or why people bother with it at all beyond some 5-line script. Then again, Perl used to be THE glue language in the past and mod_perl was as big as FastAPI, and Perl users would also point out how CPAN was unparalleled in breadth and depth. I wonder if Python will follow a similar route as Perl. One can hope :-)
[1] https://github.com/phoboslab/jsmpeg
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Looking for a simple (MJPEG-like) browser-friendly way to stream live video
There's also mpegts over websockets if you don't need iphone support. https://github.com/phoboslab/jsmpeg
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RTCP stream in HTML throught WebSocket
We will use jsmpeg to display the video on the page
numexpr
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Making Python 100x faster with less than 100 lines of Rust
You can just slap numexpr on top of it to compile this line on the fly.
https://github.com/pydata/numexpr
- Extending Python with Rust
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[D] How to avoid CPU bottlenecking in PyTorch - training slowed by augmentations and data loading?
Are you doing any costly chained NumPy operations in your preprocessing? E.g. max(abs(large_ary)), this produces multiple copies of your data, https://github.com/pydata/numexpr can greatly reduce time spent with such operations
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Selection in pandas using query
What is not entirely obvious here is that under the hood you can install a nice library called numexpr (docs, src) that exists to make calculations with large NumPy (and pandas) objects potentially much faster. When you use query or eval, this expression is passed into numexpr and optimized using its bag of tricks. Expected performance improvement can be between .95x and up to 20x, with average performance around 3-4x for typical use cases. You can read details in the docs, but essentially numexpr takes vectorized operations and makes them work in chunks that optimize for cache and CPU branch prediction. If your arrays are really large, your cache will not be hit as often. If you break your large arrays into very small pieces, your CPU won’t be as efficient.
What are some alternatives?
FFmpeg - Mirror of https://git.ffmpeg.org/ffmpeg.git
pytorch-lightning - Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems). [Moved to: https://github.com/Lightning-AI/lightning]
ustreamer - µStreamer - Lightweight and fast MJPEG-HTTP streamer
pygfx - A python render engine running on wgpu.
node-rtsp-stream - Stream any RTSP stream and output to websocket for consumption by jsmpeg (https://github.com/phoboslab/jsmpeg). HTML5 streaming video! Requires ffmpeg.
greptimedb - An open-source, cloud-native, distributed time-series database with PromQL/SQL/Python supported. Available on GreptimeCloud.
Streama - Self hosted streaming media server. https://docs.streama-project.com/
jnumpy - Writing Python C extensions in Julia within 5 minutes.
PythonCall.jl - Python and Julia in harmony.
poly-match - Source for the "Making Python 100x faster with less than 100 lines of Rust" blog post
ruff - An extremely fast Python linter and code formatter, written in Rust.