ogv.js
JavaScript media player using Ogg/Vorbis/Theora/Opus/WebM libs compiled with Emscripten (by bvibber)
numexpr
Fast numerical array expression evaluator for Python, NumPy, Pandas, PyTables and more (by pydata)
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| ogv.js | numexpr | |
|---|---|---|
| 7 | 4 | |
| 1,182 | 2,147 | |
| - | 0.8% | |
| 7.2 | 8.2 | |
| 2 days ago | 4 days ago | |
| JavaScript | Python | |
| GNU General Public License v3.0 or later | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
ogv.js
Posts with mentions or reviews of ogv.js.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-03-29.
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"MP3 is dead" missed the real, much better story (2017)
Yeah, that's what they do using this https://github.com/brion/ogv.js/
- Making Python 100x faster with less than 100 lines of Rust
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Google and Mozilla are working on iOS browsers that aren't based on WebKit
I've been told this at least three times now on HN over the years (pretty soon I'm going to start keeping a list of URLs so people know I'm not exaggerating.) Every single time it turns out that it isn't actually true.
It was added to desktop Safari. iOS Safari supports VP9 only in WebRTC. It may have changed, but I can't find any evidence that it has.
If you see it working somewhere, it is almost definitely using the polyfill[1].
[1]: https://github.com/brion/ogv.js/
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How to stream OGG on iOS?
I found a library "ogv.js" that says it decodes .ogg/.webm using WebAssembly, and this demo plays on my iPhone SE3 in Safari.
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Anti-innovative effects of Apple's prohibition of alternative browser engines
I believe Wikipedia has resorted to polyfilling it using this:
https://github.com/brion/ogv.js
That's great and all, but it has limitations, and obviously, is ludicrously less efficient than it should be.
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Privacy analysis of FLoC
We already have JS/WebGL video decoders (e.g: Broadway.js, OGOV.js). Much of the earlier video playback/acceleration work was getting it accelerated on GPUs-- using DirectX, OpenGL, or other GPU programming standards.
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WebCodecs is a flexible web API for encoding and decoding audio and video
This is great and overdue. Hopefully all major browsers will add some support for open source/royalty free codecs.
Emscripten/WebAssembly actually worked rather well with audio (OPUS is just awesome) but when it comes to video it's just unfeasible, especially if you are looking at doing low latency streaming. That said, I cannot fail to mention the incredible effort done by ogv.js [1] to make a/v decoding possible almost anywhere.
Looking forward to experiment with this new API.
[1] https://github.com/brion/ogv.js/
numexpr
Posts with mentions or reviews of numexpr.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-03-29.
-
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.