imageproc (PistonDevelopers)
rust-ndarray
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imageproc (PistonDevelopers) | rust-ndarray | |
---|---|---|
3 | 19 | |
569 | 2,814 | |
2.5% | 2.2% | |
1.3 | 6.7 | |
4 days ago | 8 days ago | |
Rust | Rust | |
MIT License | Apache License 2.0 |
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.
imageproc (PistonDevelopers)
- Looking for an image manipulation library that can add text to images. (and has documentation for it)
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Searching help for Rust Image Manipulation
I suggest you have a look at the [imageproc](https://github.com/image-rs/imageproc) crate. Personally, I feel like image processing / manipulation in Rust has a long way to go, though.
- manipulating jpeg files
rust-ndarray
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faer 0.8.0 release
Sadly Ndarray does look a little abandoned to me: https://github.com/rust-ndarray/ndarray
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Status and Future of ndarray?
The date of the last commit of [ndarray](https://github.com/rust-ndarray/ndarray) lies 6 month in the past while many recent issues are open and untouched.
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Announcing Burn: New Deep Learning framework with CPU & GPU support using the newly stabilized GAT feature
Burn is different: it is built around the Backend trait which encapsulates tensor primitives. Even the reverse mode automatic differentiation is just a backend that wraps another one using the decorator pattern. The goal is to make it very easy to create optimized backends and support different devices and use cases. For now, there are only 3 backends: NdArray (https://github.com/rust-ndarray/ndarray) for a pure rust solution, Tch (https://github.com/LaurentMazare/tch-rs) for an easy access to CUDA and cuDNN optimized operations and the ADBackendDecorator making any backend differentiable. I am now refactoring the internal backend API to make it as easy as possible to plug in new ones.
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Pure rust implementation for deep learning models
Looks like it's an open request
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The Illustrated Stable Diffusion
https://github.com/rust-ndarray/ndarray/issues/281
Answer: you can’t with this crate. I implemented a dynamic n-dim solution myself but it uses views of integer indices that get copied to a new array, which have indexes to another flattened array in order to avoid duplication of possibly massive amounts of n-dimensional data; using the crate alone, copying all the array data would be unavoidable.
Ultimately I’ve had to make my own axis shifting and windowing mechanisms. But the crate is still a useful lib and continuing effort.
While I don’t mind getting into the weeds, these kinds of side efforts can really impact context focus so it’s just something to be aware of.
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Any efficient way of splitting vector?
In principle you're trying to convert between columnar and row-based data layouts, something that happens fairly often in data science. I bet there's some hyper-efficient SIMD magic that could be invoked for these slicing operations (and maybe the iterator solution does exactly that). Might be worth taking a look at how the relevant Rust libraries like ndarray do it.
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Rust or C/C++ to learn as a secondary language?
ndarray and numpy crates provide good way to operate on numpy ndarrays from python
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Enzyme: Towards state-of-the-art AutoDiff in Rust
I don't think any of the major ML projects have GPU acceleration because ndarray doesn't support it.
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Announcing Rust CUDA 0.2
Not sure about ndarray: https://github.com/rust-ndarray/ndarray/issues/840
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Signal processing library
I used basic_dsp a while back and found it lacking. I was hoping to find something that uses the ndarray datatype but i'm not seeing this yet. If you're primarily trying to learn though it might not really matter which library you contribute to. As for myself, I just picked the one that was most used and actively worked on at the time. However I keep an eye out on other libraries; if I see something take off, I might switch over. Either way you'll learn and can point to it as work accomplished.
What are some alternatives?
nalgebra - Linear algebra library for Rust.
Rust-CUDA - Ecosystem of libraries and tools for writing and executing fast GPU code fully in Rust.
magick-rust - Rust bindings for ImageMagick
opencv-rust - Rust bindings for OpenCV 3 & 4
image - Encoding and decoding images in Rust
neuronika - Tensors and dynamic neural networks in pure Rust.
utah - Dataframe structure and operations in Rust
oxipng - Multithreaded PNG optimizer written in Rust
imageproc - An advanced image processing library for Rust.
linfa - A Rust machine learning framework.
dasp - The fundamentals for Digital Audio Signal Processing. Formerly `sample`.