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Recent Posts
- Superfast void-and-cluster Blue Noise in Python (Numpy/Jax) April 21, 2021
- Computing gradients on grids of pixels and voxels – forward, central, and… diagonal differences February 28, 2021
- Bilinear down/upsampling, aligning pixel grids, and that infamous GPU half pixel offset February 15, 2021
- Is this a branch? January 18, 2021
- Converting wavetables to Ableton Operator AMS waves January 5, 2021
Categories
Tag Archives: jax
Superfast void-and-cluster Blue Noise in Python (Numpy/Jax)
This is a super short blog post to accompany this Colab notebook. It’s not an official part of my dithering / Blue Noise post series, but thematically fits it well and be sure to check it out for some motivation … Continue reading
Posted in Code / Graphics
Tagged blue noise, dithering, graphics programming, jax, numpy, python
1 Comment
“Optimizing” blue noise dithering – backpropagation through Fourier transform and sorting
Introduction This will be a blog post that is second in an (unanticipated) series on interesting uses of the JAX numpy autodifferentiation library, as well as an extra post in my very old post series on dithering in games and … Continue reading
Posted in Code / Graphics
Tagged blue noise, dithering, frequency domain, image processing, jax, machine learning, noise, numpy, python
2 Comments
Using JAX, numpy, and optimization techniques to improve separable image filters
In today’s blog post I will look at two topics: how to use JAX (“hyped” new Python ML / autodifferentiation library), and a basic application that is follow-up to my previous blog post on using SVD for low-rank approximations and … Continue reading
Posted in Code / Graphics
Tagged bokeh, colab, github, graphics programming, image processing, jax, maths, numpy, postprocessing, programming, python
6 Comments
