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Recent Posts
- Using JAX, numpy, and optimization techniques to improve separable image filters March 15, 2020
- Separate your filters! Separability, SVD and low-rank approximation of 2D image processing filters February 3, 2020
- Analyze your own activity data using Google Takeout – music listening stats example January 6, 2020
- Local linear models and guided filtering – an alternative to bilateral filter September 22, 2019
- How (not) to test graphics algorithms August 14, 2019
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Categories
Tag Archives: numpy
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
4 Comments
Separate your filters! Separability, SVD and low-rank approximation of 2D image processing filters
In this blog post, I explore separable convolutional image filters: how can we check if a 2D filter is separable, and how to compute separable approximations to any arbitrary 2D filter represented in a numerical / matrix form using SVD. Continue reading
Posted in Code / Graphics
Tagged algorithms, approximation, blur, bokeh, depth of field, graphics, image processing, linear algebra, numpy, optimizations, postprocessing, python
6 Comments
Analyze your own activity data using Google Takeout – music listening stats example
The goal of this post is to show how to download our own data stored and used by internet services to generate personalized stats / charts like below and will show step-by-step how to do it using colab, Python, pandas, … Continue reading
Posted in Code / Graphics
Tagged colab, data, numpy, programming, python, statistics, visualization
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