https://github.com/tommoral/benchmark_image_inverse_problem

Benchmarking inverse problem solvers on images
https://github.com/tommoral/benchmark_image_inverse_problem

Last synced: 23 days ago
JSON representation

Benchmarking inverse problem solvers on images

• Host: GitHub
• URL: https://github.com/tommoral/benchmark_image_inverse_problem
• Owner: tomMoral
• Created: 2022-06-29T08:32:53.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2022-07-07T16:26:24.000Z (over 2 years ago)
• Last Synced: 2023-10-10T22:07:35.600Z (about 1 year ago)
• Language: Python
• Size: 92.8 KB
• Stars: 4
• Watchers: 1
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README.rst

Awesome Lists containing this project

README

        
Inmage Inverse Problem Benchmark

================================

|Build Status| |Python 3.6+|

Benchopt is a package to simplify and make more transparent and

reproducible the comparisons of optimization algorithms.

This benchmark is dedicated to solver of **describe your problem**:

$$\\min_{w} f(X, w)$$

where $n$ (or ``n_samples``) stands for the number of samples, $p$ (or ``n_features``) stands for the number of features and

$$X \\in \\mathbb{R}^{n \\times p} \\ , \\quad w \\in \\mathbb{R}^p$$

Install

--------

This benchmark can be run using the following commands:

.. code-block::

   $ pip install -U benchopt

   $ git clone https://github.com/tomMoral/benchmark_image_inverse_problem

   $ benchopt run benchmark_image_inverse_problem

Apart from the problem, options can be passed to ``benchopt run``, to restrict the benchmarks to some solvers or datasets, e.g.:

.. code-block::

	$ benchopt run benchmark_image_inverse_problem -s solver1 -d dataset2 --max-runs 10 --n-repetitions 10

Use ``benchopt run -h`` for more details about these options, or visit https://benchopt.github.io/api.html.

.. |Build Status| image:: https://github.com/tomMoral/benchmark_image_inverse_problem/workflows/Tests/badge.svg

   :target: https://github.com/tomMoral/benchmark_image_inverse_problem/actions

.. |Python 3.6+| image:: https://img.shields.io/badge/python-3.6%2B-blue

   :target: https://www.python.org/downloads/release/python-360/