Intel to Release Open Image Denoise Library

C++ written library is created to provide efficient and easy-to-use noise reduction function
31 January 2019   1330

Intel introduced the first experimental release of the oidn library (Open Image Denoise), which offers a collection of filters for eliminating noise in images prepared using ray tracing based rendering systems. The library is being developed as part of a larger Intel Rendering Framework project aimed at developing software for visualizing scientific calculations (SDVis (Software Defined Visualization)), which includes Embree ray tracing library, GLuRay photorealistic rendering system, OSPRay distributed ray tracing system and OpenSWR software rasterization system. Code written in C ++ and published under the Apache 2.0 license.

The goal of the Open Image Denoise library is to provide high-quality, efficient and easy-to-use noise reduction functions that can be used to improve the quality of the ray tracing results. The proposed filters allow, based on the result of the reduced ray tracing cycle, to obtain a final quality level comparable to the result of a more costly and lengthy process of detailed rendering.

The proposed algorithms provide screening of random noise, simulated by the Monte Carlo method, characteristic of stochastic ray tracing algorithms, such as path-based rendering. To achieve high quality rendering in such algorithms, tracing of a very large number of rays is required, otherwise noticeable artifacts in the form of random noise appear on the resulting image.

The use of Open Image Denoise allows you to reduce the number of necessary calculations by several orders of magnitude when calculating each pixel. As a result, it is possible to generate much initially noisy images and bring it to an acceptable quality using fast noise reduction algorithms. Depending on the equipment used, this approach can even be used for interactive ray tracing and imaging on the run.

Nuitka 0.6.6 to be Released

This compiler allows to translate a Python script into a C ++ representation, which can then be compiled into an exe file using libpython
08 January 2020   125

Nuitka 0.6.6 has been released. This is a compiler that allows you to translate a Python script into a C ++ representation, which can then be compiled into an executable file using libpython to ensure maximum compatibility with CPython (using regular CPython tools for managing objects) . Fully compatible with current releases of Python 2.x and 3.x. Compared to CPython, compiled scripts show up to 312% higher performance in pystone tests. Project code is distributed under the Apache license.

The new version adds experimental support for Python 3.8 and provides compatibility with libraries and applications sklearn, osgeo, gdal, dill, scikit-image, skimage, weasyprint, dask, pendulum, pytz and pytzdata. Distutils adds support for individual modules (py_modules, not just packages) and packages with separate namespaces. Work with variables in loops has been optimized and optimized options for the abs and all built-in functions have been implemented, as well as accelerated operations with int and long types. Numerous improvements have been made to reduce memory consumption.
In addition, it is possible to postpone the end of support for the Python 2 branch from January to April. In April 2020, the last final update of the Python 2.7 branch will be generated, after which the corrective releases will not be published. At the same time, work on fixing vulnerabilities in Python 2.7 will be continued by community representatives who are interested in continuing to support this branch in their products. For example, Red Hat will continue to maintain packages with Python 2.7 throughout the entire life cycle of RHEL 6 and 7 distributions, and for RHEL 8 it will generate package updates in the Application Stream until June 2024. Recall that the Python 2.7 branch was formed in 2010 and it was originally planned to stop supporting it in 2015, but due to the insufficiently active migration of projects to Python 3, the lifetime of Python 2 was extended to 2020.