Open Source Python 3D Viewers for Mac

PyRx is a Virtual Screening software for Computational Drug Discovery that can be used to screen libraries of compounds against potential drug targets. PyRx enables Medicinal Chemists to run Virtual Screening from any platform and helps users in every step of this process - from data preparation to job submission and analysis of the results. While it is true that there is no magic button in the drug discovery process, PyRx includes docking wizard with easy-to-use user interface which makes it a valuable tool for Computer-Aided Drug Design. PyRx also includes chemical spreadsheet-like functionality and powerful visualization engine that are essential for Rational Drug Design. Please visits PyRx home page to learn more about PyRx and watch videos on how to use it.

DXF2GCODE is a tool for converting 2D (dxf, pdf, ps) drawings to CNC machine compatible GCode. Windows, Linux, and Mac support by using python scripting language.

PoJamas aims to provide a Python and tools for loading, processing, and producing .cr2, pz3 (crz, pzz) files compatible with the SmithMicro (e-frontier) Poser character animation application. PoJamas is composed of: - Python library - Python Wavefront (.obj) 3D viewer based on GLFW - LibreOffice/Python Application (to ease the library and the viewer usage) As of 2020, the project is ported in Python3 As of 2021 this project proposes a 3D viewer for Wavefront files (pypos3dv) PyPosPosLO v0.15 (and above) provides the means to easily create Poser Mechanical Character. Results can be seen here: https://sharecg.com/v/94509/view/11/Poser/Hawker-Tempest-Character-v2

3D rendering engine made using Python as an exploratory adventure into the world of 3D graphics. It also Incorporates the wireless display handler from the Electronic-Shelf-Label-Management-System V2.0. Based on the work of Rad-hi: https://github.com/Rad-hi/3D-Rendering-Desktop-App Used .obj file: https://free3d.com/3d-model/low_poly_tree-816203.html

GEOMS2 is a geostatistics and geosciences modeling software. Provides interface for grid (mesh), point, surface and data (non-spatial) objects. It has a 3D viewer and 2D plots using the well known Python engines Mayavi and Matplotlib. It has several functions to manipulate your data as well as provide univariate and multivariate analysis. NOTE: The software is still an early beta. Please tell us if you found a bug. Download datasets for students of Geostatistics 2017 (Petroleum Engineering): https://sourceforge.net/projects/geoms2/files/Geostatistics_Petroleum.zip/download Download datasets for students of Geostatistics 2017 (Geology and Mining Engineering): https://sourceforge.net/projects/geoms2/files/Geostatistics_Mining.zip/download Old: http://sourceforge.net/projects/geoms2/files/SETS_geoestatistica2_2015.7z/download https://sites.google.com/site/cmrpsoftware/downloads/Quarry_sets.7z?attredirects=0&d=1 http://sourceforge.net/projects/geoms2/files/Mining.7z/download

ML Sharp is a research code release that turns a single 2D photograph into a photorealistic 3D representation that can be rendered from nearby viewpoints. Instead of requiring multi-view input, it predicts the parameters of a 3D Gaussian scene representation directly from one image using a single forward pass through a neural network. The core idea is speed: the 3D representation is produced in under a second on a standard GPU, and then the resulting scene can be rendered in real time to generate new views interactively. The representation is metric, meaning it supports camera movements with an absolute scale rather than only relative depth cues, which is useful for consistent viewpoint changes and downstream spatial tasks. The project is structured for reproducibility, with code and assets aimed at demonstrating view synthesis quality, sharp details, and fine structures when rendering high-resolution images.