Open Source tiny 3D engine for tkinter
Tiny 3D Engine
This package is a python 3D engine based on the Tkinter Canvas. It uses Numpy for math handling.
Install this using
pip install tiny_3d_engine
It create simle 3D rendering for
quad elements and store the scenes in Ensight's ASCII
A trivial grid would look like:
Loading a model
In this simple example, a .geo file is loaded
load_file_as_scene into a 3D scene. This scene is given to a new engine object
Engine3D. We apply a rotation
.rotate() before rendering
.render()the scene on the screen, then leave the interaction to the user
scene = load_file_as_scene("myfile.geo") test = Engine3D(scene) test.rotate('y', 45) test.render() test.mainloop()
The SCENE and the ENGINE
The SCENE is an object storing the 3D model.
A void scene is simply
None. You can update a scene with the method
.update(). Each scene handle several parts identified by a name, a string looking either as
"ceiling") or as
The ENGINE is used to project the scene on the 2D screen.
Once started, the view point can be contrlled by methods such as
.rotate(), then refreshed with
.render(). The scen cane be update with
.update(). If you want user interaction with the result, finish with the typical TK
What if I already have my vertices and polygons?
In the following example, two squares are appended to an initially void Scene3D object, using the method
- The first, in blue, is made of edges (2 vertices connectivity)
- The second, in red, is made od squares (4 vertices connectivity)
This scene is passed to the Engine3D object, triggering a window.
from tiny_3d_engine import (Scene3D, Engine3D) scene = Scene3D() SIZE = 2 LENGTH= 200. points = list() conn = list() dx = LENGTH/ for i in range(SIZE): for j in range(SIZE): index = len(points) points.append([i*dx, j*dx, 0]) points.append([(i+1)*dx, j*dx, 0]) points.append([i*dx, (j+1)*dx, 0]) points.append([(i+1)*dx, (j+1)*dx, 0]) conn.append([index, index+1]) conn.append([index+3, index+1]) scene.update("square1", points, conn, color="#0000ff") points = list() conn = list() for i in range(SIZE): for j in range(SIZE): index = len(points) points.append([i*dx, j*dx, LENGTH]) points.append([(i+1)*dx, j*dx, LENGTH]) points.append([i*dx, (j+1)*dx, LENGTH]) points.append([(i+1)*dx, (j+1)*dx, LENGTH]) conn.append([index, index+1, index+3, index+2]) scene.update("square2", points, conn, color="#ff0000") test = Engine3D(scene) test.rotate("x", 45) test.rotate("y", 45) test.render() test.mainloop()
(It would have been easier in numpy, but I wanted to keep this readable for non-numpy programmers)
A small command line interface is available:
Usage: tiny_3d_engine [OPTIONS] COMMAND [ARGS]... --------------- TINY_3D_ENGINE -------------------- You are now using the Command line interface of Tiny 3D engine, a Python3 Tkinter lightweight 3D engine, created at CERFACS (https://cerfacs.fr). This package is likely as a dependency of other packages, to provide a light 3D feedback for small 3D scenes <100 000 polygons. This CLI is given here for developers perusal and demonstrations. Find the script of these small tools in the /examples folder of the package. This is a python package currently installed in your python environement. See the full documentation at : https://tiny-3d-engine.readthedocs.io/en/latest/. DISCLAIMER: Tiny 3D engine is a brute force flat renderer. As it is NOT using your graphical card, do not excpect anything fancier than a 1980 video game. Options: --help Show this message and exit. Commands: bench Run a short benchmark on your machine. load Load a 3D scene from FILENAME. rabbit Run a demo with the Stanford Rabbit.
Do not expect more than an early 90s videogame. During mouse interations, the frames per second is roughly 30 000 / nb. of polygons (i.e. 15 fps for 2000 polygons).
The engine is by default limited 100 000 polygons in a static view and 2 000 during mouse interactions. If the model goes beyond these limits, the engine ramdomly remove polygons at the loading time, to keep the window responsive.
The present library require Numpy and Tkinter. The Tk aspects are limited to the screen object. In the future I might write extensions for PyQT4 Canvas or Matplotlib... or not.
The present one allow several parts to be loaded, and uses numpy. Scenes can be dumped or read from the Ensight .case/.geo files.
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