A very impractical 3D rendering engine that runs in the python terminal.

Related tags

Deep LearningTerminal-3D-Render
Overview

Terminal-3D-Render

A very impractical 3D rendering engine that runs in the python terminal. do NOT try to run this program using the standard python IDE as it does not use ANSI escape codes. If your terminal of choice does not support ANSI escape codes it will also break in the same way.

ONLY ON VERSIONS BEFORE 0.1.3: Due to the time it takes to use the print command, sometimes the screen will refresh while the program is in the process of clearing and redrawing the screen. this causes the screen to flash rapidly and the effect worsens the higher your refresh rate is. At 60Hz it isn't that bad, but I would still be careful running this if you suffer from any conditions that cause light sensitivity.

NOTES: if you want to use your own models with this program you must export them without normals but with UVs included. if you're using blender, when exporting make sure to click on the "Geometry" tab in the exporting menue, check the "Triangulate faces" option, and un-check the "Write normals" option. It should now load correctly.

Thanks for checking this out!

-E. Parker

You might also like...
UnsupervisedR&R: Unsupervised Pointcloud Registration via Differentiable Rendering

UnsupervisedR&R: Unsupervised Pointcloud Registration via Differentiable Rendering This repository holds all the code and data for our recent work on

Mohamed El Banani 118 Dec 6, 2022
Style-based Point Generator with Adversarial Rendering for Point Cloud Completion (CVPR 2021)
Style-based Point Generator with Adversarial Rendering for Point Cloud Completion (CVPR 2021)

Style-based Point Generator with Adversarial Rendering for Point Cloud Completion (CVPR 2021) An efficient PyTorch library for Point Cloud Completion.

Microsoft 119 Jan 2, 2023
Rendering Point Clouds with Compute Shaders
Rendering Point Clouds with Compute Shaders

Compute Shader Based Point Cloud Rendering This repository contains the source code to our techreport: Rendering Point Clouds with Compute Shaders and

Markus Schütz 460 Jan 5, 2023
Official repo for AutoInt: Automatic Integration for Fast Neural Volume Rendering in CVPR 2021
Official repo for AutoInt: Automatic Integration for Fast Neural Volume Rendering in CVPR 2021

AutoInt: Automatic Integration for Fast Neural Volume Rendering CVPR 2021 Project Page | Video | Paper PyTorch implementation of automatic integration

Stanford Computational Imaging Lab 149 Dec 22, 2022
Code for PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Relighting and Material Editing

PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Relighting and Material Editing CVPR 2021. Project page: https://kai-46.github.io/

Kai Zhang 141 Dec 14, 2022
Generative Query Network (GQN) in PyTorch as described in
Generative Query Network (GQN) in PyTorch as described in "Neural Scene Representation and Rendering"

Update 2019/06/24: A model trained on 10% of the Shepard-Metzler dataset has been added, the following notebook explains the main features of this mod

Jesper Wohlert 313 Dec 27, 2022
This repository contains the source code for the paper
This repository contains the source code for the paper "DONeRF: Towards Real-Time Rendering of Compact Neural Radiance Fields using Depth Oracle Networks",

DONeRF: Towards Real-Time Rendering of Compact Neural Radiance Fields using Depth Oracle Networks Project Page | Video | Presentation | Paper | Data L

Facebook Research 281 Dec 22, 2022
[CVPR2021] De-rendering the World's Revolutionary Artefacts

De-rendering the World's Revolutionary Artefacts Project Page | Video | Paper In CVPR 2021 Shangzhe Wu1,4, Ameesh Makadia4, Jiajun Wu2, Noah Snavely4,

null 49 Nov 6, 2022
The source code of the ICCV2021 paper
The source code of the ICCV2021 paper "PIRenderer: Controllable Portrait Image Generation via Semantic Neural Rendering"

The source code of the ICCV2021 paper "PIRenderer: Controllable Portrait Image Generation via Semantic Neural Rendering"

Ren Yurui 261 Jan 9, 2023
Releases(v0.1.5)

  • v0.1.5(Mar 31, 2022)

    Minor Update:

    Added camera movement - WASD to move, IJKL to look. Precalculated Divisions to speed up rendering.

    some other minor tweaks I've forgotten about.

    Source code(tar.gz)
    Source code(zip)

  • v0.1.4.3(Mar 29, 2022)

    Minor improvements,

    Removed os.system(CLS) call, replaced with proper ANCI code. Added support for the greyscale portion of 256 colour mode.

    I forgot to add a licence agreement in the last couple versions, that one's on me.

    Minor tweaks and fixes.

    Source code(tar.gz)
    Source code(zip)

  • v0.1.3(Mar 28, 2022)

    Some cool updates!

    Sorry for the version skip, there were a couple of versions I didn't feel were good enough to release so close to the last patch. I'd much rather have a good and working version of a piece of software rather than a bunch of dysfunctional versions that have continuity.

    • 256 colour mode now working using ANSI escape codes.
    • Flickering completely fixed, switched from print statements to ANSI escape sequence (Thanks u/SamyBencherif for suggesting this!)
    • Minor UI fixes
    Source code(tar.gz)
    Source code(zip)

  • v0.1.0(Mar 27, 2022)

  • v0.0.9(Mar 27, 2022)

Owner
GitHub Repository
[BMVC'21] Official PyTorch Implementation of Grounded Situation Recognition with Transformers

Grounded Situation Recognition with Transformers Paper | Model Checkpoint This is the official PyTorch implementation of Grounded Situation Recognitio

Junhyeong Cho 18 Jul 19, 2022
The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021

Directed Graph Contrastive Learning Paper | Poster | Supplementary The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL). In this

Tong Zekun 28 Jan 08, 2023
The Noise Contrastive Estimation for softmax output written in Pytorch

An NCE implementation in pytorch About NCE Noise Contrastive Estimation (NCE) is an approximation method that is used to work around the huge computat

Kaiyu Shi 287 Nov 25, 2022
A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.

Probabilistic U-Net + **Update** + An improved Model (the Hierarchical Probabilistic U-Net) + LIDC crops is now available. See below. Re-implementatio

Simon Kohl 498 Dec 26, 2022
An interactive DNN Model deployed on web that predicts the chance of heart failure for a patient with an accuracy of 98%

Heart Failure Predictor About A Web UI deployed Dense Neural Network Model Made using Tensorflow that predicts whether the patient is healthy or has c

Adit Ahmedabadi 0 Jan 09, 2022
Reference PyTorch implementation of "End-to-end optimized image compression with competition of prior distributions"

PyTorch reference implementation of "End-to-end optimized image compression with competition of prior distributions" by Benoit Brummer and Christophe

Benoit Brummer 6 Jun 16, 2022
YoloV3 Implemented in Tensorflow 2.0

YoloV3 Implemented in TensorFlow 2.0 This repo provides a clean implementation of YoloV3 in TensorFlow 2.0 using all the best practices. Key Features

Zihao Zhang 2.5k Dec 26, 2022
Implementation of CoCa, Contrastive Captioners are Image-Text Foundation Models, in Pytorch

CoCa - Pytorch Implementation of CoCa, Contrastive Captioners are Image-Text Foundation Models, in Pytorch. They were able to elegantly fit in contras

Phil Wang 565 Dec 30, 2022
Reimplementation of the paper "Attention, Learn to Solve Routing Problems!" in jax/flax.

JAX + Attention Learn To Solve Routing Problems Reinplementation of the paper Attention, Learn to Solve Routing Problems! using Jax and Flax. Fully su

Gabriela Surita 7 Dec 01, 2022
Official implementation of "CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D Point Cloud Understanding" (CVPR, 2022)

CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D Point Cloud Understanding (CVPR'22) Paper Link | Project Page Abstract : Manual an

Mohamed Afham 152 Dec 23, 2022
Deep Learning for Morphological Profiling

Deep Learning for Morphological Profiling An end-to-end implementation of a ML System for morphological profiling using self-supervised learning to di

Danielh Carranza 0 Jan 20, 2022
Self-training with Weak Supervision (NAACL 2021)

This repo holds the code for our weak supervision framework, ASTRA, described in our NAACL 2021 paper: "Self-Training with Weak Supervision"

Microsoft 148 Nov 20, 2022
The implementation of the paper "A Deep Feature Aggregation Network for Accurate Indoor Camera Localization".

A Deep Feature Aggregation Network for Accurate Indoor Camera Localization This is the PyTorch implementation of our paper "A Deep Feature Aggregation

9 Dec 09, 2022
DC3: A Learning Method for Optimization with Hard Constraints

DC3: A learning method for optimization with hard constraints This repository is by Priya L. Donti, David Rolnick, and J. Zico Kolter and contains the

CMU Locus Lab 57 Dec 26, 2022
Using deep actor-critic model to learn best strategies in pair trading

Deep-Reinforcement-Learning-in-Stock-Trading Using deep actor-critic model to learn best strategies in pair trading Abstract Partially observed Markov

281 Dec 09, 2022
Point Cloud Denoising input segmentation output raw point-cloud valid/clear fog rain de-noised Abstract Lidar sensors are frequently used in environme

Point Cloud Denoising input segmentation output raw point-cloud valid/clear fog rain de-noised Abstract Lidar sensors are frequently used in environme

75 Nov 24, 2022
Pytorch implementation of set transformer

set_transformer Official PyTorch implementation of the paper Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks .

Juho Lee 410 Jan 06, 2023
[PyTorch] Official implementation of CVPR2021 paper "PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency". https://arxiv.org/abs/2103.05465

PointDSC repository PyTorch implementation of PointDSC for CVPR'2021 paper "PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency",

153 Dec 14, 2022
Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs

PhyCRNet Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs Paper link: [ArXiv] By: Pu Ren, Chengping Rao, Yang

Pu Ren 11 Aug 23, 2022
Unofficial pytorch-lightning implement of Mip-NeRF

mipnerf_pl Unofficial pytorch-lightning implement of Mip-NeRF, Here are some results generated by this repository (pre-trained models are provided bel

Jianxin Huang 159 Dec 23, 2022