The all new way to turn your boring vector meshes into the new fad in town; Voxels!

Overview

Voxelator

The all new way to turn your boring vector meshes into the new fad in town; Voxels!

Notes: I have not tested this on a rotated mesh. With further testing I may improve on this.

It is necessary for a uniform scale on the mesh that is to be voxelated. In otherwords make sure your x scale, y scale, and z scale are all the same. (dimensions may be non-uniform)

I do suggest setting your image scaling to "closest" under your mesh's material settings to fully cover each face in a single color.

Installation: To install simply go to the top tool bar in blender under edit> preferences > addons > install, then choose voxelator.py Once you are done simply select a single object, then in 3d view mode go under object > voxelate

Options: Resolution size: Affects how many cubes will fill the longest axis of the mesh (other axis will have an automated amount) Warning: Resolution affects load times of voxelation dramatically.

Fill volume: Whether or not to fill the entire voxelated mesh with cubes.

Separate Cubes: Cubes Will not be attached by vertices, they will each be their own individual cube. It does what it says on the tin.

Example:

Here is a model courtesy of: https://opengameart.org/users/quandtum original

And then here it is after being voxelated with a resolution of 64. voxelated

And the wireframe showing off those sweet generated cubes and totally empty volume. wireframe_voxelated

And here's a lil place you can help me if you're feeling gratuitous: https://www.patreon.com/TITANDERP

QueryDet: Cascaded Sparse Query for Accelerating High-Resolution SmallObject Detection

QueryDet-PyTorch This repository is the official implementation of our paper: QueryDet: Cascaded Sparse Query for Accelerating High-Resolution Small O

Chenhongyi Yang 276 Dec 31, 2022
PyTorch implementation of SCAFFOLD (Stochastic Controlled Averaging for Federated Learning, ICML 2020).

Scaffold-Federated-Learning PyTorch implementation of SCAFFOLD (Stochastic Controlled Averaging for Federated Learning, ICML 2020). Environment numpy=

KI 30 Dec 29, 2022
YOLOv5 in PyTorch > ONNX > CoreML > TFLite

This repository represents Ultralytics open-source research into future object detection methods, and incorporates lessons learned and best practices evolved over thousands of hours of training and e

Ultralytics 34.1k Dec 31, 2022
Open standard for machine learning interoperability

Open Neural Network Exchange (ONNX) is an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides

Open Neural Network Exchange 13.9k Dec 30, 2022
TuckER: Tensor Factorization for Knowledge Graph Completion

TuckER: Tensor Factorization for Knowledge Graph Completion This codebase contains PyTorch implementation of the paper: TuckER: Tensor Factorization f

Ivana Balazevic 296 Dec 06, 2022
3D dataset of humans Manipulating Objects in-the-Wild (MOW)

MOW dataset [Website] This repository maintains our 3D dataset of humans Manipulating Objects in-the-Wild (MOW). The dataset contains 512 images in th

Zhe Cao 28 Nov 06, 2022
Implementation of Kalman Filter in Python

Kalman Filter in Python This is a basic example of how Kalman filter works in Python. I do plan on refactoring and expanding this repo in the future.

Enoch Kan 35 Sep 11, 2022
Out-of-distribution detection using the pNML regret. NeurIPS2021

OOD Detection Load conda environment conda env create -f environment.yml or install requirements: while read requirement; do conda install --yes $requ

Koby Bibas 23 Dec 02, 2022
Collection of Docker images for ML/DL and video processing projects

Collection of Docker images for ML/DL and video processing projects. Overview of images Three types of images differ by tag postfix: base: Python with

OSAI 87 Nov 22, 2022
Human annotated noisy labels for CIFAR-10 and CIFAR-100.

Dataloader for CIFAR-N CIFAR-10N noise_label = torch.load('./data/CIFAR-10_human.pt') clean_label = noise_label['clean_label'] worst_label = noise_lab

<a href=[email protected]"> 117 Nov 30, 2022
Deep Crop Rotation

Deep Crop Rotation Paper (to come very soon!) We propose a deep learning approach to modelling both inter- and intra-annual patterns for parcel classi

Félix Quinton 5 Sep 23, 2022
A data-driven approach to quantify the value of classifiers in a machine learning ensemble.

Documentation | External Resources | Research Paper Shapley is a Python library for evaluating binary classifiers in a machine learning ensemble. The

Benedek Rozemberczki 188 Dec 29, 2022
Gradient representations in ReLU networks as similarity functions

Gradient representations in ReLU networks as similarity functions by Dániel Rácz and Bálint Daróczy. This repo contains the python code related to our

1 Oct 08, 2021
A Comparative Framework for Multimodal Recommender Systems

Cornac Cornac is a comparative framework for multimodal recommender systems. It focuses on making it convenient to work with models leveraging auxilia

Preferred.AI 671 Jan 03, 2023
Tensorflow port of a full NetVLAD network

netvlad_tf The main intention of this repo is deployment of a full NetVLAD network, which was originally implemented in Matlab, in Python. We provide

Robotics and Perception Group 225 Nov 08, 2022
Code for the paper: Adversarial Machine Learning: Bayesian Perspectives

Code for the paper: Adversarial Machine Learning: Bayesian Perspectives This repository contains code for reproducing the experiments in the ** Advers

Roi Naveiro 2 Nov 11, 2022
State-to-Distribution (STD) Model

State-to-Distribution (STD) Model In this repository we provide exemplary code on how to construct and evaluate a state-to-distribution (STD) model fo

<a href=[email protected]"> 2 Apr 07, 2022
Performant, differentiable reinforcement learning

deluca Performant, differentiable reinforcement learning Notes This is pre-alpha software and is undergoing a number of core changes. Updates to follo

Google 114 Dec 27, 2022
Weakly-supervised object detection.

Wetectron Wetectron is a software system that implements state-of-the-art weakly-supervised object detection algorithms. Project CVPR'20, ECCV'20 | Pa

NVIDIA Research Projects 342 Jan 05, 2023
Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and Noisy Student Training

Flood Detection Challenge This repository contains code for our submission to the ETCI 2021 Competition on Flood Detection (Winning Solution #2). Acco

Siddha Ganju 108 Dec 28, 2022