Processed, version controlled history of Minecraft's generated data and assets

Related tags

Deep Learningmcmeta
Overview

mcmeta

Processed, version controlled history of Minecraft's generated data and assets

Repository structure

Each of the following branches has a commit per version. Starting from 1.14, updated to the latest snapshot. Each commit is tagged <version>-<branch>.

  • summary - Branch with condensed reports from the data generator or assets, in a variety of formats.
    • blocks - Containing block state properties and defaults for all necessary blocks.
    • commands - The brigadier command tree.
    • registries - Collections of resource locations. Including the generated registries, data, and assets.
    • sounds - The sounds.json from assets.
    • versions - A list of versions up to that point ordered with the most recent first. Each entry has the same format as the version.json at the root of each branch.
  • data - The vanilla data as it if would appear in a data pack.
  • data-json - The same as data but only containing json files, so excluding structures.
  • assets - The vanilla assets is if they would appear in a resource pack.
  • assets-json - The same as assets but only containing json files, so excluding textures, sounds and shaders.

Sources

  • Version manifest, a list of versions and metadata, client and server jars by following links
  • Sound files from Mojang's API following the version manifest
  • Data generator using the following command:
    java -cp server.jar net.minecraft.data.Main --server --reports
  • Slicedlime's examples repo for worldgen changes before 1.18-pre1

Credits

This project has taken inspiration from Arcensoth/mcdata and SPGoding/vanilla-datapack.

Disclaimer

mcmeta is not an official Minecraft product, and is not endorsed by or associated with Mojang Studios. All data and assets were obtained through Mojang's internal data generator and public API. If Mojang ever has something against this data existing here, the repository will be promptly removed.

Owner
Misode
Misode
Some experiments with tennis player aging curves using Hilbert space GPs in PyMC. Only experimental for now.

NOTE: This is still being developed! Setup notes This document uses Jeff Sackmann's tennis data. You can obtain it as follows: git clone https://githu

Martin Ingram 1 Jan 20, 2022
PyMatting: A Python Library for Alpha Matting

Given an input image and a hand-drawn trimap (top row), alpha matting estimates the alpha channel of a foreground object which can then be composed onto a different background (bottom row).

PyMatting 1.4k Dec 30, 2022
🔀 Visual Room Rearrangement

AI2-THOR Rearrangement Challenge Welcome to the 2021 AI2-THOR Rearrangement Challenge hosted at the CVPR'21 Embodied-AI Workshop. The goal of this cha

AI2 55 Dec 22, 2022
An ever-growing playground of notebooks showcasing CLIP's impressive zero-shot capabilities.

Playground for CLIP-like models Demo Colab Link GradCAM Visualization Naive Zero-shot Detection Smarter Zero-shot Detection Captcha Solver Changelog 2

Kevin Zakka 101 Dec 30, 2022
Region-aware Contrastive Learning for Semantic Segmentation, ICCV 2021

Region-aware Contrastive Learning for Semantic Segmentation, ICCV 2021 Abstract Recent works have made great success in semantic segmentation by explo

Hanzhe Hu 30 Dec 29, 2022
Code for our ALiBi method for transformer language models.

Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation This repository contains the code and models for our paper Tra

Ofir Press 211 Dec 31, 2022
MGFN: Multi-Graph Fusion Networks for Urban Region Embedding was accepted by IJCAI-2022.

Multi-Graph Fusion Networks for Urban Region Embedding (IJCAI-22) This is the implementation of Multi-Graph Fusion Networks for Urban Region Embedding

202 Nov 18, 2022
A Transformer-Based Siamese Network for Change Detection

ChangeFormer: A Transformer-Based Siamese Network for Change Detection (Under review at IGARSS-2022) Wele Gedara Chaminda Bandara, Vishal M. Patel Her

Wele Gedara Chaminda Bandara 214 Dec 29, 2022
Explicable Reward Design for Reinforcement Learning Agents [NeurIPS'21]

Explicable Reward Design for Reinforcement Learning Agents [NeurIPS'21]

3 May 12, 2022
Evaluating deep transfer learning for whole-brain cognitive decoding

Evaluating deep transfer learning for whole-brain cognitive decoding This README file contains the following sections: Project description Repository

Armin Thomas 5 Oct 31, 2022
This repo contains the source code and a benchmark for predicting user's utilities with Machine Learning techniques for Computational Persuasion

Machine Learning for Argument-Based Computational Persuasion This repo contains the source code and a benchmark for predicting user's utilities with M

Ivan Donadello 4 Nov 07, 2022
High performance Cross-platform Inference-engine, you could run Anakin on x86-cpu,arm, nv-gpu, amd-gpu,bitmain and cambricon devices.

Anakin2.0 Welcome to the Anakin GitHub. Anakin is a cross-platform, high-performance inference engine, which is originally developed by Baidu engineer

514 Dec 28, 2022
MADE (Masked Autoencoder Density Estimation) implementation in PyTorch

pytorch-made This code is an implementation of "Masked AutoEncoder for Density Estimation" by Germain et al., 2015. The core idea is that you can turn

Andrej 498 Dec 30, 2022
Code for layerwise detection of linguistic anomaly paper (ACL 2021)

Layerwise Anomaly This repository contains the source code and data for our ACL 2021 paper: "How is BERT surprised? Layerwise detection of linguistic

6 Dec 07, 2022
Source code of generalized shuffled linear regression

Generalized-Shuffled-Linear-Regression Code for the ICCV 2021 paper: Generalized Shuffled Linear Regression. Authors: Feiran Li, Kent Fujiwara, Fumio

FEI 7 Oct 26, 2022
Supplementary code for the AISTATS 2021 paper "Matern Gaussian Processes on Graphs".

Matern Gaussian Processes on Graphs This repo provides an extension for gpflow with Matérn kernels, inducing variables and trainable models implemente

41 Dec 17, 2022
Code for our EMNLP 2021 paper "Learning Kernel-Smoothed Machine Translation with Retrieved Examples"

KSTER Code for our EMNLP 2021 paper "Learning Kernel-Smoothed Machine Translation with Retrieved Examples" [paper]. Usage Download the processed datas

jiangqn 23 Nov 24, 2022
Code I use to automatically update my videos' metadata on YouTube

mCodingYouTube This repository contains the code I use to automatically update my videos' metadata on YouTube, including: titles, descriptions, tags,

James Murphy 19 Oct 07, 2022
Paddle-Skeleton-Based-Action-Recognition - DecoupleGCN-DropGraph, ASGCN, AGCN, STGCN

Paddle-Skeleton-Action-Recognition DecoupleGCN-DropGraph, ASGCN, AGCN, STGCN. Yo

Chenxu Peng 3 Nov 02, 2022
ULMFiT for Genomic Sequence Data

Genomic ULMFiT This is an implementation of ULMFiT for genomics classification using Pytorch and Fastai. The model architecture used is based on the A

Karl 276 Dec 12, 2022