A Dying Light 2 (DL2) PAKFile Utility for Modders and Mod Makers.

Overview

Dying Light 2 PAKFile Utility

A Dying Light 2 (DL2) PAKFile Utility for Modders and Mod Makers.
This tool aims to make PAKFile (.pak files) modding a breeze for both Dying Light 2 modders and mod makers.
See the roadmap for a better idea of what's to come!
More TBA Soon.

Features

  • Ability to Examine PAKFiles (see size, validity, and any CRC / Header mismatch errors)
  • Ability to Extract PAKFiles into a Folder to Edit
  • Ability to Build a PAKFile from a Folder

Known Bugs / Issues

This is a collective list of known bugs / glitches / issues.

  • None / TBA

Running the Utility

As an Executable / Binary

Step-by-step instructions to running the utility as a standalone executable.

  1. Download the Latest Release from GitHub.
  2. Save it somewhere easy to remember. A mod management folder is recommended.
  3. Right-Click the DL2-PAKFile-Utility.exe File and Select Run as Administrator
  4. Follow the On-Screen Prompts

From Source

Step-by-step instructions to running the utility from source.

  1. Open an Elevated Command Prompt
  2. Make a Virtual Environment and Activate it
  3. pip install -r requirements.txt
  4. python main.py
  5. ???
  6. $$ PROFIT $$

Making Mods

The location of the two default PAKFiles (data0.pak and data1.pak) is \steamapps\common\Dying Light 2\ph\source . Opening these PAKFiles and extracting them allows you to see all of the scripts that run in the game's engine, the C-Engine. To make a mod, extract one of these PAKFiles and then simply find the files inside of the extracted contents that include what you wish to change, modify them how you'd like, delete everything else that wasn't changed, and then build a PAKFile from that folder! To use the mod you've made, build it as dataN.pak where N is the next highest available number in your default PAKFile location (for example, if you only have data0.pak and data1.pak, you'd build a data3.pak). If other users wish to use it and they have a different number of PAKFiles than you, they may simply rename it to be a higher number in the filename.

Theory on Mod Loading Order

As writing a new mod makes use of upping the integer in the dataN.pak filenames, I'm assuming the higher the integer, the higher the order of precedence is. This is perhaps to say, for example, if one mod (data3.pak) gives unlimited stamina and another (data4.pak) removes unlimited stamina, I believe data4.pak's effects would take priority over data3.pak's and would render stamina untouched / not unlimited.

FAQ

Q1: Why does this need to be ran as an administrator?
A1: Some people store their games / mod management folders in weird places that non-elevated applications typically can't access. This is simply insurance on that possibility, making sure any user who stores their files anywhere can use this tool!
Q2: Why not opt for a better compression algorithm?
A2: This application originally used LZMA compression, which works great, but is unfortunately unsupported by C-Engine. It appears the current compression method, the default zip compression method of deflation, is the only functioning method of compressing .pak files.

Roadmap

This is a loose outline of what is in the future for the DL2 PAKFile Utility!

  • Ability to Examine PAKFiles (see size, validity, and any CRC / Header mismatch errors)
  • Ability to Extract PAKFiles into a Folder to Edit
  • Ability to Build a PAKFile from a Folder
  • Search PAKFiles for Specific Contents
  • GUI Integration
  • Intelligently Browse DL2 PAKFile Folder Contents (MOD MANAGER FUNCTIONALITY)
  • Detailed Documentation for both the Application and for Modding DL2
  • Auto-Updating Feature for the Utility that Pulls from GitHub
  • More Modding Tools Built-In

More to be Announced Soon!

You might also like...
CVPR '21: In the light of feature distributions: Moment matching for Neural Style Transfer
CVPR '21: In the light of feature distributions: Moment matching for Neural Style Transfer

In the light of feature distributions: Moment matching for Neural Style Transfer (CVPR 2021) This repository provides code to recreate results present

CondenseNet: Light weighted CNN for mobile devices
CondenseNet: Light weighted CNN for mobile devices

CondenseNets This repository contains the code (in PyTorch) for "CondenseNet: An Efficient DenseNet using Learned Group Convolutions" paper by Gao Hua

A light-weight image labelling tool for Python designed for creating segmentation data sets.
A light-weight image labelling tool for Python designed for creating segmentation data sets.

An image labelling tool for creating segmentation data sets, for Django and Flask.

Official code of
Official code of "R2RNet: Low-light Image Enhancement via Real-low to Real-normal Network."

R2RNet Official code of "R2RNet: Low-light Image Enhancement via Real-low to Real-normal Network." Jiang Hai, Zhu Xuan, Ren Yang, Yutong Hao, Fengzhu

LLVIP: A Visible-infrared Paired Dataset for Low-light Vision
LLVIP: A Visible-infrared Paired Dataset for Low-light Vision

LLVIP: A Visible-infrared Paired Dataset for Low-light Vision Project | Arxiv | Abstract It is very challenging for various visual tasks such as image

PyTorch Implementation of
PyTorch Implementation of "Light Field Image Super-Resolution with Transformers"

LFT PyTorch implementation of "Light Field Image Super-Resolution with Transformers", arXiv 2021. [pdf]. Contributions: We make the first attempt to a

Light-weight network, depth estimation, knowledge distillation, real-time depth estimation, auxiliary data.
Light-weight network, depth estimation, knowledge distillation, real-time depth estimation, auxiliary data.

light-weight-depth-estimation Boosting Light-Weight Depth Estimation Via Knowledge Distillation, https://arxiv.org/abs/2105.06143 Junjie Hu, Chenyou F

Yolo Traffic Light Detection With Python

Yolo-Traffic-Light-Detection This project is based on detecting the Traffic light. Pretained data is used. This application entertained both real time

Implementation of light baking system for ray tracing based on Activision's UberBake

Vulkan Light Bakary MSU Graphics Group Student's Diploma Project Treefonov Andrey [GitHub] [LinkedIn] Project Goal The goal of the project is to imple

Releases(v0.4.6)
  • v0.4.6(Feb 11, 2022)

    v0.4.6 | General Improvements

    This release is just an update to fix some crashing issues (now gives detailed error output and won't close / exit the application) and to address the false-flagging by some anti-virus softwares of this application. It should now give 0 flags on an anti-virus, and should feel a lot smoother in terms of user experience. Also addressed was a minor formatting but when the rebuild feature has been enabled with errors giving a limit of 1-4 when the limit is 1-6 for the main menu selection integer.

    Known Issues

    There are no known issues within this release.

    Upcoming

    Full cross-platform support is planned, and the GUI is a work-in-progress! Big things are coming to this utility soon. Plans for a fully-functional and fully-featured mod loader / manager are in the works.

    Changelog

    This is what is new or different:

    • Better Error and Exception Handling (no more random crashes)
    • Fixed Integer Bounds Formatting
    • Cleanly-Built Pyinstaller Bootloader to Fix False AV Flags
    Source code(tar.gz)
    Source code(zip)
    DL2-PAKFile-Utility.exe(7.29 MB)
  • v0.3.9(Feb 10, 2022)

    v0.3.9 | Hotfix and Improvements

    This is a hotfix. It is intended to fix a bug with built PAKFiles not loading properly into Dying Light 2 / C-Engine. The issue was with LZMA vs Deflation compression methods. Additionally, an option to rebuild the last built .pak has been added for rapid development as you tweak the mods you're making. There won't be much in terms of information in this release, as more work is still being done for future updates. This is simply a hotfix release coupled with a feature request.

    Known Issues

    There is one main issue to be aware of for this release:
    False-Flagging for Antiviruses

    • See this link for an in-depth explanation.
    • TL;DR - a lot of people use pyinstaller, the tool used to freeze the executable, for malicious purposes. Thusly, applications built with the signature of pyinstaller may also be flagged as a virus simply by association of the method used to compile the executable.
    • This will be fixed soon once I've rewritten the pyinstaller bootloader, or possibly switched to nuitka.
    • If the issue annoys you or gives you problems, simply create an antivirus / firewall exception for the app, or build it from source yourself.

    Changelog

    This is what is new or different:

    • Application-Built PAKs Now Work Properly with Dying Light 2 / C-Engine
    • Ability to Rebuild Last PAK from Main Menu
    • Changed Icon Color to Neon Cyan for Visibility (Contrast to Dying Light 2 Game Icon)
    Source code(tar.gz)
    Source code(zip)
    DL2-PAKFile-Utility.exe(7.29 MB)
  • v0.0.1(Feb 9, 2022)

    v0.0.1 | Initial Release

    This is an initial release. It is being released as a "beta" because it's more in a beta state and not in an ideal "release" state currently.
    By no means is it complete and / or finished. It is still lacking in a lot of ways that I wish to improve upon in the near future (see the roadmap).
    Make sure to read the instructions on how to run it before getting upset that it's "immediately closing".
    There are bound to be some bugs and errors, and I implore you to report them in this repository's issue tracker.

    Features

    With all of that being said, here is what you can expect to be working as of this release:

    • Ability to Examine PAKFiles (see size, validity, and any CRC / Header mismatch errors)
    • Ability to Extract PAKFiles into a Folder to Edit
    • Ability to Build a PAKFile from a Folder
    • Incredibly Efficient Mod Builder with 79% (21% of Original Size) LZMA Compression on the size of the mods!
    Source code(tar.gz)
    Source code(zip)
    DL2-PAKFile-Utility.exe(7.55 MB)
Owner
RHQ Online
RHQ Online.
RHQ Online
Analyses of the individual electric field magnitudes with Roast.

Aloi Davide - PhD Student (UoB) Analysis of electric field magnitudes (wp2a dataset only at the moment) and correlation analysis with Dynamic Causal M

Davide Aloi 7 Dec 15, 2022
Automatic Number Plate Recognition using Contours and Convolution Neural Networks (CNN)

Cite our paper if you find this project useful https://www.ijariit.com/manuscripts/v7i4/V7I4-1139.pdf Abstract Image processing technology is used in

Adithya M 2 Jun 28, 2022
Re-implememtation of MAE (Masked Autoencoders Are Scalable Vision Learners) using PyTorch.

mae-repo PyTorch re-implememtation of "masked autoencoders are scalable vision learners". In this repo, it heavily borrows codes from codebase https:/

Peng Qiao 1 Dec 14, 2021
PyTorch code for ICLR 2021 paper Unbiased Teacher for Semi-Supervised Object Detection

Unbiased Teacher for Semi-Supervised Object Detection This is the PyTorch implementation of our paper: Unbiased Teacher for Semi-Supervised Object Detection

Facebook Research 366 Dec 28, 2022
This repository contains the code used for the implementation of the paper "Probabilistic Regression with HuberDistributions"

Public_prob_regression_with_huber_distributions This repository contains the code used for the implementation of the paper "Probabilistic Regression w

David Mohlin 1 Dec 04, 2021
Rainbow DQN implementation that outperforms the paper's results on 40% of games using 20x less data 🌈

Rainbow 🌈 An implementation of Rainbow DQN which outperforms the paper's (Hessel et al. 2017) results on 40% of tested games while using 20x less dat

Dominik Schmidt 31 Dec 21, 2022
KGDet: Keypoint-Guided Fashion Detection (AAAI 2021)

KGDet: Keypoint-Guided Fashion Detection (AAAI 2021) This is an official implementation of the AAAI-2021 paper "KGDet: Keypoint-Guided Fashion Detecti

Qian Shenhan 35 Dec 29, 2022
DiffWave is a fast, high-quality neural vocoder and waveform synthesizer.

DiffWave DiffWave is a fast, high-quality neural vocoder and waveform synthesizer. It starts with Gaussian noise and converts it into speech via itera

LMNT 498 Jan 03, 2023
Codes for the ICCV'21 paper "FREE: Feature Refinement for Generalized Zero-Shot Learning"

FREE This repository contains the reference code for the paper "FREE: Feature Refinement for Generalized Zero-Shot Learning". [arXiv][Paper] 1. Prepar

Shiming Chen 28 Jul 29, 2022
CVPR 2021 Challenge on Super-Resolution Space

Learning the Super-Resolution Space Challenge NTIRE 2021 at CVPR Learning the Super-Resolution Space challenge is held as a part of the 6th edition of

andreas 104 Oct 26, 2022
Code for a seq2seq architecture with Bahdanau attention designed to map stereotactic EEG data from human brains to spectrograms, using the PyTorch Lightning.

stereoEEG2speech We provide code for a seq2seq architecture with Bahdanau attention designed to map stereotactic EEG data from human brains to spectro

15 Nov 11, 2022
Kaggle Feedback Prize - Evaluating Student Writing 15th solution

Kaggle Feedback Prize - Evaluating Student Writing 15th solution First of all, I would like to thank the excellent notebooks and discussions from http

Lingyuan Zhang 6 Mar 24, 2022
Code + pre-trained models for the paper Keeping Your Eye on the Ball Trajectory Attention in Video Transformers

Motionformer This is an official pytorch implementation of paper Keeping Your Eye on the Ball: Trajectory Attention in Video Transformers. In this rep

Facebook Research 192 Dec 23, 2022
Code for Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights

Piggyback: https://arxiv.org/abs/1801.06519 Pretrained masks and backbones are available here: https://uofi.box.com/s/c5kixsvtrghu9yj51yb1oe853ltdfz4q

Arun Mallya 165 Nov 22, 2022
A resource for learning about deep learning techniques from regression to LSTM and Reinforcement Learning using financial data and the fitness functions of algorithmic trading

A tour through tensorflow with financial data I present several models ranging in complexity from simple regression to LSTM and policy networks. The s

195 Dec 07, 2022
A complete speech segmentation system using Kaldi and x-vectors for voice activity detection (VAD) and speaker diarisation.

bbc-speech-segmenter: Voice Activity Detection & Speaker Diarization A complete speech segmentation system using Kaldi and x-vectors for voice activit

BBC 16 Oct 27, 2022
Intrinsic Image Harmonization

Intrinsic Image Harmonization [Paper] Zonghui Guo, Haiyong Zheng, Yufeng Jiang, Zhaorui Gu, Bing Zheng Here we provide PyTorch implementation and the

VISION @ OUC 44 Dec 21, 2022
Learning Pixel-level Semantic Affinity with Image-level Supervision for Weakly Supervised Semantic Segmentation, CVPR 2018

Learning Pixel-level Semantic Affinity with Image-level Supervision This code is deprecated. Please see https://github.com/jiwoon-ahn/irn instead. Int

Jiwoon Ahn 337 Dec 15, 2022
PPLNN is a Primitive Library for Neural Network is a high-performance deep-learning inference engine for efficient AI inferencing

PPLNN is a Primitive Library for Neural Network is a high-performance deep-learning inference engine for efficient AI inferencing

943 Jan 07, 2023
Code for Neural-GIF: Neural Generalized Implicit Functions for Animating People in Clothing(ICCV21)

NeuralGIF Code for Neural-GIF: Neural Generalized Implicit Functions for Animating People in Clothing(ICCV21) We present Neural Generalized Implicit F

Garvita Tiwari 104 Nov 18, 2022