Convert game ISO and archives to CD CHD for emulation on Linux.

Overview

tochd

Convert game ISO and archives to CD CHD for emulation.

What is this program for and what are CHD files?

Automation script written in Python as a frontend to 7z and chdman for converting CD formats into CD CHD.

When you are playing CD based games on RetroArch or possibly on any emulator which supports CHD files, then you might want to convert your ISO and CUE+BIN or GDI files into the CHD format. It has the advantage good compression and produces a single file for each CD. This saves a lot of space and makes organization easier.

To achieve this, the separate program chdman from the MAME tools is invoked, which introduced the CHD format in the first place. Often you need to extract those various CD formats from archives such as .7z or .zip files too. The program 7z is used to extract those files, before handing them over for conversion.

Requirements

The script is written in Python 3.10 for Linux. No other Python module is required. The following external applications are required to run the script:

7z
chdman

On my Manjaro system, they are available in the packages: p7zip mame-tools

Installation

No special installation setup is required, other than the above base requirements. Run the script from any directory you want. Give it the executable bit, rename the script to exclude file extension and put it into a folder that is in the systems $PATH . An installation script "install.sh" is provided, but not required.

If you have an older Python version, then you might want to check the binary release package, which bundles up the script and Python interpreter to create a standalone executable.

Optional: Makefile and PyInstaller (you can ignore this part)

The included "Makefile" is to build the package with the standalone binary. It will create a venv, update stuff in it and run PyInstaller from it. If the process fails, then maybe the system package mpdecimal could be required. At least this was required on my Manjaro system.

Usage

usage: tochd [OPTIONS] [FILE ...]

usage: tochd [-h] [--version] [--list-examples] [--list-formats]
             [--list-programs] [--7z CMD] [--chdman CMD] [-d DIR] [-R] [-p]
             [-t NUM] [-c NUM] [-f] [-q] [-E] [-X] [-]
             [file ...]

This is a commandline application without a graphical interface. The most basic operation is to give it a filename, a list of files or directories to work on. The default behaviour is to convert .iso and .cue+bin and .gdi files to .chd files with same basename in their original folders. Archives such as .7z and .zip are extracted and searched for files to convert. The progress information from 7z and chdman are printed to stdout.

How to use the commandline options

Options start with a dash and everything else is file or folder. In example tochd . will search current working directory for files to convert. Using the option -X like this tochd -X . will just list files without processing them. The option -d DIR specifies a directory to output the created .chd files into. In example tochd -q -d ~/chd ~/Downloads will process all files it can find in the "Downloads" directory and save the resulting .chd files in a folder named "chd" in the users home folder. The -q option means "quiet" and will hide progress information from 7z and chdman, but still print out the current job information from the script itself.

You can also specify filenames directly or use shell globbing * in example to give a list of files over. Usually that is not a problem, but if any filename starts with a dash -, then the filename would be interpreted as an option. But you can use the double dash -- to indicate that anything following the double dash is a filename, regardless what the first character is. In example tochd -- *.7z will process all .7z files in current directory.

Use tochd --help to list all options and their brief description.

Examples

$ tochd --help
$ tochd .
$ tochd -X .
$ tochd ~/Downloads
$ tochd -- *.7z
$ tochd -pfq ~/Downloads | grep 'Completed:' | grep -Eo '/.+$'
$ ls -1 | tochd -

Example output

The following is an output from some files I used to test the program. The failing jobs are supposed to fail, for one or another reason. "Completed" jobs are files that are successfully created. "Failed" jobs point to the path that would have been created.

$ tochd -fq cue iso gdi unsupported .
Job 1     Started:	/home/tuncay/Downloads/cue/Vampire Savior (English v1.0).7z
Job 1   Completed:	/home/tuncay/Downloads/cue/Vampire Savior (English v1.0).chd
Job 2     Started:	/home/tuncay/Downloads/cue/3 x 3 Eyes - Sanjiyan Hensei (ACD, SCD)(JPN).zip
Job 2      Failed:	/home/tuncay/Downloads/cue/3 x 3 Eyes - Sanjiyan Hensei (ACD, SCD)(JPN).chd
Job 3     Started:	/home/tuncay/Downloads/cue/Simpsons Wrestling, The (USA).7z
Job 3   Completed:	/home/tuncay/Downloads/cue/Simpsons Wrestling, The (USA).chd
Job 4     Started:	/home/tuncay/Downloads/cue/Shining Wisdom (USA) (DW0355).rar
Job 4   Completed:	/home/tuncay/Downloads/cue/Shining Wisdom (USA) (DW0355).chd
Job 5     Started:	/home/tuncay/Downloads/iso/Parodius_Portable_JPN_PSP-Caravan.iso
Job 5   Completed:	/home/tuncay/Downloads/iso/Parodius_Portable_JPN_PSP-Caravan.chd
Job 6     Started:	/home/tuncay/Downloads/iso/Bust_A_Move_Deluxe_USA_PSP-pSyPSP.iso
Job 6   Completed:	/home/tuncay/Downloads/iso/Bust_A_Move_Deluxe_USA_PSP-pSyPSP.chd
Job 7     Started:	/home/tuncay/Downloads/gdi/[GDI] Metal Slug 6.7z
Job 7   Completed:	/home/tuncay/Downloads/gdi/[GDI] Metal Slug 6.chd
Job 8     Started:	/home/tuncay/Downloads/gdi/[GDI] Virtua Striker 2 (US).7z
Job 8   Completed:	/home/tuncay/Downloads/gdi/[GDI] Virtua Striker 2 (US).chd
Job 9     Started:	/home/tuncay/Downloads/gdi/GigaWing 2.zip
Job 9   Completed:	/home/tuncay/Downloads/gdi/GigaWing 2.chd
Job 10    Started:	/home/tuncay/Downloads/unsupported/Dragon_Ball_Z_Shin_Budokai_USA_PSP-DMU.rar
Job 10     Failed:	/home/tuncay/Downloads/unsupported/Dragon_Ball_Z_Shin_Budokai_USA_PSP-DMU.chd
Job 11    Started:	/home/tuncay/Downloads/unsupported/ActRaiser 2 (USA) (MSU1) [Hack by Conn & Kurrono v4].7z
Job 11     Failed:	/home/tuncay/Downloads/unsupported/ActRaiser 2 (USA) (MSU1) [Hack by Conn & Kurrono v4].chd
Job 12    Started:	/home/tuncay/Downloads/missingfiles.gdi
Job 12     Failed:	/home/tuncay/Downloads/missingfiles.chd

Cancel jobs

At default Ctrl+c in the terminal will abort current job and start next one. Temporary folders and files are removed automatically, but it can't hurt to check manually for confirmation. Temporary folders are hidden starting with a dot in name.

Multiprocessing support

At default all files are processed sequential, only one at a time. Use option -p (short for --parallel) to activate multithreading with 2 threads. This enables the processing of multiple jobs at the same time. Set number of max threads with option -t (short for --threads).

Drawbacks with multiprocessing / parallel option

  • live progress bars and stderror messages of invoked processes from 7z and chdman cannot be provided anymore, as they would have been overlapping on the terminal, but stdout messages such as statistics are still output
  • user input won't be allowed and is automated as much as possible, because overlapping messages could lead to stuck on waiting for input and losing the context to what file it belongs to are potential problems

Additional notes, workarounds and quirks

If you forcefully terminate the script while working, then unfinished files and especially temporary folders cannot be removed anymore. These files and folders can take up huge amount of space! Temporary folders are hidden starting with a dot "." in the name, followed by the name of archive and some random characters added. Make sure these files are deleted, in case you forcefully terminate the script.

Some archives contain multiple folders, each with ISO files of same name. These are usually intended to copy and overwrite files in a main folder as a meaning of patching. However, the script has no understanding and knowledge about this and would try to convert each .iso file on it's own. As a workaround all .iso files in the archive are ignored when a sheet type such as CUE or GDI files are found.

You might also like...
Dcf-game-infrastructure-public - Contains all the components necessary to run a DC finals (attack-defense CTF) game from OOO

dcf-game-infrastructure All the components necessary to run a game of the OOO DC

Torchlight2 lan game server tool - A message forwarding tool for Torchlight 2 lan game

Torchlight 2 Lan Game Server Tool A message forwarding tool for Torchlight 2 lan

MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.

MMdnn MMdnn is a comprehensive and cross-framework tool to convert, visualize and diagnose deep learning (DL) models. The "MM" stands for model manage

A tutorial showing how to train, convert, and run TensorFlow Lite object detection models on Android devices, the Raspberry Pi, and more!
A tutorial showing how to train, convert, and run TensorFlow Lite object detection models on Android devices, the Raspberry Pi, and more!

A tutorial showing how to train, convert, and run TensorFlow Lite object detection models on Android devices, the Raspberry Pi, and more!

Facial detection, landmark tracking and expression transfer library for Windows, Linux and Mac

Welcome to the CSIRO Face Analysis SDK. Documentation for the SDK can be found in doc/documentation.html. All code in this SDK is provided according t

tf2onnx - Convert TensorFlow, Keras and Tflite models to ONNX.

tf2onnx converts TensorFlow (tf-1.x or tf-2.x), tf.keras and tflite models to ONNX via command line or python api.

Simple helper library to convert a collection of numpy data to tfrecord, and build a tensorflow dataset from the tfrecord.

numpy2tfrecord Simple helper library to convert a collection of numpy data to tfrecord, and build a tensorflow dataset from the tfrecord. Installation

Convert Pytorch model to onnx or tflite, and the converted model can be visualized by Netron
Convert Pytorch model to onnx or tflite, and the converted model can be visualized by Netron

Convert Pytorch model to onnx or tflite, and the converted model can be visualized by Netron

This is a repository for a No-Code object detection inference API using the OpenVINO. It's supported on both Windows and Linux Operating systems.
This is a repository for a No-Code object detection inference API using the OpenVINO. It's supported on both Windows and Linux Operating systems.

OpenVINO Inference API This is a repository for an object detection inference API using the OpenVINO. It's supported on both Windows and Linux Operati

Comments
  • Add GDI as supported file extension for conversion

    Add GDI as supported file extension for conversion

    chdman supports the conversion of GDI files, a format used by Sega Dreamcast emulators. Adding it to the list of supported ISO file extensions is enough to enable conversion of GDI files to CHD.

    opened by farmerbb 4
Releases(v0.9)
  • v0.9(Jul 6, 2022)

  • v0.8(Mar 30, 2022)

    • new: pseudo compiled bundle of the script with pyinstaller to build a standalone executable, available on Releases page
    • new: "Makefile" script for make to create the standalone bundle of Python script with the Python interpreter and package it into an archive
    • changed: runs with default options -X ., if no options provided
    • some little internal optimizations or additions, such as code comments
    Source code(tar.gz)
    Source code(zip)
    tochd-0.8-bin.7z(7.26 MB)
Owner
Tuncay
Tuncay
A Strong Baseline for Image Semantic Segmentation

A Strong Baseline for Image Semantic Segmentation Introduction This project is an open source semantic segmentation toolbox based on PyTorch. It is ba

Clark He 49 Sep 20, 2022
Official implementation of the paper 'High-Resolution Photorealistic Image Translation in Real-Time: A Laplacian Pyramid Translation Network' in CVPR 2021

LPTN Paper | Supplementary Material | Poster High-Resolution Photorealistic Image Translation in Real-Time: A Laplacian Pyramid Translation Network Ji

372 Dec 26, 2022
PyTorch implementation of saliency map-aided GAN for Auto-demosaic+denosing

Saiency Map-aided GAN for RAW2RGB Mapping The PyTorch implementations and guideline for Saiency Map-aided GAN for RAW2RGB Mapping. 1 Implementations B

Yuzhi ZHAO 20 Oct 24, 2022
Progressive Growing of GANs for Improved Quality, Stability, and Variation

Progressive Growing of GANs for Improved Quality, Stability, and Variation — Official TensorFlow implementation of the ICLR 2018 paper Tero Karras (NV

Tero Karras 5.9k Jan 05, 2023
SigOpt wrappers for scikit-learn methods

SigOpt + scikit-learn Interfacing This package implements useful interfaces and wrappers for using SigOpt and scikit-learn together Getting Started In

SigOpt 73 Sep 30, 2022
Official implementation for "Style Transformer for Image Inversion and Editing" (CVPR 2022)

Style Transformer for Image Inversion and Editing (CVPR2022) https://arxiv.org/abs/2203.07932 Existing GAN inversion methods fail to provide latent co

Xueqi Hu 153 Dec 02, 2022
The official PyTorch implementation of paper BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition

BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition Boyan Zhou, Quan Cui, Xiu-Shen Wei*, Zhao-Min Chen This repo

Megvii-Nanjing 616 Dec 21, 2022
City-Scale Multi-Camera Vehicle Tracking Guided by Crossroad Zones Code

City-Scale Multi-Camera Vehicle Tracking Guided by Crossroad Zones Requirements Python 3.8 or later with all requirements.txt dependencies installed,

88 Dec 12, 2022
Amazing-Python-Scripts - 🚀 Curated collection of Amazing Python scripts from Basics to Advance with automation task scripts.

📑 Introduction A curated collection of Amazing Python scripts from Basics to Advance with automation task scripts. This is your Personal space to fin

Avinash Ranjan 1.1k Dec 29, 2022
[NeurIPS 2021] The PyTorch implementation of paper "Self-Supervised Learning Disentangled Group Representation as Feature"

IP-IRM [NeurIPS 2021] The PyTorch implementation of paper "Self-Supervised Learning Disentangled Group Representation as Feature". Codes will be relea

Wang Tan 67 Dec 24, 2022
This repo is about to create the Streamlit application for given ML model.

HR-Attritiion-using-Streamlit This repo is about to create the Streamlit application for given ML model. Problem Statement: Managing peoples at workpl

Pavan Giri 0 Dec 10, 2021
Code for "Finding Regions of Heterogeneity in Decision-Making via Expected Conditional Covariance" at NeurIPS 2021

Finding Regions of Heterogeneity in Decision-Making via Expected Conditional Covariance Justin Lim, Christina X Ji, Michael Oberst, Saul Blecker, Leor

Sontag Lab 3 Feb 03, 2022
Implementation of Hourglass Transformer, in Pytorch, from Google and OpenAI

Hourglass Transformer - Pytorch (wip) Implementation of Hourglass Transformer, in Pytorch. It will also contain some of my own ideas about how to make

Phil Wang 61 Dec 25, 2022
Learning to Identify Top Elo Ratings with A Dueling Bandits Approach

Learning to Identify Top Elo Ratings We propose two algorithms MaxIn-Elo and MaxIn-mElo to solve the top players identification on the transitive and

2 Jan 14, 2022
M2MRF: Many-to-Many Reassembly of Features for Tiny Lesion Segmentation in Fundus Images

M2MRF: Many-to-Many Reassembly of Features for Tiny Lesion Segmentation in Fundus Images This repo is the official implementation of paper "M2MRF: Man

12 Dec 14, 2022
Pywonderland - A tour in the wonderland of math with python.

A Tour in the Wonderland of Math with Python A collection of python scripts for drawing beautiful figures and animating interesting algorithms in math

Zhao Liang 4.1k Jan 03, 2023
This is an example of object detection on Micro bacterium tuberculosis using Mask-RCNN

Mask-RCNN on Mycobacterium tuberculosis This is an example of object detection on Mycobacterium Tuberculosis using Mask RCNN. Implement of Mask R-CNN

Jun-En Ding 1 Sep 16, 2021
Urban mobility simulations with Python3, RLlib (Deep Reinforcement Learning) and Mesa (Agent-based modeling)

Deep Reinforcement Learning for Smart Cities Documentation RLlib: https://docs.ray.io/en/master/rllib.html Mesa: https://mesa.readthedocs.io/en/stable

1 May 15, 2022
A framework for GPU based high-performance medical image processing and visualization

FAST is an open-source cross-platform framework with the main goal of making it easier to do high-performance processing and visualization of medical images on heterogeneous systems utilizing both mu

Erik Smistad 315 Dec 30, 2022
Data Consistency for Magnetic Resonance Imaging

Data Consistency for Magnetic Resonance Imaging Data Consistency (DC) is crucial for generalization in multi-modal MRI data and robustness in detectin

Dimitris Karkalousos 19 Dec 12, 2022