Getting Started

Getting Started

This guide walks you through installing and setting up the DDD Capture Toolkit.

Prerequisites

Before you begin, ensure you have:

• Conda - Miniconda or Anaconda package manager
• Git - For cloning and managing submodules
• Domesday Duplicator hardware - For RF capture
• Clockgen Lite mod - Recommended for synchronised audio capture
• Linux - Primary supported platform (macOS and Windows via WSL also work)

Installation

Step 1: Clone the Repository

Clone the repository with all submodules:

git clone --recurse-submodules https://github.com/yourname/ddd-capture-toolkit.git
cd ddd-capture-toolkit

If you've already cloned without submodules:

git submodule update --init --recursive

Step 2: Run Setup

The toolkit provides two installation modes:

Easy Mode (Recommended for most users)

./setup.sh

• Uses pre-compiled conda packages
• Approximately 5 minute setup
• Good performance for most users

Performance Mode

./setup.sh --performance

• Compiles from source with CPU-specific optimisations
• 30-60 minute setup time
• 10-30% faster processing
• Recommended for production archival work

Additional Setup Options

# Specify a particular vhs-decode version
./setup.sh --performance --vhs-decode-version 0.3.8.1

# Use the latest bleeding-edge version
./setup.sh --performance --vhs-decode-version latest

# Uninstall the toolkit
./setup.sh --uninstall

# Clean reinstall
./clean-setup.sh && ./setup.sh

Step 3: Activate and Launch

conda activate ddd-capture-toolkit
python3 ddd_main_menu.py

Or use the convenience script:

./start.sh

First-Time Configuration

Configure Processing Locations

Before you can process files, tell the toolkit where your capture files are located:

1. Launch the main menu: python3 ddd_main_menu.py
2. Select Menu Option 4 - Configuration
3. Select Manage Processing Locations
4. Add your capture directory paths

You can add multiple locations (e.g., different drives or network shares).

Check Dependencies

Verify all dependencies are correctly installed:

1. From the main menu, select System
2. Select Check Dependencies

This will verify that vhs-decode, tbc-video-export, FFmpeg, and other required tools are available.

Directory Structure

After setup, your toolkit directory will contain:

ddd-capture-toolkit/
├── config/                  # Configuration files
│   ├── config.json         # Main configuration
│   ├── processing_locations.json  # Your capture directories
│   ├── job_queue.json      # Persistent job queue
│   └── project_flags.json  # Per-project flag settings
├── external/               # Git submodules
│   ├── vhs-decode/        # VHS RF decoder
│   ├── ld-decode/         # LD-decode tools
│   ├── tbc-video-export/  # TBC to video converter
│   └── DomesdayDuplicator/ # DdD software
├── tools/                  # Additional tools
│   ├── audio-sync/        # Audio alignment scripts
│   └── timecode-generator/ # Test pattern generation
├── logs/                   # Log files
└── *.py                    # Main Python scripts

Project File Naming

The toolkit uses a consistent naming convention. A project named MyTape will produce:

Stage	File	Description
Capture	MyTape.lds	Raw RF capture
Capture	MyTape.flac	Captured audio
Capture	MyTape.json	Capture metadata
Decode	MyTape.tbc	Time Base Corrected video
Decode	MyTape.tbc.json	TBC metadata (different from capture .json)
Compress	MyTape.tbc.lz4	Compressed TBC
Export	MyTape_ffv1.mkv	Lossless FFV1 video
Align	MyTape_aligned.flac	Synchronised audio
Final	MyTape_final.mkv	Final muxed output

Video Standard Detection

PAL and NTSC are automatically detected from the capture metadata JSON file. You don't need to manually specify the video standard - the toolkit reads it from the capture and applies the correct settings automatically.

Next Steps

• Workflow Control Centre - Learn how to use the main processing interface
• Project Flags - Configure per-project options
• Segment Mode - Test with short segments before full processing