Encode Forge v0.4.0 - Audio Normalization, Performance Updates, and Bug Fixes

This release consolidates features developed across branches v0.3.2 and v0.3.3 into a stable production release. Version 0.4.0 focuses on audio normalization capabilities, GPU-accelerated AI subtitle generation, UI/UX polish, and significant performance optimizations.

Highlights

Audio Normalization

Ensure consistent audio levels across all your media files with the new audio normalization feature.

• Integrated directly into the encoding workflow
• Configurable through settings
• Works with all supported hardware encoders

GPU-Accelerated AI Subtitles

10x-20x faster subtitle generation with intelligent GPU support!

• Automatic GPU Detection - Detects NVIDIA CUDA, AMD ROCm, or Apple Silicon
• Smart PyTorch Installation - Downloads the correct PyTorch version for your hardware
• Fallback Support - Automatically uses CPU if no GPU is available
• Universal Compatibility - Works on Windows (CUDA only), macOS (Intel & Apple Silicon), and Linux

Enhanced User Interface

A more polished and professional interface with improved visual depth and better component scaling.

• Enhanced dark theme with improved contrast
• Minimum component sizes for better readability
• Better layout scaling across different screen sizes
• More consistent styling throughout the application

Performance Improvements

Faster startup times and reduced memory usage through intelligent lazy loading.

• Lazy Module Initialization - Core modules load only when needed
• Reduced Memory Footprint - Lower RAM usage, especially on startup
• Faster Application Launch - Improved initialization sequence
• Better Process Handling - Enhanced Python API performance

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What's New

Added Features

Audio Processing

• Audio Normalization Flag (998f7ae)
  • Normalize audio levels during encoding
  • Configurable normalization settings
  • Works alongside all hardware acceleration options

AI Subtitle Generation

• Intelligent GPU Support (fa8d13a)

  • Automatic detection of NVIDIA, AMD, and Apple Silicon GPUs
  • Platform-specific PyTorch installation (CUDA, ROCm, MPS)
  • Dramatic speed improvements on compatible hardware

• Enhanced Whisper Processing (e34463c)

  • Optimized device selection
  • Better resource management
  • Support for macOS M1/M2/M3 GPUs

UI/UX Improvements

• Visual Polish (1687422)
  • Added depth to UI components
  • Minimum component sizes for consistency
  • Improved component spacing and alignment
  • Better visual hierarchy

Performance Enhancements

• Lazy Loading (9de93c6, ed3800e)
  • Whisper manager loads on-demand
  • Core Python modules initialize when needed
  • Faster application startup
  • Lower initial memory usage

Bug Fixes

• Whisper AI Setup (eed524c)
  • Fixed initialization dialog issues
  • Improved error handling
  • Better feedback during installation

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Installation

Download

Choose the installer for your platform:

Note: macOS builds hang on opening. I don't use macOS and have limiited access to one.

• Windows: EncodeForge-0.4.0-windows-x64.exe or .msi
• Linux (Debian/Ubuntu): encodeforge_0.4.0-1_amd64.deb
• Linux (Fedora/RHEL): encodeforge-0.4.0-1.x86_64.rpm
• macOS (Intel): EncodeForge-0.4.0-macos-x64.dmg
• macOS (Apple Silicon): EncodeForge-0.4.0-macos-arm64.dmg

First-Time Setup

On first launch, EncodeForge will automatically:

1. Download and install FFmpeg (~100-150 MB)
2. Install required Python libraries (~50 MB)
3. Configure everything with a progress window

This one-time setup takes 2-5 minutes depending on your internet connection.

Optional: AI Subtitle Generation

Install GPU-accelerated Whisper AI later through:
Tools → Setup AI Subtitles

The installer will automatically detect your GPU and download the appropriate PyTorch version!

Known Issues

None at this time. Please report issues at: https://github.com/SirStig/EncodeForge/issues

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