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Advanced Video Encoder

A comprehensive Python-based video encoding application with hardware acceleration support, intelligent resolution scaling, and real-time progress monitoring.

Features

Hardware Detection & Acceleration

  • Automatic GPU Detection: Detects NVIDIA GeForce, AMD Radeon, and Intel integrated graphics
  • Hardware Acceleration: Supports NVIDIA NVENC, AMD VCE, and Intel QuickSync
  • Smart Codec Selection: Automatically selects the best encoder based on available hardware
  • Fallback Support: Falls back to CPU-based encoding when hardware acceleration is unavailable

Resolution Management

  • Preset Resolutions: HD (720p), FHD (1080p), QHD (1440p), UHD (4K)
  • Intelligent Scaling: Automatically downscales videos exceeding target resolution
  • Aspect Ratio Preservation: Maintains original aspect ratio during scaling
  • No Unnecessary Upscaling: Preserves smaller videos at their original resolution

Encoding Methods

  • Quality-Based (CRF): Constant Rate Factor encoding for consistent quality
  • Bitrate-Based (VBR): Variable bitrate encoding with customizable multipliers
  • Quality Presets: Ultra High, High, Medium, Low, Very Low quality settings
  • Custom Parameters: Fine-tune encoding settings for specific requirements

Real-Time Interface

  • Rich Terminal UI: Beautiful progress bars and real-time statistics
  • Live Progress Tracking: Monitor encoding progress for each file
  • Comprehensive Statistics: File sizes, compression ratios, encoding times
  • Error Handling: Detailed error reporting and failed file management

Requirements

  • Python 3.8 or higher
  • FFmpeg installed and accessible in PATH
  • Supported video formats: MP4, AVI, MKV, MOV, WMV, FLV, WebM, M4V

Installation

  1. Clone the repository:

    git clone <repository-url>
cd Auto-Encoder-Py

  2. Install dependencies:

    pip install -r requirements.txt

  3. Install FFmpeg:

Usage

Basic Usage

Run the application:

python main.py

Follow the interactive prompts to:

  1. Select target directory
  2. Choose maximum resolution preset
  3. Configure encoding method (CRF or VBR)
  4. Set processing options

Command Line Example

from video_encoder import VideoEncoder
from resolution_handler import ResolutionPreset
from encoding_config import EncodingMethod

# Initialize encoder
encoder = VideoEncoder()

# Configure settings
encoder.set_resolution_preset(ResolutionPreset.FHD)
encoder.set_encoding_method(EncodingMethod.CRF, 23)

# Discover and encode files
video_files = encoder.discover_video_files("/path/to/videos")
results = encoder.encode_batch(video_files)

Architecture

The application is built using a modular architecture:

Core Modules

  • hardware_detector.py: GPU detection and hardware acceleration capability assessment
  • resolution_handler.py: Video resolution management and scaling calculations
  • encoding_config.py: Encoding configuration management (CRF/VBR)
  • progress_display.py: Real-time progress monitoring with Rich UI
  • video_encoder.py: Main encoding engine that orchestrates all components
  • main.py: Interactive application interface

Key Classes

  • HardwareDetector: Detects available GPUs and their encoding capabilities
  • ResolutionHandler: Manages target resolution and scaling operations
  • EncodingConfigManager: Handles encoding method configuration
  • ProgressDisplay: Provides real-time progress feedback
  • VideoEncoder: Main orchestrator for the encoding process

Resolution Presets

Preset Resolution Description
HD 1280×720 HD (720p) - Standard definition
FHD 1920×1080 Full HD (1080p) - High definition
QHD 2560×1440 Quad HD (1440p) - Ultra high definition
UHD 3840×2160 Ultra HD (4K) - Maximum quality

Hardware Acceleration

Supported Encoders

GPU Vendor Encoder Codec Support
NVIDIA NVENC H.264, H.265/HEVC
AMD VCE H.264, H.265/HEVC
Intel QuickSync H.264, H.265/HEVC

Automatic Detection

The application automatically detects your hardware and selects the best available encoder:

  1. NVIDIA NVENC (Priority 1) - Best performance and quality
  2. AMD VCE (Priority 2) - Good performance
  3. Intel QuickSync (Priority 3) - Decent performance
  4. Software (CPU) (Fallback) - Highest quality, slowest speed

Encoding Methods

CRF (Constant Rate Factor) - Quality-Based

  • Range: 0-51 (lower = higher quality)
  • Recommended: 18-28 for most content
  • Use Case: When consistent quality is more important than file size

VBR (Variable Bitrate) - Bitrate-Based

  • Range: 0.1-10.0x multiplier of original bitrate
  • Recommended: 0.5-1.0x for most content
  • Use Case: When specific file sizes or bitrates are required

Performance Tips

  1. Use Hardware Acceleration: Significantly faster encoding times
  2. Choose Appropriate CRF: CRF 23 provides good balance of quality and size
  3. Batch Processing: Process multiple files for efficiency
  4. SSD Storage: Use SSD for input/output files when possible

Troubleshooting

Common Issues

FFmpeg not found:

  • Ensure FFmpeg is installed and in your system PATH
  • Test with: ffmpeg -version

Hardware acceleration not working:

  • Check if your GPU supports hardware encoding
  • Update GPU drivers to the latest version
  • Some older GPUs may not support modern encoders

Out of memory errors:

  • Reduce the number of concurrent encodings
  • Use a lower resolution preset
  • Close other applications to free up memory

Slow encoding speeds:

  • Check if hardware acceleration is enabled
  • Use faster encoding presets (may reduce quality)
  • Ensure adequate cooling for sustained workloads

License

This project is licensed under the MIT License. See the LICENSE file for details.

Acknowledgements

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/AmazingFeature)
  3. Commit your changes (git commit -m 'Add some AmazingFeature')
  4. Push to the branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

Support

If you encounter any issues or have questions, please open an issue on the GitHub repository.