ghoststream 1.0.0

Open Source Cross-Platform Transcoding Service & SDK

GhostStream

Open-Source Video Transcoding Server

GhostStream is a hardware-accelerated video transcoding server with automatic GPU detection, adaptive bitrate streaming, and minimal configuration. It serves as the transcoding backend for GhostHub but can be used standalone.

Quick Start

Pre-built Binaries

Platform	Download	Run
Windows	GhostStream.exe	Double-click
Linux	GhostStream-Linux	chmod +x && ./GhostStream-Linux
macOS	GhostStream-macOS	chmod +x && ./GhostStream-macOS

Requires FFmpeg. The application will provide installation instructions if FFmpeg is not found.

From Source

git clone https://github.com/BleedingXiko/GhostStream.git
cd GhostStream
python run.py

The launcher creates a virtual environment, installs dependencies, and starts the server.

Docker

# CPU-only
docker run -d -p 8765:8765 ghcr.io/bleedingxiko/ghoststream

# NVIDIA GPU
docker run -d -p 8765:8765 --gpus all ghcr.io/bleedingxiko/ghoststream:nvidia

SDK Installation

pip install ghoststream              # SDK only (lightweight)
pip install ghoststream[server]      # Full server with all dependencies

Usage

Python SDK (recommended):

from ghoststream import GhostStreamClient, TranscodeStatus

client = GhostStreamClient(manual_server="localhost:8765")

# Synchronous (Flask/gevent compatible)
job = client.transcode_sync(source="https://example.com/video.mp4", resolution="720p")
print(f"Stream URL: {job.stream_url}")

# Or async
async with GhostStreamClient(manual_server="localhost:8765") as client:
    job = await client.transcode(source="https://example.com/video.mp4")
    print(f"Stream URL: {job.stream_url}")

curl:

curl -X POST http://localhost:8765/api/transcode/start \
  -H "Content-Type: application/json" \
  -d '{"source": "https://example.com/video.mp4", "mode": "stream"}'

See the examples/ directory for additional usage examples.

Features

• HLS Streaming - Real-time transcoding with immediate playback
• Adaptive Bitrate (ABR) - Multiple quality variants for bandwidth adaptation
• HDR to SDR - Automatic tone mapping for HDR content
• Codec Support - H.264, H.265/HEVC, VP9, AV1
• Batch Processing - Queue multiple files with optional two-pass encoding
• Hardware Acceleration - NVIDIA NVENC, Intel QuickSync, AMD AMF, Apple VideoToolbox
• Automatic Fallback - Falls back to software encoding if hardware fails
• Thermal Management - Reduces load when GPU temperature is high

Supported Hardware Encoders

Platform	Encoder	Detection
NVIDIA	NVENC	Automatic via nvidia-smi
Intel	QuickSync	Automatic via VA-API
AMD	AMF/VCE	Automatic
Apple	VideoToolbox	Native macOS support
CPU	libx264/libx265	Always available

API Reference

Endpoints

Method	Endpoint	Description
POST	/api/transcode/start	Start a transcoding job
GET	/api/transcode/{id}/status	Get job status & progress
POST	/api/transcode/{id}/cancel	Cancel a job
DELETE	/api/transcode/{id}	Delete job & cleanup
GET	/api/health	Health check
GET	/api/capabilities	Hardware & codec info
WS	/ws/progress	Real-time progress via WebSocket

Start Transcode Request

{
  "source": "https://example.com/video.mp4",
  "mode": "stream",           // "stream", "abr", or "batch"
  "output": {
    "resolution": "720p",     // "4k", "1080p", "720p", "480p", "original"
    "video_codec": "h264",    // "h264", "h265", "vp9", "av1"
    "audio_codec": "aac",     // "aac", "opus", "copy"
    "hw_accel": "auto"        // "auto", "nvenc", "qsv", "software"
  },
  "start_time": 0             // Seek to position (seconds)
}

Response

{
  "job_id": "abc-123",
  "status": "processing",
  "stream_url": "http://localhost:8765/stream/abc-123/master.m3u8",
  "progress": 0
}

Examples

File	Description
demo.py	Basic demo with auto-play
demo.html	Browser-based demo
minimal.py	Minimal Python example
quickstart.py	Interactive examples
curl_examples.md	HTTP/curl commands
web_player.html	Full-featured web player

Configuration

Create ghoststream.yaml to customize (optional):

server:
  host: 0.0.0.0
  port: 8765

transcoding:
  max_concurrent_jobs: 2
  segment_duration: 4
  tone_map_hdr: true
  retry_count: 3

hardware:
  prefer_hw_accel: true
  fallback_to_software: true

GhostHub Integration

GhostStream serves as the transcoding backend for GhostHub.

Architecture

┌─────────────────────────────────┐      ┌─────────────────────────────────┐
│        Raspberry Pi             │      │         Your PC                 │
│  ┌───────────────────────────┐  │      │  ┌───────────────────────────┐  │
│  │       GhostHub            │  │ WiFi │  │      GhostStream          │  │
│  │    (Media Server)         │◄─┼──────┼─►│   (GPU Transcoder)        │  │
│  └───────────────────────────┘  │      │  └───────────────────────────┘  │
└─────────────────────────────────┘      └─────────────────────────────────┘

• Auto-Discovery: GhostStream advertises via mDNS (_ghoststream._tcp.local)
• On-Demand: Transcoding occurs only when requested
• Local Network: No internet connection required

Python SDK

pip install ghoststream

from ghoststream import GhostStreamClient, TranscodeStatus

# Auto-discover on network
client = GhostStreamClient()
client.start_discovery()

# Or connect directly
client = GhostStreamClient(manual_server="192.168.1.100:8765")

# Synchronous API (Flask/gevent compatible)
job = client.transcode_sync(
    source="http://pi:5000/media/video.mkv",
    resolution="1080p"
)
if job.status != TranscodeStatus.ERROR:
    print(job.stream_url)

# Async API
job = await client.transcode(source="http://pi:5000/media/video.mkv")

WebSocket Progress

# Subscribe to job updates
ws.send({"type": "subscribe", "job_ids": ["job-123"]})

# Receive real-time progress
{"type": "progress", "job_id": "job-123", "data": {"progress": 45.2}}
{"type": "status_change", "job_id": "job-123", "data": {"status": "ready"}}

Contributing

Contributions are welcome. See CONTRIBUTING.md for guidelines.

# Development setup
git clone https://github.com/BleedingXiko/GhostStream.git
cd GhostStream
python -m venv venv && source venv/bin/activate  # or venv\Scripts\activate on Windows
pip install -r requirements.txt
python -m ghoststream --log-level DEBUG

License

MIT License - see LICENSE for details.