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Ecosystem

Imagor Studio is part of a larger ecosystem of image processing tools and libraries.

Core Projects​

imagor​

Fast, secure image processing server and Go library

imagor is a fast, secure image processing server and Go library that uses libvips with Go binding vipsgen. libvips is one of the most efficient image processing libraries available, and imagor implements libvips streaming that facilitates parallel processing pipelines, achieving high network throughput.

Key Features​

  • URL-based transformations - All image operations defined in the URL
  • High performance - libvips streaming architecture for efficient processing
  • Comprehensive operations - Resize, crop, filters, format conversion, watermarks, and more
  • Multiple storage backends - HTTP(s), File System, AWS S3, Google Cloud Storage
  • HMAC URL signing - Prevent URL tampering and DDoS attacks
  • thumbor compatibility - Drop-in replacement for thumbor with better performance
  • Docker support - First-class Docker images and deployment
  • Extensive filters - Brightness, contrast, blur, sharpen, saturation, and many more

Use Cases​

  • Image CDN and transformation service
  • On-the-fly thumbnail generation
  • Dynamic image resizing and optimization
  • Format conversion (JPEG, PNG, WebP, AVIF)
  • Watermarking and text overlay
  • Smart cropping with focal point detection

Integration with Imagor Studio​

Imagor Studio uses imagor as its image processing engine:

  • Embedded mode (default) - Built-in imagor server for zero-configuration setup
  • External mode - Connect to standalone imagor service for distributed processing

All image transformations in Imagor Studio are powered by imagor, providing professional-grade image processing capabilities.

vipsgen​

Type-safe, comprehensive Go binding generator for libvips

vipsgen is a Go binding generator for libvips - a fast and efficient image processing library. Existing Go libvips bindings rely on manually written code that is often incomplete, error-prone, and difficult to maintain as libvips evolves. vipsgen solves this by generating type-safe, robust, and fully documented Go bindings using GObject introspection.

Key Features​

  • Comprehensive - Bindings for around 300 libvips operations
  • Type-Safe - Proper Go types for all libvips C enums and structs
  • Idiomatic - Clean Go APIs that feel natural to use
  • Streaming - VipsSource and VipsTarget integration with Go io.Reader and io.Writer for streaming
  • Auto-generated - Uses GObject introspection to stay current with libvips
  • Well-documented - Generated code includes full API documentation

How It Works​

vipsgen uses a multi-layer generation approach:

  1. Introspection Analysis - Analyzes libvips API using GObject introspection
  2. C Layer Generation - Creates C wrapper functions for type-safe parameter handling
  3. Go Binding Layer - Generates Go wrappers handling CGO complexity
  4. Go Method Layer - Provides idiomatic Go methods with options pattern

This approach ensures type safety while maintaining the flexibility of libvips's dynamic parameter system.

Role in Ecosystem​

vipsgen is the foundation that powers imagor:

  • Direct libvips access - Full access to libvips functionality
  • Type-safe operations - Compile-time type checking for image operations
  • Efficient memory management - Proper resource cleanup and lifecycle management
  • Streaming support - Integration with Go's io interfaces for efficient processing
  • Maintainability - Auto-generated bindings stay current with libvips updates

Without vipsgen, imagor wouldn't have the comprehensive, type-safe, and performant libvips integration it has today.

imagorvideo​

imagor video thumbnail server with Go and ffmpeg C bindings

imagorvideo brings video thumbnail capability through ffmpeg, built on the foundations of imagor. It uses ffmpeg C bindings to extract video thumbnails by selecting the best frame from an RMSE (Root Mean Square Error) histogram, then processes it through the imagor pipeline for cropping, resizing, and filters.

Key Features​

  • Smart frame selection - Automatically selects the best frame using RMSE histogram analysis
  • Skips black frames - Avoids common black frames at video start
  • FFmpeg integration - Direct ffmpeg C bindings for efficient processing
  • imagor pipeline - Full access to imagor's image processing capabilities
  • Flexible positioning - Specify exact frame, time duration, or percentage position
  • Metadata extraction - Get video info (duration, dimensions, FPS) without processing
  • Storage integration - Works with HTTP, File System, S3, Google Cloud Storage
  • Seek simulation - Handles non-seekable sources (HTTP, S3) using memory/temp buffers

Video-Specific Filters​

  • frame(n) - Specify exact position or time for thumbnail extraction
    • Float (0.0-1.0): Position percentage, e.g., frame(0.5) for middle
    • Time duration: Elapsed time, e.g., frame(5m1s), frame(200s)
  • seek(n) - Seek to approximate position, then auto-select best frame
    • Float (0.0-1.0): Position percentage
    • Time duration: Elapsed time
  • max_frames(n) - Limit frames for selection (faster processing)

How It Works​

  1. Stream frames - Extracts limited number of frames from video
  2. Calculate histogram - Analyzes each frame using RMSE
  3. Select best frame - Chooses frame with best quality (skips black frames)
  4. Convert to RGB - Converts selected frame to image data
  5. imagor processing - Applies all imagor operations (resize, crop, filters)

Integration with Imagor Studio​

Imagor Studio integrates imagorvideo for seamless video support:

  • Video files in gallery - MP4, WebM, AVI, MOV, MKV appear alongside images
  • Automatic thumbnails - Best frame automatically selected and processed
  • Play icon overlays - Visual distinction for video files
  • Configurable extensions - Customize which video formats to support
  • Same editing capabilities - Apply all imagor filters and transformations to video thumbnails

Technology Stack​

Backend Technologies​

libvips​

  • Website: libvips.github.io/libvips
  • Purpose: Image processing library
  • Features:
    • Streaming processing
    • Memory efficient
    • Multi-threaded
    • Wide format support

FFmpeg​

  • Website: ffmpeg.org
  • Purpose: Video processing
  • Features:
    • Video decoding
    • Thumbnail extraction
    • Format conversion
    • Frame extraction

Go​

  • Website: go.dev
  • Purpose: Backend language
  • Benefits:
    • High performance
    • Concurrent processing
    • Static typing
    • Easy deployment

Frontend Technologies​

React​

  • Website: react.dev
  • Purpose: UI framework
  • Features:
    • Component-based
    • Virtual DOM
    • Rich ecosystem

Vite​

  • Website: vitejs.dev
  • Purpose: Build tool
  • Features:
    • Fast development
    • Hot module replacement
    • Optimized builds

TanStack Router​

  • Website: tanstack.com/router
  • Purpose: Type-safe routing
  • Features:
    • Type safety
    • Data loaders
    • Code splitting

Tailwind CSS​

  • Website: tailwindcss.com
  • Purpose: Utility-first CSS
  • Features:
    • Rapid development
    • Consistent design
    • Small bundle size

Image Processing​

  • Sharp (Node.js) - High-performance image processing
  • Thumbor (Python) - Image processing service
  • Pillow (Python) - Image processing library

Storage Solutions​

  • MinIO - S3-compatible object storage
  • Cloudflare R2 - Object storage
  • AWS S3 - Cloud object storage
  • DigitalOcean Spaces - Object storage

Deployment Platforms​

  • Docker - Containerization
  • Kubernetes - Container orchestration
  • Cloudflare Pages - Static site hosting
  • Vercel - Web hosting
  • Netlify - Web hosting

Community​

Getting Help​

Contributing​

Contributions are welcome to all projects in the ecosystem:

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Submit a pull request

License​

All projects in the ecosystem are open source:

  • Imagor Studio: Apache License 2.0
  • imagor: Apache License 2.0
  • vipsgen: Apache License 2.0
  • imagorvideo: Apache License 2.0

Resources​

Documentation​

Docker Images​

Source Code​

Next Steps​