cshum/imagor

Fast, secure image processing server and Go library, using libvips

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Summary Information

Updated 57 minutes ago
Added to GitGenius on September 17th, 2026
Created on May 15th, 2021
Open Issues & Pull Requests: 2 (+0)
GitHub issues: Enabled
Number of forks: 175
Total Stargazers: 4,022 (+0)
Total Subscribers: 26 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 3.5 days
Mean response time: 89.6 days
90th percentile: 295.5 days
Tracked items: 65

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Issue Activity (beta)

Open issues: 2
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 63 days
Stale 30+ days: 0
Stale 90+ days: 0

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • Stale (37)
  • enhancement (2)

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Detailed Description

Imagor is a fast, secure image processing server and Go library that uses libvips for image manipulation.

The tool addresses the need for efficient server-side image processing with a focus on security and performance. It leverages libvips, a high-performance image processing library, to handle operations like resizing, cropping, and format conversion. The server architecture allows developers to integrate image processing capabilities into their applications without reimplementing complex image manipulation logic, while the Go library enables direct programmatic access for those building in Go.

Imagor suits projects that require on-demand image transformation at scale, particularly those handling user-uploaded content or needing to serve images in multiple formats and sizes. The tool supports modern image formats including WebP, AVIF, and JPEG XL alongside traditional formats like PNG, GIF, and JPEG. It includes watermarking capabilities for protecting images. Teams building microservices, content delivery systems, or applications with heavy image processing demands would find this approach valuable, as it offloads computation to a dedicated service rather than embedding processing logic in application code.

The project shows consistent maintenance with regular updates addressing both bug fixes and feature additions. Development activity demonstrates responsiveness to issues and pull requests, with the maintainer actively reviewing and merging contributions. The codebase reflects attention to code quality and security considerations appropriate for a tool handling user-supplied image data. Docker support is built in, facilitating deployment in containerized environments.