Credits¶
ImgCompress is built upon a foundation of industry-leading open-source technologies. This page serves as a tribute to the tools and communities that enable high-performance, private image optimization.
Core Processing Engine¶
| Component | Technology | Role |
|---|---|---|
| Local AI | rembg | Powered by the U2-Net model for offline background removal. |
| Execution | onnxruntime | High-performance inference engine for local AI model execution. |
| Image Logic | Pillow | Standard Python library for image manipulation. |
Infrastructure & Hosting¶
| Component | Technology | Role |
|---|---|---|
| Containerization | Docker | Ensures "works everywhere" portability and strict process isolation. |
| Distribution | Docker Hub | Reliable hosting for the official imgcompress container images. |
| Documentation | GitHub Pages | Static site hosting for this documentation portal. |
| Networking | AWS Route 53 | Highly available and scalable Cloud DNS for the project domain. |
| Site Generator | Zensical | Modern static site generator utilized for building and maintaining the project documentation of imgcompress. |
Privacy & Security¶
Privacy Commitment
By utilizing these local-first libraries, ImgCompress guarantees that no images, metadata, or behavioral data ever leave your local network.
Assets & Media¶
Image Credits
Landscape with sunset in Yixing (Freepik) is used as a demonstration asset for AI background removal examples.