Help & FAQ
Everything you need to know about our WebP conversion system
WebP is a modern image format developed by Google that provides superior compression for images on the web. It supports both lossy and lossless compression, alpha transparency, and even animations. WebP images are typically 25-35% smaller than JPEGs and PNGs, which leads to faster page loads and reduced bandwidth usage.
Our system uses Docker containers to ensure secure and isolated processing of images. The conversion process is handled by Python scripts that utilize libraries like Pillow and OpenCV for high-quality image processing. This server-side approach ensures consistent results across all devices and browsers.
Our system primarily uses Python for image processing tasks. The web interface is built with PHP and JavaScript, utilizing modern frameworks and libraries to provide a seamless user experience.
Docker is a platform that allows developers to package applications into containers—standardized executable components combining application source code with the operating system libraries and dependencies required to run that code in any environment.
In our system, Docker is used to create isolated environments for image processing tasks. Each conversion task runs in its own container, ensuring that processes are separated and secure. This isolation helps prevent conflicts between different tasks and enhances the security of our system by limiting the potential impact of any vulnerabilities.
By using Docker, we can also ensure that our application behaves the same way, regardless of where it is deployed. This consistency is crucial for maintaining high-quality service and reliability across different environments.
Docker containers provide an isolated environment for processing, which enhances security by limiting the potential impact of any vulnerabilities. Each conversion task runs in its own container, ensuring that processes are separated and secure.
Server-side processing allows us to handle large files and complex operations without burdening the user's device. It ensures consistent performance and quality, regardless of the user's hardware or browser capabilities.
We use advanced algorithms and libraries like Pillow and OpenCV to process images. These tools allow us to maintain high visual quality while optimizing file size and performance.
Our system supports a variety of image formats, including WebP, JPEG, PNG, and SVG. We use specialized conversion functions to ensure optimal results for each format, leveraging tools like rsvg-convert for SVGs and pngquant for PNG optimization.
We prioritize user privacy by automatically deleting files after processing. Our Docker-based infrastructure ensures that each task is isolated, minimizing the risk of data leaks or unauthorized access.
Our server-side processing is optimized to handle large files efficiently. We use Docker containers to allocate resources dynamically, ensuring that even large images are processed quickly without affecting system performance.
We plan to expand our system's capabilities by integrating more advanced image processing features and supporting additional formats. We are also exploring the use of AI to enhance image quality and optimize conversion processes further.