Abstract:
This paper introduces a domain-specific language (DSL) for image processing, that will overcome the limitations of existing tools in batch processing and automation, crucial for data science and machine learning applications. Unlike traditional image manipulation software that requires extensive programming knowledge or fails to efficiently handle multiple files, this DSL simplifies complex operations, enabling seamless batch processing of images. Its intuitive syntax makes it a useful tool for data preprocessing, a vital step in machine learning model development. This DSL stands out by offering a terminal-based interface, which significantly reduces resource consumption, making it accessible on lower-end hardware. This approach not only democratizes advanced image processing tasks but also aligns with the needs of data science professionals, facilitating their workflows without the steep learning curve typically associated with image processing libraries.