Music2P: A Multi-Modal AI-Driven Tool for Simplifying Album Cover Design

August 03, 2024 · Entered Twilight · 🏛 International Conference on Information and Knowledge Management

Repo contents: .DS_Store, ColabToFlask.ipynb, QRCode_generator (1).ipynb, README.md, app.py, base.png, custom_data, demo.png, demo, flask_seg_demo.ipynb, id2label.json, requirements__.txt, seg_demo, static, templates

Authors Joong Ho Choi, Geonyeong Choi, Ji-Eun Han, Wonjin Yang, Zhi-Qi Cheng arXiv ID 2408.01651 Category cs.MM: Multimedia Cross-listed cs.AI, cs.HC Citations 0 Venue International Conference on Information and Knowledge Management Repository https://github.com/JC-78/Music2P ⭐ 5 Last Checked 1 month ago

Abstract

In today's music industry, album cover design is as crucial as the music itself, reflecting the artist's vision and brand. However, many AI-driven album cover services require subscriptions or technical expertise, limiting accessibility. To address these challenges, we developed Music2P, an open-source, multi-modal AI-driven tool that streamlines album cover creation, making it efficient, accessible, and cost-effective through Ngrok. Music2P automates the design process using techniques such as Bootstrapping Language Image Pre-training (BLIP), music-to-text conversion (LP-music-caps), image segmentation (LoRA), and album cover and QR code generation (ControlNet). This paper demonstrates the Music2P interface, details our application of these technologies, and outlines future improvements. Our ultimate goal is to provide a tool that empowers musicians and producers, especially those with limited resources or expertise, to create compelling album covers.