AutoVisual Fusion Suite: A Comprehensive Evaluation of Image Segmentation and Voice Conversion Tools on HuggingFace Platform
This work provides a practical guide for users seeking to deploy AI tools on Linux, but it is incremental as it focuses on evaluation and integration of existing models without novel contributions.
The study evaluated image segmentation and voice conversion tools on HuggingFace, identifying top tools and implementing them on Linux systems, resulting in the successful integration of video segmentation and voice conversion into the AutoVisual Fusion Suite project.
This study presents a comprehensive evaluation of tools available on the HuggingFace platform for two pivotal applications in artificial intelligence: image segmentation and voice conversion. The primary objective was to identify the top three tools within each category and subsequently install and configure these tools on Linux systems. We leveraged the power of pre-trained segmentation models such as SAM and DETR Model with ResNet-50 backbone for image segmentation, and the so-vits-svc-fork model for voice conversion. This paper delves into the methodologies and challenges encountered during the implementation process, and showcases the successful combination of video segmentation and voice conversion in a unified project named AutoVisual Fusion Suite.