Image Segmentation with Hugging Face Models

Computer vision is transforming how machines understand the visual world, going beyond simple image classification to analyze scenes pixel by pixel. This text-based course guides you through the foundational concepts and practical implementation of image segmentation using Hugging Face models, enabling you to build precise visual analysis systems. What you will learn: - Understand the core differences between semantic, instance, and panoptic segmentation. - Load and configure pre-trained segmentation models using the Hugging Face transformers library. - Process image data and prepare pixel-level labels for training and inference. - Implement modern segmentation architectures, including Segment Anything and SegFormer. - Evaluate model performance using standard computer vision metrics like Intersection over Union. - Deploy segmentation pipelines for real-world scene analysis. We begin with essential terminology and image processing concepts before exploring code-based pipelines and model evaluation. This course is designed for beginners in computer vision, with no prior deep learning experience required. Start reading today to unlock pixel-level insights from your visual data.