Can YOLOv11 Handle Fiber Segmentation? - Training and Testing YOLOv11 for Fiber Image Segmentation in Python

Learn to train and test YOLOv11 for fiber image segmentation in this comprehensive Python tutorial that demonstrates practical implementation using Ultralytics, OpenCV, and NumPy. Master the complete workflow from data preparation to model inference, covering essential steps including formatting data for YOLO, building and training custom YOLOv11 models on fiber datasets, running inference on new images, and extracting, visualizing, and saving predicted masks. Discover how to compare predicted versus true masks using OpenCV techniques, making this tutorial valuable for defect detection, material analysis, and semantic segmentation applications. The tutorial provides hands-on experience with real-world fiber segmentation use cases, walking through installation procedures, data preparation techniques, model building and training processes, and practical testing methods for validating model performance on individual images.