Computer Vision: Real-Time Instance Segmentation with YOLO

Train and deploy YOLO segmentation models for pixel-level visual understanding, inspection, measurement, and automation tasks.

Categories

Tech Used

Problem

Many computer-vision problems require exact object boundaries rather than simple bounding boxes, especially for measurement, inspection, defect analysis, and scene understanding.

Approach

• Trained and fine-tuned YOLO segmentation models with data augmentation and dataset-quality improvements
• Evaluated model behavior using IoU, precision, recall, and task-relevant visual checks
• Built OpenCV-based inference workflows for images and video
• Prepared ONNX and TensorRT exports for optimized deployment

Results

• Created a reusable segmentation pipeline for pixel-level computer-vision applications
• Established an optimized path from training and evaluation to real-time inference deployment
• Built a foundation applicable to visual inspection, measurement, medical imaging, and industrial automation

Demo Videos