Labellerr/Hands-On-Learning-in-Computer-Vision — reverse-engineered prompt

Build me a hands on computer vision learning repository for Labellerr style tutorials. I want it to feel like a friendly notebook hub where someone can browse practical AI vision projects by industry, open the matching Jupyter notebook, and optionally launch it in Google Colab.

Include examples like waste classification, mask detection, electronics instance segmentation, conveyor belt counting, drone based city analysis, cricket pose analysis, and traffic speed or heatmap analysis. Organize the content into clear sections such as healthcare, retail, manufacturing, construction, robotics, sports, security, automotive, life sciences, model notebooks, SDK tutorials, and AI agents.

Each tutorial page or README section should explain what the notebook does in simple language, what kind of input it uses, what the user will learn, and link to any related video or docs if available. Keep it beginner friendly, focused on object detection, segmentation, tracking, OCR, and YOLO fine tuning. If you need current Labellerr or Colab details, look them up online.