Automated Fringe Detection and Counting
Location: - Instructor: Junjie TANG Instructions: In this experiment, we utilize computer graphics techniques to automate the analysis of video captured from a Michelson Interferometer. By leveraging Python and OpenCV, the goal is to accurately count the number of fringes in the video. This process involves reading the video, performing background subtraction, detecting contours, and applying morphological operations to isolate and count the light spots efficiently. Requirement: Python3 Manual: Automated Fringe Detection and Counting
Learn the Git
Location: - Instructor: Junjie TANG Instructions: Git is the world's leading version control system, widely adopted in software development for tracking code changes historically and enabling collaborative efforts among multiple contributors. This manual starts with essential background information and fundamental concepts of Git to deepen your understanding. Following this, you will be guided through a series of tasks step by step, covering the basics of Git, branching strategies, and illustrating a comprehensive development process for...
Make Your Own Ethernet Cable
Location: - Instructor: Junjie TANG junjietang@hkust-gz.edu.cn Instructions: Make your own Ethernet cable and take it home for free! Please make an appointment via email, and the instructor will prepare all the necessary materials for you. Equipment: Lab Manual Making_Ethernet_Cables.pdf
Build a Smart Weather Reminder with Raspberry Pi
Location: - Instructor: Junjie TANG Instructions: This project utilizes a Raspberry Pi and various sensors to collect real-time weather data, which is then periodically emailed to individuals who need this information. Requirement: Manual: Build a Smart Weather Reminder with Raspberry Pi.pdf
Develop a Snooker Game
Location: - Instructor: - Instructions: This experiment will guide you step by step in developing a simplified version of a classic 8-ball pool game using JavaScript and HTML5. Throughout the process, you will have the opportunity to learn about web game development and fascinating concepts in physics such as collisions and friction. To ease the initial learning curve, the experiment provides foundational code, allowing you to focus on achieving the objectives outlined in each chapter....
Exploring the Implementation Details of a Key-Value Database
Location: - Instructor: - Instructions: The experiment aims to delve into the design and code implementation of this Key-Value database, exploring how it allows users to query and retrieve values associated with specific keys. Not only will we delve into the intricacies of its initial development, but we will also embark on an exciting journey of modifying and enhancing its functionalities. Equipment: Python 3 Manual: pdf
Generating Text to Image Using Stable Diffusion
Location: - Instructor: Huiyuan LI Instructions: Stable Diffusion is a text-to-image latent diffusion model created by researchers and engineers from CompVis, Stability AI, and LAION. It is trained using images from a subset of the LAION-5B database. The Stable Diffusion web UI is a browser application for Stable Diffusion based on the Gradio library. With this web UI, we can easily generate text-to-image and image-to-image conversions using various models. Equipment: - Lab Manual: Generating Text...
Computer Network - A Simulation Using Cisco Package Tracer
Location: - Instructor: Huiyuan LI Instructions: In this Computer Lab class, we will guide you step by step in understanding the fundamentals of networking using Cisco Packet Tracer. You will have the opportunity to simulate network topologies, configure routers and switches, and visualize abstract networking concepts. The lab will provide foundational knowledge and hands-on experience to help you grasp the complexities of modern computer networks. Equipment: Cisco Package Tracer Lab Manual: Computer Network Lab Manual
Make a Chatbot with Ollama
Location: - Instructor: Huiyuan LI Instructions: This experiment introduces the Ollama framework, a tool for easily deploying and managing large language models. It particularly emphasizes its simplified setup and installation process, as well as how to test the Gemma model through command line and UI, making it suitable for AI beginners to quickly get started. Equipment: • Win10/Win11 Laptop • Ollama 0.3.9 • Google Chrome Browser Lab Manual: make-a-chatbot-with-ollama
Turn on LED by Face Recognition with Raspberry Pi
Location: - Instructor: Huiyuan, LI Instructions: Through this experiment, you will: understand the Python Dlib library and learn how to use it; understand the face_recognition library developed based on Dlib; master the development of face recognition and training models based on Dlib. Equipment: Raspberry Pi AI & Sensor Kit Lab Manual: Turn on LED by Face Recognition with Raspberry Pi
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