My first project using real-time computer vision 👀 I have worked on a few projects before, but this is my first time building something that interacts with a live camera feed and seeing it actually work felt crazy. I built an AI gesture-controlled virtual keyboard using Python, OpenCV, and MediaPipe. It allows you to type and control your system using just hand gestures no physical keyboard or mouse. Some features: • Real-time hand tracking • Gesture-based typing • Backspace and Caps Lock support • Mouse control using hand movement • Clean UI with visual feedback • Smooth interaction with gesture detection This project helped me understand how computer vision and pre-trained models can be used to build interactive, real-time systems. Still improving it and adding more features, but this is a big step for me. Would love to hear your thoughts and feedback 🙌 GitHub: https://lnkd.in/gwiXNpPC #Python #ComputerVision #OpenCV #MediaPipe #AI #Project #GitHub #Learning

🚀 Day 9/30 – Real-Time Image Filters using OpenCV 🐍📷✨ Day 9 of my 30 Days Python Challenge, and today I built a real-time image filter project using OpenCV 🎉 I experimented with different live filters, including: ✨ Original ✨ Grayscale ✨ Edge Detection ✨ Sepia ✨ Blur This hands-on project helped me understand how real-time frame processing and filter pipelines work behind the scenes in computer vision applications 💻 What I focused on today: ✨ Applying multiple filters in real time ✨ Live webcam frame processing with OpenCV ✨ Strengthening image processing fundamentals ✨ Exploring creative computer vision workflows This OpenCV streak is helping me move from basic transformations to visually engaging real-world projects 🚀 👉 Would love your feedback! 👉 Which filter should I add next? 😄 Day 10 coming tomorrow… stay tuned 👀 #Python #OpenCV #ComputerVision #ImageProcessing #30DaysChallenge #PythonProjects #AI #MachineLearning

Built a gesture-controlled drag & drop system using OpenCV + MediaPipe — no mouse, just hand tracking. 👉 Real-time hand landmark detection 👉 Pinch gesture → drag objects 👉 Three-finger gesture → create new elements This is a simple implementation, but it shows how human gestures can directly control digital systems. I’m sharing the source code below — feel free to explore and build on it. Let’s keep building something interesting every day.Projenius _ 💡 #AI #ComputerVision #MachineLearning #OpenCV #MediaPipe #Python #Developer #Innovation #Tech #LearningInPublic #BuildInPublic

Excited to share my latest Computer Vision project: AI Air Canvas – Real-Time Writing Using Computer Vision In this project, I built an interactive system that allows users to write and draw in the air using hand gestures captured through a webcam. Using OpenCV, MediaPipe, and NumPy, the application tracks finger movements in real time to create a touchless digital drawing experience. 🔹 Key Features: • Real-time hand gesture detection • Air drawing without mouse or keyboard • Color selection and clear canvas functionality • Computer Vision-based interactive interface This project helped me strengthen my skills in Computer Vision, Python, and AI-based real-time applications, and explore how vision-based systems can enable intuitive human-computer interaction. 🔗 GitHub Repository: https://lnkd.in/dsrwpZDr #AI #ComputerVision #Python #OpenCV #MachineLearning #DeepLearning #GitHub #PortfolioProject #LearningJourney

Built a gesture-controlled drag & drop system using OpenCV + MediaPipe no mouse, just hand tracking. 👉🏼Real-time hand landmark detection 👉🏼Pinch gesture → move objects 👉🏼Three-finger gesture → create new elements A simple yet effective implementation that shows how hand gestures can control digital systems. Source code shared in the comments below. Let's keep building cool stuff every day... #AI #ComputerVision #Machine Learning #OpenCV #MediaPipe #Python #Developer #Innovation #Tech #LearningInPublic #BuildinPublic

After spending around 2 weeks working on a real-world Computer Vision project, I’m happy to share my Drowsiness Detection System using Python and OpenCV 🚀 This project focuses on detecting driver fatigue in real-time using a webcam. It identifies the face and eyes using Haar Cascade classifiers, and continuously monitors eye activity. If the eyes remain closed for a certain duration, the system triggers an alert sound notification to indicate possible drowsiness. During this project, I worked on: Real-time video capture and processing using OpenCV Face and eye detection using Haar Cascade classifiers Frame-based logic to track eye closure duration Implementing an alert system using sound notification Handling file paths and runtime stability issues This project really helped me understand how computer vision works in real-time environments and how small logical improvements can make a system more reliable and effective. It also strengthened my understanding of: Python programming OpenCV fundamentals Real-time system design Debugging and problem-solving skills Looking forward to building more such real-world projects and improving my skills in Computer Vision and AI development 🚀 GitHub Repo:- https://lnkd.in/gD8ystW9 #Python #OpenCV #ComputerVision #AI #MachineLearning #Project #CodingJourney #LearningByBuilding #Consistency #Programming

🚀 Air Sketch: Drawing with Hand Gestures I’m excited to share a project I recently built that allows users to sketch in the air using simple hand gestures. Using computer vision techniques, the system tracks hand movements in real time and enables: 🤏 Pinch gesture to draw ✊ Fist gesture to clear the screen Smooth and intuitive interaction without any physical tools This project helped me strengthen my understanding of gesture recognition, real-time tracking, and building interactive systems. Tech Stack: Python, OpenCV, MediaPipe Always open to feedback and suggestions for improvement! #ComputerVision #Python #OpenCV #AI #MachineLearning #Projects #Innovation Github-https://lnkd.in/ggWmHZYu

🚀 Built an Air Writing System using Computer Vision I created a real-time system that lets you write in the air using just your hand — no keyboard, no mouse, just gestures ✋ Using hand tracking, the system detects finger movements and converts them into drawing on a virtual canvas through a webcam. ✨ Key Features: ☝️ Index finger → Draw ✌️ Index + Middle → Move cursor 🤟 Three fingers → Change color 🎨 🖐️ Four fingers → Eraser 🧽 ✊ Fist (hold) → Clear screen 🧠 Tech Stack: Python, OpenCV, MediaPipe, NumPy 💡 What I explored: Real-time hand landmark detection Gesture-based interaction systems Frame processing & smoothing Building touchless UI using computer vision This project gave me a deeper understanding of how AI can enable natural human-computer interaction. #ComputerVision #OpenCV #Python #AI #MachineLearning #MediaPipe #Projects #Coding

🚀 Built a Virtual Mouse using Python and Computer Vision After working on multiple AI projects, I wanted to build something that interacts directly with real-world hardware. So I created a Virtual Mouse that can control the system cursor using just hand gestures. 🎯 What it does: Move cursor using hand movement Left click using finger gesture Right click using gesture Scroll using hand movement Works in real time using webcam 🧠 Technologies used: Python OpenCV MediaPipe PyAutoGUI Computer Vision ⚙️ How it works (simple idea): The webcam captures hand movements, MediaPipe detects hand landmarks, OpenCV processes the frames, and PyAutoGUI converts gestures into mouse actions. Basically, your hand becomes the mouse. 💡 What I learned: Real-time computer vision processing Hand landmark detection Frame processing and optimization System automation using Python Integrating AI with hardware interaction This project helped me understand how AI can interact with real-world systems and not just data. Here is the demo video 👇 #Python #ComputerVision #AI #MachineLearning #OpenCV #MediaPipe #StudentDeveloper #TechProjects

Built a real-time computer vision system to automatically detect and capture high-quality moments of my dog using OpenCV and YOLOv8. What looked simple at first turned into a problem of instability, fast motion caused inconsistent detections, motion blur reduced accuracy, and lighting variations affected frame reliability. To handle this, I focused on: ● Improving detection consistency across frames ● Adding rule-based filtering to avoid false triggers ● Designing a centering mechanism to capture usable shots instead of random frames Instead of just detecting objects, the goal was to decide when a frame is worth capturing, which made this more of a decision problem than a detection task. Result: a system that behaves like a smart camera, capturing stable, well-centered moments in real time. Tech used: YOLOv8 for detection, combined with custom logic for temporal stability and frame selection. GitHub Repository: https://lnkd.in/ggTvDub4 #OpenCV #YOLO #Python #ComputerVision #AI #FunProject