Introduction OpenCV is a powerful library for computer vision, but to achieve real-time performance, we need GPU acceleration using CUDA. This guide will walk you through building OpenCV with CUDA support, solving common errors, and ensuring OpenCV uses the GPU. ✅ You Will Learn: How to build OpenCV with CUDA on Linux Common errors and their fixes How to verify GPU acceleration in OpenCV 🔹 Prerequisites Before starting, ensure you have: Ubuntu 22.04 or later NVIDIA GPU (GTX 1050 or higher) CUDA 11.8+ and cuDNN installed CMake 3.16+ 🔹 Step 1: Install Dependencies 1️⃣ Update Your System sudo apt update && sudo apt upgrade -y 2️⃣ Install Required Libraries sudo apt install -y build-essential cmake git unzip pkg-config \ libgtk-3-dev libcanberra-gtk3-module \ libavcodec-dev libavformat-dev libswscale-dev \ libv4l-dev