Opencv cuda c

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Build and Install OpenCV With CUDA GPU Support on Windows 10 | OpenCV 4.5.1 | 2021

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Build OpenCV 4.5.1 with CUDA GPU acceleration on Windows 10. In this tutorial, we will build OpenCV from source with CUDA support in Anaconda base environment as well as in a virtual environment. Building OpenCV with CUDA from source allows OpenCV to be used in any programming language. We will focus on Python 3.8 for this tutorial. - ► Time Stamps: Introduction: (0:00) Prerequisites: (0:55) Install CUDA and cuDNN: (1:23) Make OpenCV using CMake: (2:42) Install OpenCV on Windows 10: (6:49) Install OpenCV in Virtual Environment: (8:00) How to check if OpenCV is using GPU: (9:25) - ► Links: 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 - ► Commands: "C:\Program Files\CMake\bin\cmake.exe" build "C:\OpenCV_Build\build" target INSTALL config Release - Want to discuss more? ►Join my discord: 🤍 #TheCodingBug #cuda #opencv - ► My Other Tutorials: ○ Instance Segmentation as Rendering: 🤍 ○ Detectron2 Complete Tutorial: 🤍 ○ YOLOv4 On Android Using TFLite: 🤍 ○ Custom YOLOv4 Object Detection with TensorFlow and TFLite : 🤍 ○ Install TensorFlow GPU Under 90 Seconds: 🤍 ○ Install PyTorch GPU Under 90 Seconds: 🤍 ○ Darknet YOLOv4 Custom Object Detection: Part 2 (Training YOLOv4 Darknet): 🤍 ○ Darknet YOLOv4 Custom Object Detection: Part 1 (Preparing Custom Dataset): 🤍 ○ YOLOv4 Object Detection with TensorFlow, TFLite and TensorRT: 🤍 ○ Darknet YOLOv4 Object Detection for Windows 10 on Images, Videos, and Webcams: 🤍 ○ Real-Time Object Detection on Webcam and Videos Using OpenCV With YOLOv3 and YOLOv4 | Windows Linux: 🤍 ○ Build and Install OpenCV 4.4.0 With CUDA (GPU) Support on Windows 10: 🤍 ○ Install TensorFlow GPU and PyTorch with CUDA on Windows 10 Anaconda | CUDA 10.1 cuDNN 7.6: 🤍 ○ Real-time Multiple Object Tracking with YOLOv4 TensorFlow and Deep Sort | Linux, Windows: 🤍 - ► Follow us on Twitter: 🤍 ► Support us on Patreon: 🤍 - DISCLAIMER: Links included in this description might be affiliate links. If you purchase a product or service with the links that I provide I may receive a small commission. There is no additional charge to you!

Introduction to OpenCV Cuda GPU in C++

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In this Computer Vision and OpenCV Cuda GPU Tutorial, we will have a short introduction to the OpenCV Cuda Module that can be used for GPU accelerated computer vision. We will see a comparison of a CPU and GPU. We are going to go through the topics we are going to cover throughout this tutorial and look at the official OpenCV Cuda Module Documentation. In the next video, we will take a look at the core part of the module and the basic matrix operations we can do with our Cuda GPU. ⭐Enroll in YOLOv7 Course: 🤍 ⭐Enroll in OpenCV GPU Course: 🤍 ⭐Enroll in SegFormer Course: 🤍 💎GitHub: 🤍 💎LinkedIn: 🤍 💎Twitter: 🤍 💵 Patreon: 🤍 💵Channel Member for help with projects, private discord, and exclusive perks: 🤍 Time Stamps: 0:00 - Introduction 1:01 - CPU vs GPU 3:42 - OpenCV Cuda Documentation I'll be doing other tutorials alongside this one, where we are going to use C for Algorithms and Data Structures, and Artificial Intelligence. The purpose of this tutorial and channel is to build an online coding library where different programming languages and computer science topics are stored in the YouTube cloud in one place. Feel free to comment if you have any questions about the things I'm going over in the video or just in general, and remember to subscribe to the channel to help me grow and make more videos in the future. :) Tags for the video: #OpenCVcuda #OpenCV #Cuda #NVIDIA #ComputerVision

Image Filters with OpenCV Cuda on GPU in C++

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12.08.2021

In this Computer Vision and OpenCV Cuda GPU Tutorial, we will take a look at the image filters for OpenCV Cuda. We will see the different types of filters that are implemented and how to create and use them in OpenCV C. Code examples will be shown throughout the video with the different image filters. ⭐Enroll in YOLOv7 Course: 🤍 ⭐Enroll in OpenCV GPU Course: 🤍 ⭐Enroll in SegFormer Course: 🤍 💎GitHub: 🤍 💎LinkedIn: 🤍 💎Twitter: 🤍 💵 Patreon: 🤍 💵Channel Member for help with projects, private discord, and exclusive perks: 🤍 Time Stamps: 0:00 - Introduction 0:50 - OpenCV Cuda Documentation 6:45 - Image Filters OpenCV Cuda I'll be doing other tutorials alongside this one, where we are going to use C for Algorithms and Data Structures, and Artificial Intelligence. The purpose of this tutorial and channel is to build an online coding library where different programming languages and computer science topics are stored in the YouTube cloud in one place. Feel free to comment if you have any questions about the things I'm going over in the video or just in general, and remember to subscribe to the channel to help me grow and make more videos in the future. :) Tags for the video: #OpenCVcuda #OpenCV #Cuda #NVIDIA #ComputerVision

Build and Install OpenCV Python with Cuda GPU in UNDER 10 MINUTES

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In this Computer Vision Tutorial, we are going to Install and Build OpenCV with GPU for Python. We are going to use NVIDIA Cuda to run our OpenCV programs on an NVIDIA GPU. We will go over the installation process for all the required programs and files. We will then use CMake to do the configuration of the OpenCV source files and then build them with GPU support later on. At the end of the video, I'll show how we can include the OpenCV library with GPU support in Visual Studio Code and see how we can verify that everything is set up correctly. - ⭐Enroll in YOLOv7 Course: 🤍 ⭐Enroll in OpenCV GPU Course: 🤍 ⭐Enroll in SegFormer Course: 🤍 💎GitHub: 🤍 💎LinkedIn: 🤍 💎Twitter: 🤍 💵 Patreon: 🤍 💵Channel Member for help with projects, private discord, and exclusive perks: 🤍 Video for Installation and C: 🤍 OpenCV Source Code: 🤍 OpenCV Contrib: 🤍 Visual Studio 2019: 🤍 Anaconda 3: 🤍 CMake: 🤍 NVIDIA Cuda: 🤍 NVIDIA cuDNN: 🤍 cuDNN Installation Guide: 🤍 Cuda Wikipedia: 🤍 Command to Install: cmake build "C:\your_path\build" target INSTALL config Release - Join this channel to get access to exclusive perks: 🤍 Join the public Discord chat here: 🤍 I'll be doing other tutorials alongside this one, where we are going to use C for Computer Vision and Artificial Intelligence. The purpose of this tutorial and channel is to build an online coding library where different programming languages and computer science topics are stored in the YouTube cloud in one place. Feel free to comment if you have any questions about the things I'm going over in the video or just in general, and remember to subscribe to the channel to help me grow and make more videos in the future. :) Tags for the video: #OpenCV #opencvGPU #NVIDIA #Cuda #ComputerVision #OpenCVpython #Python

Core and Matrix Operations with OpenCV Cuda on GPU in C++

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In this Computer Vision and OpenCV Cuda GPU Tutorial, we will take a look at the core part of the module. We will see how to use upload an image to the GPU, do operations on it and then download it again and display it. We will also take a look at some of the matrix operations we can do on the GPU with OpenCV. Code examples will be shown throughout the video. ⭐Enroll in YOLOv7 Course: 🤍 ⭐Enroll in OpenCV GPU Course: 🤍 ⭐Enroll in SegFormer Course: 🤍 💎GitHub: 🤍 💎LinkedIn: 🤍 💎Twitter: 🤍 💵 Patreon: 🤍 💵Channel Member for help with projects, private discord, and exclusive perks: 🤍 Time Stamps: 0:00 - Introduction 0:57 - CPU vs GPU 1:33 - OpenCV Cuda Documentation 7:00 - OpenCV Cuda Core Code 13:40 - Matrix Operations with OpenCV GPU I'll be doing other tutorials alongside this one, where we are going to use C for Algorithms and Data Structures, and Artificial Intelligence. The purpose of this tutorial and channel is to build an online coding library where different programming languages and computer science topics are stored in the YouTube cloud in one place. Feel free to comment if you have any questions about the things I'm going over in the video or just in general, and remember to subscribe to the channel to help me grow and make more videos in the future. :) Tags for the video: #OpenCVcuda #OpenCV #Cuda #NVIDIA #ComputerVision

GPU vs CPU in OpenCV and Computer Vision | OpenCV Cuda C++ | GPU IS UP TO 40X FASTER

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In this Computer Vision Tutorial, we are going to do a comparison of the GPU and CPU in OpenCV and Computer Vision. We are going to see how fast and efficient it is to run computer vision applications on a GPU compared to a CPU. We will also see how to use the OpenCV Cuda module to do image processing and operations on the GPU. In this example here it's up to 40 times faster on a standard GPU. ⭐Enroll in YOLOv7 Course: 🤍 ⭐Enroll in OpenCV GPU Course: 🤍 ⭐Enroll in SegFormer Course: 🤍 💎GitHub: 🤍 💎LinkedIn: 🤍 💎Twitter: 🤍 💵 Patreon: 🤍 💵Channel Member for help with projects, private discord, and exclusive perks: 🤍 Time Stamps: 0:00 - OpenCV Cuda Documentation 3:35 - GPU vs CPU OpenCV I'll be doing other tutorials alongside this one, where we are going to learn about Deep Learning, Artificial Intelligence, and Computer Vision. The purpose of this tutorial and channel is to build an online coding library where different programming languages and computer science topics are stored in the YouTube cloud in one place. Feel free to comment if you have any questions about the things I'm going over in the video or just in general, and remember to subscribe to the channel to help me grow and make more videos in the future. :) Tags for the video: #OpenCVcuda #OpenCV #Cudan #ComputerVision #OpenCVgpu #GPUvsCPU

Hough Transforms with OpenCV Cuda on GPU in C++

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In this Computer Vision and OpenCV Cuda GPU Tutorial, we will take a look at the Hough Transformations in OpenCV Cuda. We will see the different types of hough transformations that are implemented and how to create and use them in OpenCV C. Code examples will be shown throughout the video with the hough circle transform to detect circles in the images from the webcam. ⭐Enroll in YOLOv7 Course: 🤍 ⭐Enroll in OpenCV GPU Course: 🤍 ⭐Enroll in SegFormer Course: 🤍 💎GitHub: 🤍 💎LinkedIn: 🤍 💎Twitter: 🤍 💵 Patreon: 🤍 💵Channel Member for help with projects, private discord, and exclusive perks: 🤍 Time Stamps: 0:00 - Introduction 0:33 - OpenCV Cuda Documentation 2:58 - Hough Circle OpenCV Cuda I'll be doing other tutorials alongside this one, where we are going to use C for Algorithms and Data Structures, and Artificial Intelligence. The purpose of this tutorial and channel is to build an online coding library where different programming languages and computer science topics are stored in the YouTube cloud in one place. Feel free to comment if you have any questions about the things I'm going over in the video or just in general, and remember to subscribe to the channel to help me grow and make more videos in the future. :) Tags for the video: #OpenCVcuda #OpenCV #Cuda #NVIDIA #ComputerVision

Face Detection Using OpenCV with CUDA GPU Acceleration | Images, Videos

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25.01.2021

Face detection using Python OpenCV in images and videos with speedup using CUDA GPU acceleration. Face detection is the first step to implement a face recognition system. In this quick tutorial, I explain step by step how to detect faces in images and videos using OpenCV, which might come in handy for a face recognition system or facial expression recognition system. I am using Python 3.8 on Windows 10. You can use it on Linux as well. However, the CUDA Acceleration while detecting faces on videos requires building OpenCV from the source. *Code is available for our Patreon supporters* - ► Time Stamps: Introduction: (0:00) Face Detection on Images: (0:18) Face Detection on Videos: (5:42) Enabling CUDA Acceleration: (5:58) Link to Model: 🤍 - Want to discuss more? ►Join my discord: 🤍 #TheCodingBug #FaceDetection #OpenCV - ► My Other Tutorials: ○ Build and Install OpenCV 4.5.1 With CUDA GPU Support on Windows 10: 🤍 ○ YOLOv4 On Android Using TFLite: 🤍 ○ Install TensorFlow GPU Under 90 Seconds: 🤍 ○ Install PyTorch GPU Under 90 Seconds: 🤍 ○ Custom YOLOv4 Object Detection with TensorFlow and TFLite : 🤍 ○ Darknet YOLOv4 Custom Object Detection: Part 2 (Training YOLOv4 Darknet): 🤍 ○ Darknet YOLOv4 Custom Object Detection: Part 1 (Preparing Custom Dataset): 🤍 ○ YOLOv4 Object Detection with TensorFlow, TFLite and TensorRT: 🤍 ○ Darknet YOLOv4 Object Detection for Windows 10 on Images, Videos, and Webcams: 🤍 ○ Real-Time Object Detection on Webcam and Videos Using OpenCV With YOLOv3 and YOLOv4 | Windows Linux: 🤍 ○ Build and Install OpenCV 4.4.0 With CUDA (GPU) Support on Windows 10: 🤍 ○ Install TensorFlow GPU and PyTorch with CUDA on Windows 10 Anaconda | CUDA 10.1 cuDNN 7.6: 🤍 ○ Real-time Multiple Object Tracking with YOLOv4 TensorFlow and Deep Sort | Linux, Windows: 🤍 - ► Follow us on Twitter: 🤍 ► Support us on Patreon: 🤍 - DISCLAIMER: Links included in this description might be affiliate links. If you purchase a product or service with the links that I provide I may receive a small commission. There is no additional charge to you!

How to Build OpenCV 4.1.1 with GPU (CUDA) Suport on Windows

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This video will help you to build your OpenCV-4.1.1 with GPU (CUDA) support on windows. Prerequisites:- 1. You must have Nvidia GPU mounted on your PC, and it must have CUDA support. 2. You must have installed Nvidia GPU drivers and CUDA development Kit. 3. You must have MicroSoft Visual Studio 2017 or newer version. 4. You must have installed Python 3. (Optional but Recommended) 5. You must have Installed Latest C-Make. OpenCV GIT HUB Source: (🤍 CUDA SDK Download Source: (🤍 Python Download: (🤍 C-Make Download: (🤍 Commands: To change the directory: "cd (Build Path Directory)" To build when you are in build Directory: "msbuild INSTALL.vcxproj /p:Configuration=Release" Music: 🤍

How To Install and Build OpenCV with GPU for C++ | Visual Studio Code | NVIDIA Cuda and OpenCV 4.5.2

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In this Computer Vision Tutorial, we are going to Install and Build OpenCV with GPU in C. We are going to use NVIDIA Cuda to run our OpenCV programs on an NVIDIA GPU. We will go over the installation process for all the required programs and files. We will then use CMake to do the configuration of the OpenCV source files and then build them with GPU support later on. At the end of the video, I'll show how we can include the OpenCV library with GPU support in Visual Studio code and see how we can verify that everything is set up correctly. ⭐Enroll in YOLOv7 Course: 🤍 ⭐Enroll in OpenCV GPU Course: 🤍 ⭐Enroll in SegFormer Course: 🤍 💎GitHub: 🤍 💎LinkedIn: 🤍 💎Twitter: 🤍 💵 Patreon: 🤍 💵Channel Member for help with projects, private discord, and exclusive perks: 🤍 - OpenCV Source Code: 🤍 OpenCV Contrib: 🤍 Visual Studio 2019: 🤍 Anaconda 3: 🤍 CMake: 🤍 NVIDIA Cuda: 🤍 NVIDIA cuDNN: 🤍 cuDNN Installation Guide: 🤍 Cuda Wikipedia: 🤍 Command to Install: cmake build "C:\your_path\build" target INSTALL config Release REMEMBER TO ADD THE OPENCV BIN FOLDER TO THE PATH IN ENVIRONMENTAL VARIABLES C:\your_path\opencv\build\install\x64\vc16\bin The code example is available on my GitHub: 🤍 - Join this channel to get access to exclusive perks: 🤍 Join the public Discord chat here: 🤍 Time Stamps: 0:00 - Overview 2:30 - Download OpenCV Source 5:39 - Install Visual Studio 7:03 - Anaconda and Python 7:47 - CMake 8:21 - Install NVIDIA Cuda and cuDNN 11:12 - CMake Configuration 18:09 - Build OpenCV with GPU 20:10 - Verify Installation and VSCode Setup I'll be doing other tutorials alongside this one, where we are going to use C for Computer Vision and Artificial Intelligence. The purpose of this tutorial and channel is to build an online coding library where different programming languages and computer science topics are stored in the YouTube cloud in one place. Feel free to comment if you have any questions about the things I'm going over in the video or just in general, and remember to subscribe to the channel to help me grow and make more videos in the future. :) Tags for the video: #OpenCV #opencvGPU #NVIDIA #Cuda #ComputerVision #OpenCVcpp #CPP

Corner Detection with OpenCV Cuda on GPU in C++

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In this Computer Vision and OpenCV Cuda GPU Tutorial, we will take a look at the Corner Detection Methods for OpenCV Cuda. We will see the different types of corner detectors that are implemented and how to create and use them in OpenCV C. Code examples will be shown throughout the video with the different corner detectors on a webcam. ⭐Enroll in YOLOv7 Course: 🤍 ⭐Enroll in OpenCV GPU Course: 🤍 ⭐Enroll in SegFormer Course: 🤍 💎GitHub: 🤍 💎LinkedIn: 🤍 💎Twitter: 🤍 💵 Patreon: 🤍 💵Channel Member for help with projects, private discord, and exclusive perks: 🤍 Time Stamps: 0:00 - Introduction 0:35 - OpenCV Cuda Documentation 5:30 - Corner Detection OpenCV Cuda I'll be doing other tutorials alongside this one, where we are going to use C for Algorithms and Data Structures, and Artificial Intelligence. The purpose of this tutorial and channel is to build an online coding library where different programming languages and computer science topics are stored in the YouTube cloud in one place. Feel free to comment if you have any questions about the things I'm going over in the video or just in general, and remember to subscribe to the channel to help me grow and make more videos in the future. :) Tags for the video: #OpenCVcuda #OpenCV #Cuda #NVIDIA #ComputerVision

Simple Cuda Image Processing Demo

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A simple demo of a CUDA application I wrote. My personal interest in CUDA comes from fast image processing for robotics or security applications. This demo is very, very simple. All it does is convert an image to grayscale, blur it a bit, and then apply the sobel edge finding algorithm to it. Code: 🤍

5. Getting Started with OpenCV with CUDA Support

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Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA is available from: Packt.com: 🤍 Amazon: 🤍 This is the “Code in Action” video for chapter 5 of Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA by Bhaumik Vaidya, published by Packt. It includes the following topics: 00:16 Read and display an image 1:02 Creating images using OpenCV 2:25 Drawing shapes on the blank image 3:32 Working with video stored on a computer 4:16 Working with videos from a webcam 5:04 Addition of two images 6:04 Subtracting two images 6:50 Image blending 7:38 Image inversion This book is a guide to explore how accelerating of computer vision applications using GPUs will help you develop algorithms that work on complex image data in real time. It will solve the problems you face while deploying these algorithms on embedded platforms with the help of development boards from NVIDIA such as the Jetson TX1, Jetson TX2, and Jetson TK1. Connect with Packt: Find us on Facebook: 🤍 Find us on Twitter: 🤍 Video created by Bhaumik Vaidya

Writing Code That Runs FAST on a GPU

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In this video, we talk about how why GPU's are better suited for parallelized tasks. We go into how a GPU is better than a CPU at certain tasks. Finally, we setup the NVIDIA CUDA programming packages to use the CUDA API in Visual Studio. GPUs are a great platform to executed code that can take advantage of hyper parallelization. For example, in this video we show the difference between adding vectors on a CPU versus adding vectors on a GPU. By taking advantage of the CUDA parallelization framework, we can do mass addition in parallel. Join me on Discord!: 🤍 Support me on Patreon!: 🤍

Building OpenCV from source with Cuda support on Windows

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pip uninstall opencv-python pip uninstall opencv-contrib-python 🤍 🤍 🤍 🤍 🤍 Install numpy 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍

OPENCV 4 + CUDA on Jetson Nano

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How to build and package OpenCV with CUDA support on the NVIDIA Jetson Nano Developer Kit. Please Like, Share and Subscribe! Full article on JetsonHacks: 🤍 In the video, we use: * Jetson Nano * Raspberry Pi V2 camera * Samsung T5 Drive * A 5V, 4A power supply The items above are available through the JetsonHacks Amazon store front! 🤍 As an Amazon Associate I earn from qualifying purchases. There's no charge to you, and the channel gets a small commission. Thanks! Website: 🤍 Github: 🤍 Twitter: 🤍

How to Build OPENCV with CUDA support on Jetson Nano or Xavier

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Watch all Nvidia Jetson Inference videos: 🤍 In this video, we will see how we can build #opencv with #cuda support on #jetson nano or xavier. OpenCV-Python is a library of Python bindings designed to solve computer vision problems. #opencvpython is the #python API for OpenCV, combining the best qualities of the OpenCV C API and the Python language. OpenCV supports a wide variety of programming languages such as C, Python, Java, etc., and is available on different platforms including Windows, Linux, OS X, Android, and iOS. Interfaces for high-speed GPU operations based on CUDA and OpenCL are also under active development Refer below repository for scripts to build opencv: 🤍

How To Install and Build OpenCV with GPU for Python | VS Code | NVIDIA Cuda and OpenCV 4.5.2

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29.05.2021

In this Computer Vision Tutorial, we are going to Install and Build OpenCV with GPU for Python. We are going to use NVIDIA Cuda to run our OpenCV programs on an NVIDIA GPU. We will go over the installation process for all the required programs and files. We will then use CMake to do the configuration of the OpenCV source files and then build them with GPU support later on. At the end of the video, I'll show how we can include the OpenCV library with GPU support in Visual Studio Code and see how we can verify that everything is set up correctly. ⭐Enroll in YOLOv7 Course: 🤍 ⭐Enroll in OpenCV GPU Course: 🤍 ⭐Enroll in SegFormer Course: 🤍 💎GitHub: 🤍 💎LinkedIn: 🤍 💎Twitter: 🤍 💵 Patreon: 🤍 💵Channel Member for help with projects, private discord, and exclusive perks: 🤍 - Video for Installation and C: 🤍 OpenCV Source Code: 🤍 OpenCV Contrib: 🤍 Visual Studio 2019: 🤍 Anaconda 3: 🤍 CMake: 🤍 NVIDIA Cuda: 🤍 NVIDIA cuDNN: 🤍 cuDNN Installation Guide: 🤍 Cuda Wikipedia: 🤍 Command to Install: cmake build "C:\your_path\build" target INSTALL config Release The code example is available on my GitHub: 🤍 - Join this channel to get access to exclusive perks: 🤍 Join the public Discord chat here: 🤍 Time Stamps: 0:00 - Overview 2:30 - Download OpenCV Source 3:37 - Anaconda and Python 7:33 - CMake Configuration 19:34 - Verify Installation and VSCode Setup Python I'll be doing other tutorials alongside this one, where we are going to use C for Computer Vision and Artificial Intelligence. The purpose of this tutorial and channel is to build an online coding library where different programming languages and computer science topics are stored in the YouTube cloud in one place. Feel free to comment if you have any questions about the things I'm going over in the video or just in general, and remember to subscribe to the channel to help me grow and make more videos in the future. :) Tags for the video: #OpenCV #opencvGPU #NVIDIA #Cuda #ComputerVision #OpenCVpython #Python

Lesson 1: OpenCV CUDA C++ , (device info and prepare VScode to compile OpenCV CUDA)

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In this tutorial you will learn how to prepare Visual Studio Code to Compile OpenCV CUDA C without CMAKE. and also how to get NVIDIA GPU information of your device. # OpenCV CUDA C # NVIDIA #vscode #opencv C #opencvscode #cuda #cudainfo #opencvcuda #c #gpu #gpuprogramming #cudaprogramming

Build and install OpenCV from source with CUDA and cuDNN support

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- IMPORTANT - Please add OPENCV_GENERATE_PKGCONFIG=1 flag when configuring to create the opencv.pc so other applications can find opencv. If "nvcc not found" then create following soft links to local bin. sudo ln -s /usr/local/cuda-11.3/bin/* /usr/local/bin sudo ln -s /usr/local/cuda-11.3/nvvm/bin/* /usr/local/bin - END - - IMPORTANT - cuDNN installation has changed since this video. Please refer the instruction in the documentation 🤍 - END - CUDA instillation guide: 🤍 cuDNN installation guide: 🤍 OpenCV repositories: 🤍 🤍 CUDA wiki page: 🤍 Follow me on: Email: srineshnisala🤍gmail.com GitHub: 🤍 LinkedIn: 🤍 Facebook: 🤍 Instagram: 🤍

Setup OpenCV-DNN module with CUDA backend support on Windows

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This video shows step by step tutorial on how to set up the OpenCV-DNN module with CUDA backend support on Windows. ① ⚡⚡ Website Blog post on this ⚡⚡ 👉🏻 🤍 ⚡⚡ Medium post ⚡⚡ 👉🏻 🤍 ② ⚡⚡ Website Blog post on CUDA & cuDNN installation ⚡⚡ 👉🏻 🤍 ⚡⚡ Medium post on CUDA & cuDNN installation ⚡⚡ 👉🏻 🤍 ③ ⚡⚡ Required Software ⚡⚡ 👉🏻 CMake GUI: 🤍 👉🏻 Anaconda: 🤍 👉🏻 Microsoft Visual Studio: 🤍 ④ ⚡⚡ CUDA Toolkit download links ⚡⚡ 👉🏻 🤍 👉🏻 🤍 ⑤ ⚡⚡ Latest cuDNN version download ⚡⚡ 👉🏻 🤍 ⚡⚡ cuDNN archive download link ⚡⚡ 👉🏻 🤍 ⑥ ⚡⚡ OpenCV download link ⚡⚡ 👉🏻 🤍 👉🏻 🤍 ⑦ ⚡⚡ CUDA compiler Compute Capability(CC) link ⚡⚡ 👉🏻 🤍 #opencvdnncuda #opencvdnn #objectdetection #opencvdnnwindows ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ GitHub repo with all the code and stuff: 🤍 Follow me on twitter: 🤍 Follow me on insta: 🤍 Contact me directly: ✉ 👉🏻 admin🤍techzizou.com ✉ 👉🏻 support🤍techzizou.com ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Making these videos takes a lot of time and effort, so if you like these videos and if you can, then please support the channel using any of the following: ► Buy me a coffee! ☕ 👉🏻 buymeacoffee.com/techzizou ► Support channel on Patreon! 🖖 👉🏻 🤍 ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Thanks for watching!

HowTo Build OpenCV With Cuda

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00:12:31
28.06.2020

This is a tutorial on how to build your own opencv libraries from source code with support for cuda. Download Links: Nvidia drivers (🤍 Cuda toolkit (🤍 OpenCV source code (🤍 Opencv contrib source code (🤍 Cmake (🤍 Visual Studio Community (🤍

Lesson 3: OpenCV CUDA C++ , (Bilateral Filter, and Compare CPU & GPU Speed)

17
0
0
00:10:17
16.01.2023

In this video we will cover Bilateral Filter in c and opencv with CUDA. We also compare speed of CPU and GPU to perform the task. #opencv #opencvcuda #cuda #c #opencv cuda #vscode # visual studio code #Bilateral #Bilateral Filter #GPU #compare cpu & gpu #image processing #imageproccessing #jetson nano #jetson

OpenCV (C++) Contrib cuDNN CUDA GPU Installation on Ubuntu and Integration with Qt

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00:10:28
08.10.2018

#opencv #qt #ubuntu OpenCV C Kütüphane sinin Contrib ve cuDNN CUDA GPU ile Ubuntu ya Kurulum u ve Qt ile Kullanım OpenCV C Qt Ubuntu installation with CUDA contrib gpu cuDNN OpenCV C Ubuntu installation compile with Cmake GCC and Qt OpenCV C Kütüphane sinin Extra Modül ü Contrib ile Ubuntu Kurulum u ve Qt ile Kullanım OpenCV C Kütüphanesi nin (Contrib ile) Kaynak kod larından CMake (GCC) ile Ubuntu ya Kurulum How to install opencv contrib on Ubuntu OpenCV Contrib Ubuntu ya nasıl kurulur OpenCV Contrib OpenCV Contrib Ubuntu Installation OpenCV Contrib linking with Qt Ubuntu Installation OpenCV Contrib integration with Qt Ubuntu Installation OpenCV Contrib Ubuntu Kurulumu Qt OpenCV Contrib Ubuntu Kurulumu OpenCV Contrib Ubuntu Kurulumu ve Qt ile entegre edilmesi OpenCV Qt image processing OpenCV Qt görüntü işleme OpenCV Qt computer vision OpenCV Qt bilgisayarlı görü OpenCV Qt deep learning OpenCV Qt derin öğrenme OpenCV Qt machine learning OpenCV Qt makine öğrenmesi 🤍

Лекция 12 Opencv+cuda Jetson

250
14
0
00:40:30
12.12.2021

На этой лекции напишем код для работы с оптическим потоком с использование вычислений на cuda. Сравним обработку на процессоре и видеокарте на встраиваемом компьютере Jetson Nano Готовый образ для jetson 🤍 Статья, код которой использовался на лекции 🤍

OpenCV C++ tutorial to calculate optical flow on GPU using cuda::FarnebackOpticalFlow

1752
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1
00:10:23
09.12.2020

This OpenCV tutorial is a very simple code example of GPU Cuda optical flow in OpenCV written in C. The configuration of the project, code, and explanation are included for farneback Optical Flow method. Farneback algorithm is a dense method that is used to process all the pixels in the given image. The dense methods are slower but more accurate as all the pixels of the image are processed. In the following example, I am displaying just a few pixes based on a grid. Code available here 🤍 News on Facebook 🤍 Blog 🤍

Visual Studio 2019에서 CUDA를 적용한 OpenCV 빌드하기

5405
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00:11:55
06.07.2020

안녕하세요. 웹나우테스입니다. 이번 영상에서는 OpenCV에서 GPU 가속을 사용하기 위해 OpenCV를 빌드하는 방법을 다룹니다. 사용중인 NVIDIA 그래픽카드에 맞는 CUDA Toolkit와 cuDNN을 설치하고 cmake를 사용하여 OpenCV 빌드 옵션을 설정한 후, Visual Studio 2019에서 OpenCV 빌드를 진행합니다. NVIDIA 그래픽카드가 장착된 PC에서만 사용할 수 있는 방법입니다. 다음 글을 참고하였습니다. 🤍 도움이 되었으면 좋아요와 구독을 해주세요. 감사합니다. OpenCV 공부하실때 다음 책을 추천합니다. 알짜배기 예제로 배우는 OpenCV 🤍 Python과 C로 작성된 풍부한 예제가 포함되어 있습니다. 블로그 🤍 음악 출처 🤍

OpenCV CUDA Module | CUDA Toolkit 10 | CMake Tutorial | Windows | Visual Studio | Cuda Education

718
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6
01:26:13
01.01.2019

PLEASE NOTE: After building "INSTALL" in Visual Studio, add bin folder directory to "Path" Environment Variable. On my system the build folder was in C:\cudaeducationVIDEO\CMAKE_OUTPUT\install\x64\vc15\bin   |  Make sure to restart your computer before continuing. Also make sure you are online during the CMAKE Configure process, as it is actively downloading data off the internet. OpenCV + CUDA GPU functionality walkthrough. Visit cudaeducation.com/opencvcuda for more information. If you are interested in learning more about OpenCV + Cuda, I highly recommend the book "Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA" Check out the book on Amazon: 🤍 DISCLAIMER: Use at your own risk! This code and/or instructions are for teaching purposes only. CUDA Education does not guarantee the accuracy of this code in any way. The code and instructions on this site may cause hardware damage and/or instability in your system. This code and/or instructions should not be used in a production or commercial environment. Any liabilities or loss resulting from the use of this code and/or instructions, in whole or in part, will not be the responsibility of CUDA Education. All rights reserved. This code is the property of CUDA Education. Please contact CUDA Education at cudaeducation🤍gmail.com if you would like to use this code in any way, shape or form.

COMO INSTALAR OPENCV e CUDA - FINALMENTE UM TUTORIAL QUE FUNCIONA !!! Acelere sua rede YOLO

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00:22:42
10.11.2020

Neste vídeo você vai aprender a instalar de uma vez por todas o suporte a GPU do Opencv 4 e dar um boost na sua rede yolo. Quer aprender rapidamente Inteligência Artificial voltado para desenvolvedores e não para Cientistas de Dados. Aprenda os principais fundamentos dessa tecnologia e aplique em seus sistemas Web, Desktop e Mobile com JavaScript. 🤍 Comandos utilizados no vídeo: sudo apt install build-essential cmake git pkg-config libgtk-3-dev libavcodec-dev libavformat-dev libswscale-dev libv4l-dev libxvidcore-dev libx264-dev libjpeg-dev libpng-dev libtiff-dev gfortran openexr libatlas-base-dev python3-dev python3-numpy libtbb2 libtbb-dev libdc1394-22-dev libopenexr-dev libgstreamer-plugins-base1.0-dev libgstreamer1.0-dev sudo apt install g-9 gcc-10 g-10 mkdir opencv_build 🤍 mkdir ~/opencv_build && cd ~/opencv_build git clone 🤍 git clone 🤍 cd opencv mkdir build cd build ## Verificar path do python ## Verificar a arquitetura da GPU 🤍 cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_C_COMPILER=/usr/bin/gcc-9 -D CMAKE_INSTALL_PREFIX=/usr/local -D INSTALL_PYTHON_EXAMPLES=ON -D INSTALL_C_EXAMPLES=OFF -D WITH_TBB=ON \D WITH_V4L=ON -D WITH_QT=OFF -D WITH_OPENGL=ON -D WITH_GSTREAMER=ON -D OPENCV_GENERATE_PKGCONFIG=ON -D OPENCV_PC_FILE_NAME=opencv.pc -D OPENCV_ENABLE_NONFREE=ON -D OPENCV_PYTHON3_INSTALL_PATH=$HOME/.local/lib/python3.10/site-packages -D OPENCV_EXTRA_MODULES_PATH=$HOME/opencv_build/opencv_contrib/modules -D PYTHON_EXECUTABLE=/usr/bin/python3 -D BUILD_EXAMPLES=ON -D WITH_CUDA=ON -D WITH_CUDNN=ON -D OPENCV_DNN_CUDA=ON -D ENABLE_FAST_MATH=1 -D CUDA_FAST_MATH=1 -D CUDA_ARCH_BIN=7.5 -D BUILD_opencv_cudacodec=OFF -D WITH_CUBLAS=1 -D CUDNN_LIBRARY=/usr/local/cuda/lib64/libcudnn.so -D CUDNN_INCLUDE_DIR=/usr/local/cuda/include -D WITH_VA=OFF .. nproc make -j12 sudo make install Download dos pesos e arquivos da Yolo 🤍 #tutorial , #opencv, #cuda, #visaocomputacional #programação , #dev , #código, #vidadeprogramador, #machinelearning, #sistemasdeinformação, #inteligenciaartifical, #programador, #code, #python, #computer dc, #codingdays, #tecnologia, #ti, #Blockchain, #java, #programador, #developer, #sistemasdeinformação, #inteligênciaartificial

demo generate project opencv cuda

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00:07:02
25.11.2015

reference: 🤍

Como Instalar OpenCV com CUDA (GPU NVidia) no Windows 10

905
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00:07:30
12.02.2021

Como Instalar OpenCV com CUDA (GPU NVidia) no Windows 10 Aumente a velocidade de processamento para OpenCV com aceleração de GPU CUDA. Aprenda a compilar OpenCV com CUDA no Windows 10 a partir do código fonte. A instalação desta forma permite que o OpenCV seja usado em qualquer linguagem de programação (Python, C, etc.). Esse vídeo: 🤍 💎 MUNDO TUDO FÁCIL: 🤍 💡 INSTAGRAM: 🤍 💡 FACEBOOK: 🤍 #PompilioAraujoJr #MundoTudoFacil

OpenCV 4.1.1 con soporte CUDA - Jetson Nano

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00:07:17
19.04.2020

Instalación y prueba de funcionamiento de la librería OpenCV 4.1.1 con soporte CUDA en la Jetson Nano Versión de OpenCV: 4.1.1 Para más tutoriales, visita mi página: 🤍julianchaux.com

在Windows10上使用visual studio 2019编译opencv源码, 支持cuda加速,使用cmake-gui

683
6
0
00:18:33
29.12.2019

视频对应图文博文: 🤍 cmake官网: 🤍 windows安装cuda和cudnn: 🤍 搬瓦工VPS: 🤍 搬瓦工官方机场: 🤍 背景音乐: 🤍

YOLOv4 inference using OpenCV-DNN-CUDA module on Windows (Using Python)

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00:10:00
15.05.2022

This video shows step by step tutorial on how to run yolov4 inference using the opencv-dnn-cuda module on Windows. ① ⚡⚡ Website Blog post on this ⚡⚡ 👉🏻 🤍 ⚡⚡ Medium post ⚡⚡ 👉🏻 🤍 ② ⚡⚡ Website Blog post on CUDA & cuDNN installation ⚡⚡ 👉🏻 🤍 ⚡⚡ Medium post on CUDA & cuDNN installation ⚡⚡ 👉🏻 🤍 ③ ⚡⚡ Github link for Official Darknet repository ⚡⚡ 👉🏻 🤍 ④ ⚡⚡ CUDA Toolkit download links ⚡⚡ 👉🏻 🤍 👉🏻 🤍 ⑤ ⚡⚡ Latest cuDNN version download ⚡⚡ 👉🏻 🤍 ⚡⚡ cuDNN archive download link ⚡⚡ 👉🏻 🤍 ⑥ ⚡⚡ OpenCV download link ⚡⚡ 👉🏻 🤍 👉🏻 🤍 ⑦ ⚡⚡ CUDA compiler Compute Capability(CC) link ⚡⚡ 👉🏻 🤍 #yolov4opencvdnn #objectdetection #yolov4onwindows #opencvdnncuda #opencvdnn ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ GitHub repo with all the code and stuff: 🤍 Follow me on twitter: 🤍 Follow me on insta: 🤍 Contact me directly: ✉ 👉🏻 admin🤍techzizou.com ✉ 👉🏻 support🤍techzizou.com ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Making these videos takes a lot of time and effort, so if you like these videos and if you can, then please support the channel using any of the following: ► Buy me a coffee! ☕ 👉🏻 buymeacoffee.com/techzizou ► Support channel on Patreon! 🖖 👉🏻 🤍 ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Thanks for watching!

OpenCV Programming with CUDA on Linux 1: Installation of CUDA with OpenCV

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00:07:56
09.12.2014

In this tutorial I show how to download, install, and configure NVIDIA CUDA and OpenCV.The CUDA example that I use to test the installation is an example of the application of the HOG descriptor for people detection that can be found here: opencv_source_code/samples/gpu/hog.cpp NVIDIA GPUs are built on what’s known as the CUDA Architecture. You can think of the CUDA Architecture as the scheme by which NVIDIA has built GPUs that can perform both traditional graphics rendering tasks and general-purpose tasks. To program CUDA GPUs, the language that is used is CUDA C. CUDA C is essentially C with a handful of extensions to allow programming of massively parallel machines like NVIDIA GPUs. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in the commercial products. Being a BSD-licensed product, OpenCV makes it easy for businesses to utilize and modify the code. The library has more than 2500 optimized algorithms, which includes a comprehensive set of both classic and state-of-the-art computer vision and machine learning algorithms. These algorithms can be used to detect and recognize faces, identify objects, classify human actions in videos, track camera movements, track moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras, stitch images together to produce a high resolution image of an entire scene, find similar images from an image database, remove red eyes from images taken using flash, follow eye movements, recognize scenery and establish markers to overlay it with augmented reality, etc. OpenCV has more than 47 thousand people in their user community and an estimated number of downloads exceeding 7 million. The library is used extensively in companies, research groups and by governmental bodies. email: fpiscani🤍stemapks.com twitter: 🤍 git: 🤍

Lesson 2: OpenCV CUDA C++ , (Gaussian Blur, and Compare CPU & GPU Speed)

25
1
0
00:15:53
14.01.2023

In this video we will cover Gaussian Blur Filter in c and opencv with CUDA. We also compare speed of CPU and GPU to perform the task. #opencv #opencvcuda #cuda #c #opencv cuda #vscode # visual studio code #Gaussian #Gaussian Blur #Blur #GPU #compare cpu & gpu #image processing #imageprocessing

OpenCV Programming with CUDA on Linux - 3: Running your First CUDA Program

4166
23
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00:09:10
06.02.2015

In this tutorial I show how to run your first CUDA program running on a CUDA-enabled graphics processing unit from NVIDIA. NVIDIA GPUs are built on what’s known as the CUDA Architecture. You can think of the CUDA Architecture as the scheme by which NVIDIA has built GPUs that can perform both traditional graphics rendering tasks and general-purpose tasks. To program CUDA GPUs, the language that is used is CUDA C. CUDA C is essentially C with a handful of extensions to allow programming of massively parallel machines like NVIDIA GPUs. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in the commercial products. Being a BSD-licensed product, OpenCV makes it easy for businesses to utilize and modify the code. The library has more than 2500 optimized algorithms, which includes a comprehensive set of both classic and state-of-the-art computer vision and machine learning algorithms. These algorithms can be used to detect and recognize faces, identify objects, classify human actions in videos, track camera movements, track moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras, stitch images together to produce a high resolution image of an entire scene, find similar images from an image database, remove red eyes from images taken using flash, follow eye movements, recognize scenery and establish markers to overlay it with augmented reality, etc. OpenCV has more than 47 thousand people in their user community and an estimated number of downloads exceeding 7 million. The library is used extensively in companies, research groups and by governmental bodies. email: fpiscani🤍stemapks.com twitter: 🤍 git: 🤍

jetson nano編 opencv cuda與VScode C++ cv程式

169
00:27:54
05.07.2022

jetson nano編 opencv cuda與VScode C程式,[Jetson Nano連樹莓派NOIR紅外線相機opencv C測試]🤍

超簡易openCV cuda C++程式在Jetson Nano編譯執行

1434
11
00:24:10
25.07.2020

有關cuda的影片:🤍 超簡易openCV cuda C程式在Jetson Nano編譯執行。程式撰寫很簡易,影片前面還在囉嗦安裝問題,要知道沒有環境連RUN都不可能,相同程式在win 10,沒有完整用cmake重編opencv cuda也是不行 ,沒有cuda就一切沒有,Nvidia Jetson Nano在此雖然省了裝cuda的大事,但自帶的opencv是沒有的cuda的,沒有cuda功能,用8G ram的樹莓派,run openCV效能反而更好。opencv cuda的資料不多,其中一主因就是能完整安裝者不多,修修補補也是方法,安裝錯誤訊息顯示少什麼就補什麼,檔案有多少?會累死。要完整安裝此套件,其實是有竅門的,Linux環境要重編cmake-gui開始(cmake純文字,不copy& paste怎麼用?),克服套件安裝相依性問題,畢其功於一役,一次性解決。 「類vscode軟體code-ossi編寫C」🤍 「安裝opencv cuda套件」🤍 「Linux上安裝NVIDIA CUDA Toolkit與路徑設定」🤍

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