Opencv dnn

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Introduction to OpenCV DNN Module - OpenCV and Computer Vision with GPU

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05.06.2021

In this Computer Vision Tutorial, we are going to have an Introduction to OpenCV DNN Module. We will look at the DNN Module in the OpenCV documentation and go over the built-in classes and methods. We will see how to use the methods to load in neural networks with OpenCV and deploy them. At the end of the video, we will see an example with object detection that we will go in depth with in the next video line by line. Join this channel to get access to exclusive perks: 🤍 Join the public Discord chat here: 🤍 The code example is available on my GitHub: 🤍 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: #OpenCVdnn #OpenCV #DNN #ComputerVision #DeepLearning

Deep Learning with OpenCV DNN Module | Full Course | 3 hours

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11.12.2021

This is the most detailed course on Deep Learning using OpenCV’s DNN module out there, yes a complete 3-hour course that takes you from no background in DNN module, and teaches you all about it, including how to train custom classifiers and custom object detectors in TensorFlow and then deploy it in OpenCV module. You’ll also learn all the nitty-gritty details about this module in the course. Download Code: 🤍 Join for the Computer Vision Course: 🤍 Blogpost for Each Section: Section 1: 🤍 Section 2: 🤍 Section 3: 🤍 If you want us to create AI and computer vision solutions for you, then reach out to us here: 🤍 00:00 Intro 01:08 Introduction to OpenCV's Deep Neural Network Module 01:45 What are the Benefits 03:39 A Bummer that You Must Know About 04:01 So Which Frameworks can be Used to Train Neural Networks? 05:22 Section 1 - Image Classification with DenseNet121 06:04 Import the Libraries 06:15 Load the Class Labels 08:05 Extract the Label 08:36 Initialize the DNN Module 11:48 Read an Image 12:19 Pre-process an Image 18:53 Input the Blob Image to the Network 19:12 Forward Pass 21:48 Apply Softmax Function to get Probabilities 25:27 Create Functions 26:57 Initialization Function 28:05 Classification Function 29:31 Initialize the Classifier 29:34 Classify Images Using the Function 30:12 Perform Real-Time Image Classification 32:55 Important Details Regarding the DNN Module 37:49 Section 2 - Training Custom Image Classifier with Tensorflow, Converting to ONNX and using it in OpenCV DNN module 38:48 (Part 1) Training a Custom Image Classifier with Tensorflow 38:51 Import the Libraries 42:07 Download and Unzip the Dataset folder 43:52 Check the number of images in each class 45:19 Generate Images 01:01:10 Visualize Images 01:04:11 Create the model 01:11:11 compile the model 01:11:13 Model Summary 01:19:28 Train The Model 01:23:22 Visualize Training Results 01:24:15 Test on new Examples 01:28:33 Save your model to Disk 01:29:29 (Part2) Converting Our Classifier to ONNX format 01:33:16 (Part 3) Using the ONNX model in the OpenCV DNN module 01:38:26 Create Functions 01:38:26 Initialization Function 01:38:36 Classification Function 01:42:32 Section 3 - Training Object Detector with Tensorflow Object Detection API 01:52:02 (Part 1) Environmental Setup 01:52:32 (Part 2) Installation & TFOD API Setup 01:55:11 Import Required Libraries 01:55:29 Clone Tensorflow Object Detection Model Repository 01:57:25 Install Tensorflow Object Detection API & Compile Protos 02:01:16 You can Check your installation of TFOD API by Running model_builder_test.py 02:02:06 Download the Support Folder required to run this Notebook 02:03:05 (Part 3) Data Collection & Annotation 02:04:41 Step 1: Download Youtube Video 02:05:49 Step 2: Split Video Frames and store it 02:12:55 Step 3: Annotate Images with labelImg 02:19:26 Step 4: Create a label Map file 02:21:04 Step 5: Generate TFrecords 02:39:09 (Part 4) Downloading Model & Configure it 02:39:09 (Part 5) Training and Exporting Inference Graph If you enjoyed this video then don't forget to subscribe and like this video. 🎇 Subscribe to this Channel: 🤍 🎇 Subscribe to Bleed AI Blog: 🤍 🎇 Check out our Courses: 🤍 Follow Bleed AI for more 👣 : ◼ Website: 🤍 ◼ Facebook Page: 🤍 ◼ Linkedin: 🤍 ◼ Instagram: 🤍 ◼ Twitter: 🤍 ◼ Patreon: 🤍 #imageclassification #objectdetection #deeplearning #crashcourse #opencv #tensorflow

How To Deploy Neural Networks with OpenCV DNN and GPU in C++ | 100+ FPS Object Detection

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11.06.2021

In this Computer Vision Tutorial, we are going to learn How To Deploy Neural Networks with OpenCV DNN and GPU in C. We will go over each step in deploying trained neural networks for inference with OpenCV. We will see how to use the methods to load in neural networks with OpenCV and deploy them. At the end of the video, we will see an example with object detection, where we can detect a lot of different objects from the Coco dataset with 100 FPS+ on a GPU with OpenCV. Link to .pb file with weights: 🤍 Join this channel to get access to exclusive perks: 🤍 Join the public Discord chat here: 🤍 The code example is available on my GitHub: 🤍 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: #OpenCVdnn #OpenCV #DNN #ObjectDetection #ComputerVision #DeepLearning

How To Deploy Neural Networks with OpenCV DNN and GPU in Python | 100+ FPS Object Detection

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00:27:34
07.06.2021

In this Computer Vision Tutorial, we are going to learn How To Deploy Neural Networks with OpenCV DNN and GPU in Python. We will go over each step in deploying trained neural networks for inference with OpenCV. We will see how to use the methods to load in neural networks with OpenCV and deploy them. At the end of the video, we will see an example with object detection, where we can detect a lot of different objects from the Coco dataset with 100 FPS+ on a GPU with OpenCV. Join this channel to get access to exclusive perks: 🤍 Join the public Discord chat here: 🤍 The code example is available on my GitHub: 🤍 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: #OpenCVdnn #OpenCV #DNN #ObjectDetection #ComputerVision #DeepLearning

Build your OBJECT DETECTION SOFTWARE - Crash course | with Opencv and Python (2022)

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11.01.2022

Blog: 🤍 Software that can detect Objects in real-time is one of the most requested and useful resources that Computer Vision can offer at the moment and in this crash course you will learn the basics of doing it. ➤ Courses: Full Computer Vision course: 🤍 Training Mask R-CNN PRO (Notebook + Mini-Course): 🤍 ➤ Follow me on: LinkedIn: 🤍 ➤ For business inquiries: 🤍 #computervision #software #deeplearning

Setup OpenCV-DNN module with CUDA backend support on Windows

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13.05.2022

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!

Setup OpenCV-DNN module with CUDA backend support on Linux

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24.05.2022

This video shows step by step tutorial on how to set up the OpenCV-DNN module with CUDA backend support on Linux. ① ⚡⚡ Website Blog post on this ⚡⚡ 👉🏻 🤍 ⚡⚡ Medium post ⚡⚡ 👉🏻 🤍 ② ⚡⚡ Website Blog post on CUDA & cuDNN installation ⚡⚡ 👉🏻 🤍 ⚡⚡ Medium post on CUDA & cuDNN installation ⚡⚡ 👉🏻 🤍 ③ ⚡⚡ CUDA Toolkit download links ⚡⚡ 👉🏻 🤍 👉🏻 🤍 ④ ⚡⚡ Latest cuDNN version download ⚡⚡ 👉🏻 🤍 ⚡⚡ cuDNN archive download link ⚡⚡ 👉🏻 🤍 ⑤ ⚡⚡ OpenCV download link ⚡⚡ 👉🏻 🤍 👉🏻 🤍 ⑥ ⚡⚡ CUDA compiler Compute Capability(CC) link ⚡⚡ 👉🏻 🤍 #opencvdnncuda #opencvdnn #objectdetection #opencvdnnlinux ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 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 DNN Face Detector example

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25.08.2019

It is an implementation of the OpenCV Face Detector example in Python and Pygame, with reference to the tutorial in 🤍

Video Classification using OpenCV's dnn Module

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29.12.2020

The program and details are available on my blog 🤍 In this demo video, video classification is shown by using OpenCV's dnn module as deep learning inference engine. The pre-trained deep learning model based on Caffe framework namely BVLC GoogleNet which is trained on the famous ImageNet dataset is used for the inference purpose. The program can provide classification output for video file as well as for the live feed from webcam.

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. - 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

【PYTHON OPENCV】Object detection OpenCV DNN module using MobileNet SSD and caffe pre trained models

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03.05.2021

Source Code: 🤍 with ❤ by Edward Lance Lorilla Apache CXF,Ajax,Amazon Web Services,Angular Google Charts,Angular High Charts,Angular Material,Angular Material 7,Angular2,Angular4,Angular6,Angular7,Angular8,AngularJS,Angular CLI,Apache Tapestry,ASP.Net,Atomics,Aurelia,Axure RP,AWS Lambda,BabelJS,BabylonJS,BackboneJS,Bootstrap,Ngx Bootstrap,Bootstrap 4,Bulma,CakePHP,CherryPy,Codeigniter,CoffeeScript,CPanel,CSS,CSS Buttons,D3JS,DC.js,Django,Drupal,Electron,EmberJS,ExpressJS,ExtJS,ES6,Firebase,Flask,Adobe Flex,Flexbox,Foundation,Framework7,FuelPHP,GraphQL,Grav,Google Maps,Grunt,Gulp,GWT,GWT Google Charts,GWT High Charts,Highcharts,HTML,HTML5,HTTP,JasmineJS,JavaScript,Joomla,jQuery,jQueryUI,JSF,KnockoutJS,KoaJS,Laravel,LESS,LeafletJS,Lodash,Next.js,MathML,Magento Framework Material Design Lite,Materialize,MeanJS,Momentjs,Mootools,MVC Framework,Parallax Scrolling,PhantomJS,Phalcon,PHP,PHP-7,Prototype,Polymer,Pure.CSS,Requests,Redux,RichFaces,RIOT.JS,ReactJS,RequireJS RESTful Web Services,Ruby on Rails-2.1,Ruby on Rails,RxJS,SASS,Sencha Touch,script.aculo.us,SVG,Symfony,TurboGears,Typescript,TypeORM,Underscorejs,Vaadin,VBScript,VueJS,W3CSS Web Developer's Guide,Web Icons,Web2Py,WebGL,WebRTC,Web Services,Website Development,Web Sockets,Wordpress,XHTML,Yii,Zend Framework SCRIPTS,JavaScript,jQuery,jQueryUI,Lua,Perl,PHP,PHP-7,Python,Python-3,RSpec,Ruby,Sed,Tcl/Tk,Unix,VBScript,WEB DEVELOPMENT,Adaptive Software Development,Agile Methodology,Agile Data Science,Artificial Intelligence,Computer Programming,Inter Process Communication,C by Examples,Basics of Computers,Basics of Computers Science,Basic Electronics,Behavior Driven Development,Cloud Computing,Compiler Design,Computer Concepts,Computer Fundamentals,Computer Graphics, Computer Logical Organization,Computer Programming,Cryptography,Computer Networking,Data Mining,Data Structure & Algorithms,Design and Analysis of Algorithms,DBMS,Digital Circuits,Digital Image Processing,Discrete Mathematics,Distributed DBMS,Data Warehouse,E-Commerce,Embedded Systems,Estimation Techniques,Extreme Programming,Functional Programming,Graph Theory,HTTP,Human Computer Interface,Information Security and Cyber Law,Internet of Things (IoT),Internet Technologies,IPv4,IPv6,Image Processing with Java,Mgmt Information System,Microprocessor,Mobile Computing,Network Theory,OOAD,Operating System,Parallel Algorithm,Parallel Computer Architecture,Programming Methodologies,SEO Techniques,SOA,SOAP,Software Architecture Design,Software Engineering,S/W Development Life Cycle (SDLC),UDDI,UML, ,Artificial Intelligence with Python,Beautiful Soup,BioPython,Bokeh,Concurrency with Python,Cryptography with Python,Jupyter,Jython,Logistic Regression in Python,Matplotlib,Machine Learning with Python,MongoEngine,Numpy,Object Oriented Python,Peewee,PyGTK,PyQt,PyQt5,Python,Python-3,PyCharm,Python Blockchain,Python Data Access,Python Data Persistence,Python Deep Learning,Python Design Pattern,Python Digital Forensics,Python Web Scraping,Python Data Structure,Python Data Science,Python MongoDB,Python MySQL,Python Pillow,Python PostgreSQL,Python SQLite,Python Network Programming,PyTest,PyTorch,Python Text Processing,Python Forensics,Python Panda,Python Web Development Libraries,PySpark,rxpy,Seaborn,Scipy,Sympy,WxPython,Unix,Android,Aurelia,Cordova,Flutter,Google AMP,Ionic,iOS,iOS Development with Swift2,jQuery Mobile,Kotlin,Mobile Angular UI,Meteor,NativeScript,PhoneGap,React Native,SL4A,XamarinSockets,Apex,Arduino,Assembly,Awk,C Standard Library,Clojure,COBOL,C,C,C Standard Library,C#,Dart,D,Elixir,Elm,Erlang,Euphoria,Fortran,F#,Go Programing,Groovy,Haskell,Java,Java-8,Java Bean Utils,JCL,KDB+,LISP,LOLCODE,LOGO,MATLAB,Node.js,Objective C,OAuth2.0,Pascal,Parrot,CGI with PERL,Prolog,R Programming,Rexx Programming,Rust Programming,Scala,Scala Collection,Socket.io,Solidity,Swift,VB.Net,VBA,WebAssembly,DEVOPS,Ansible,Bugzilla,Chef,Consul,Docker,Gerrit,Git,Gitlab,Jira,Kubernetes,LogStash,Makefile,Mantis,Nagios,OpenShift,Puppet,Saltstack,ServiceNow,Scrapy,SVN,UNIX,Linux Admin,Ubuntu,Virtualization2.0,VersionOne,LATEST TECHNOLOGIES,Ansible,Apache Camel,Apache Flink,Bitcoin,Blockchain,Blue Prism,CloudRail,Docker,Elastic Search,Ethereum,OpenShift,Python Blockchain,Salesforce,TweetDeck,Unity,Virtualization2.0,TELECOM,5G,CDMA,FTTH,GPRS,GSM,i-Mode,LTE,NGN,SIP,Telecom Billing,Telecommunication Switching Systems and Networks (TSSN),UMTS,WAP,Wi-Fi,WiMAX,WML,EXAMS SYLLABUS,Bihar PSC Syllabus,CBSE Syllabus,CDS Syllabus,Chhattisgarh PSC Syllabus,Civil Services Exam Syllabus,GATE Exams Syllabus,IBPS PO Syllabus,Madhya Pradesh PSC Syllabus,NDA Syllabus,Rajasthan PSC Syllabus,SBI PO Syllabus,Uttar Pradesh PSC Syllabus,Agile Testing,Apache Bench,Balsamiq Mockups,Bugzilla,SEI CMMI,Computer Security,Concordion,Continuous Integration,Cucumber,Database Testing,Espresso Testing,Ethical Hacking,ETL Testing,Internet Security,Jenkins,Kali Linux,Malw

Text Detection using Neural Networks | OPENCV Python

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01:26:24
18.02.2020

In this video, we are going to learn how to detect text by creating a Convolution Neural Network to Classify digits from 0 to 9. We will write the Training code from scratch and go step by step to train about 10000 images of 10 different classes. Later we will create a testing script to use along with a webcam. I will be sharing all the details including the version of the packages and the parameters for the training Code & Files: coming soon Premium Courses: ✔️ Computer Vision Game Development Course: 🤍 ✔️ Computer Vision with Arduino Course: 🤍 ✔️ Advanced Drone Programming Course: 🤍 ✔️ Learn to Build Computer Vision Mobile Apps: 🤍 ✔️ Jetson Nano Premium Course: 🤍 Follow Me: Facebook Group: 🤍 Discord: 🤍 Facebook Page: 🤍 Instagram : 🤍 Website: 🤍 Github: 🤍 Product Links: Recommend Webcam for Computer Vision: 🤍 Budget Webcam: 🤍 Computer Vision Robot Arm : 🤍 Cheap Drone for OpenCV: 🤍 DC Motors + Wheels + Chassis: 🤍 DC Motors + Wheels: 🤍 Arduino UNO: 🤍 Motor Driver: 🤍 Battery: 🤍 Raspberry Pi 4 Best Starter Kit: 🤍 Raspberry Pi Recommended Battery: 🤍 My Setup: Mouse: 🤍 Mechanical Keyboard: 🤍 Normal Keyboard: 🤍 GPU: 🤍 CPU: 🤍 SSD: 🤍 MIC: 🤍 Camera: 🤍 3D Printer: 🤍 Sim Race: 🤍 #ComputerVision #OpenCV #CVZone

👨 Detectar rostros con modelos pre-entrenados con DNN de OpenCV | Python

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29.08.2022

¡Omesitos! En este video veremos como usar un modelo pre entrenado con Deep Learning para detectar rostros en una imagen. ¡Vamos a por ello! 😊. CONVIÉRTETE EN MIEMBRO DEL CANAL ❤️: 🤍 👩‍💻 PROGRAMACIÓN AQUÍ: 🤍 VERSIONES USADAS EN ESTE VIDEOTUTORIAL: - Python 3.8.3 - opencv-contrib-python4.6.0 CONTENIDO: 0:00​ - Introducción 0:20 - ¡Vamos con la programación! 💻 0:41 - Instalación de OpenCV 2:03 - Activación del entorno virtual en VS Code 2:43​ - Descargar arquitectura y pesos 6:08 - Leer imagen de entrada 7:02 - ¡Blob! 9:15 - ¡Experimentemos! 🧪 9:48 - 👨 ¡A detectar rostros! 👩 12:56 - Dectando rostros en video. LINKS: 🔗 Arquitectura: 🤍 🔗 Pesos: 🤍 🔗 Blob: 🤍 REFERENCIAS: 🔗 🤍 🔗 🤍 🔗 🤍 🔗 🤍 🔗 🤍 🔗 🤍 MI WEB: 💜👩‍💻 🤍omes-va.com MIS REDES SOCIALES: ☑️INSTAGRAM: 🤍gaby_omes 🔗🤍 ☑️FACEBOOK: 🤍GabyOmes 🔗🤍

opencv dnn

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00:01:01
22.12.2018

Uma demonstração de uso do OpenCV 4 com DNN para fazer detecção facil com muita acurácia. O artigo relacionado explicando como configurar CUDA, compilar o OpenCV 4 em um container e outros detalhes está em 🤍

【PYTHON OPENCV】Face detection using OpenCV DNN face detector

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00:10:00
13.04.2021

🤍 ❤ by Edward Lance Lorilla Apache CXF,Ajax,Amazon Web Services,Angular Google Charts,Angular High Charts,Angular Material,Angular Material 7,Angular2,Angular4,Angular6,Angular7,Angular8,AngularJS,Angular CLI,Apache Tapestry,ASP.Net,Atomics,Aurelia,Axure RP,AWS Lambda,BabelJS,BabylonJS,BackboneJS,Bootstrap,Ngx Bootstrap,Bootstrap 4,Bulma,CakePHP,CherryPy,Codeigniter,CoffeeScript,CPanel,CSS,CSS Buttons,D3JS,DC.js,Django,Drupal,Electron,EmberJS,ExpressJS,ExtJS,ES6,Firebase,Flask,Adobe Flex,Flexbox,Foundation,Framework7,FuelPHP,GraphQL,Grav,Google Maps,Grunt,Gulp,GWT,GWT Google Charts,GWT High Charts,Highcharts,HTML,HTML5,HTTP,JasmineJS,JavaScript,Joomla,jQuery,jQueryUI,JSF,KnockoutJS,KoaJS,Laravel,LESS,LeafletJS,Lodash,Next.js,MathML,Magento Framework Material Design Lite,Materialize,MeanJS,Momentjs,Mootools,MVC Framework,Parallax Scrolling,PhantomJS,Phalcon,PHP,PHP-7,Prototype,Polymer,Pure.CSS,Requests,Redux,RichFaces,RIOT.JS,ReactJS,RequireJS RESTful Web Services,Ruby on Rails-2.1,Ruby on Rails,RxJS,SASS,Sencha Touch,script.aculo.us,SVG,Symfony,TurboGears,Typescript,TypeORM,Underscorejs,Vaadin,VBScript,VueJS,W3CSS Web Developer's Guide,Web Icons,Web2Py,WebGL,WebRTC,Web Services,Website Development,Web Sockets,Wordpress,XHTML,Yii,Zend Framework SCRIPTS,JavaScript,jQuery,jQueryUI,Lua,Perl,PHP,PHP-7,Python,Python-3,RSpec,Ruby,Sed,Tcl/Tk,Unix,VBScript,WEB DEVELOPMENT,Adaptive Software Development,Agile Methodology,Agile Data Science,Artificial Intelligence,Computer Programming,Inter Process Communication,C by Examples,Basics of Computers,Basics of Computers Science,Basic Electronics,Behavior Driven Development,Cloud Computing,Compiler Design,Computer Concepts,Computer Fundamentals,Computer Graphics, Computer Logical Organization,Computer Programming,Cryptography,Computer Networking,Data Mining,Data Structure & Algorithms,Design and Analysis of Algorithms,DBMS,Digital Circuits,Digital Image Processing,Discrete Mathematics,Distributed DBMS,Data Warehouse,E-Commerce,Embedded Systems,Estimation Techniques,Extreme Programming,Functional Programming,Graph Theory,HTTP,Human Computer Interface,Information Security and Cyber Law,Internet of Things (IoT),Internet Technologies,IPv4,IPv6,Image Processing with Java,Mgmt Information System,Microprocessor,Mobile Computing,Network Theory,OOAD,Operating System,Parallel Algorithm,Parallel Computer Architecture,Programming Methodologies,SEO Techniques,SOA,SOAP,Software Architecture Design,Software Engineering,S/W Development Life Cycle (SDLC),UDDI,UML, ,Artificial Intelligence with Python,Beautiful Soup,BioPython,Bokeh,Concurrency with Python,Cryptography with Python,Jupyter,Jython,Logistic Regression in Python,Matplotlib,Machine Learning with Python,MongoEngine,Numpy,Object Oriented Python,Peewee,PyGTK,PyQt,PyQt5,Python,Python-3,PyCharm,Python Blockchain,Python Data Access,Python Data Persistence,Python Deep Learning,Python Design Pattern,Python Digital Forensics,Python Web Scraping,Python Data Structure,Python Data Science,Python MongoDB,Python MySQL,Python Pillow,Python PostgreSQL,Python SQLite,Python Network Programming,PyTest,PyTorch,Python Text Processing,Python Forensics,Python Panda,Python Web Development Libraries,PySpark,rxpy,Seaborn,Scipy,Sympy,WxPython,Unix,Android,Aurelia,Cordova,Flutter,Google AMP,Ionic,iOS,iOS Development with Swift2,jQuery Mobile,Kotlin,Mobile Angular UI,Meteor,NativeScript,PhoneGap,React Native,SL4A,XamarinSockets,Apex,Arduino,Assembly,Awk,C Standard Library,Clojure,COBOL,C,C,C Standard Library,C#,Dart,D,Elixir,Elm,Erlang,Euphoria,Fortran,F#,Go Programing,Groovy,Haskell,Java,Java-8,Java Bean Utils,JCL,KDB+,LISP,LOLCODE,LOGO,MATLAB,Node.js,Objective C,OAuth2.0,Pascal,Parrot,CGI with PERL,Prolog,R Programming,Rexx Programming,Rust Programming,Scala,Scala Collection,Socket.io,Solidity,Swift,VB.Net,VBA,WebAssembly,DEVOPS,Ansible,Bugzilla,Chef,Consul,Docker,Gerrit,Git,Gitlab,Jira,Kubernetes,LogStash,Makefile,Mantis,Nagios,OpenShift,Puppet,Saltstack,ServiceNow,Scrapy,SVN,UNIX,Linux Admin,Ubuntu,Virtualization2.0,VersionOne,LATEST TECHNOLOGIES,Ansible,Apache Camel,Apache Flink,Bitcoin,Blockchain,Blue Prism,CloudRail,Docker,Elastic Search,Ethereum,OpenShift,Python Blockchain,Salesforce,TweetDeck,Unity,Virtualization2.0,TELECOM,5G,CDMA,FTTH,GPRS,GSM,i-Mode,LTE,NGN,SIP,Telecom Billing,Telecommunication Switching Systems and Networks (TSSN),UMTS,WAP,Wi-Fi,WiMAX,WML,EXAMS SYLLABUS,Bihar PSC Syllabus,CBSE Syllabus,CDS Syllabus,Chhattisgarh PSC Syllabus,Civil Services Exam Syllabus,GATE Exams Syllabus,IBPS PO Syllabus,Madhya Pradesh PSC Syllabus,NDA Syllabus,Rajasthan PSC Syllabus,SBI PO Syllabus,Uttar Pradesh PSC Syllabus,Agile Testing,Apache Bench,Balsamiq Mockups,Bugzilla,SEI CMMI,Computer Security,Concordion,Continuous Integration,Cucumber,Database Testing,Espresso Testing,Ethical Hacking,ETL Testing,Internet Security,Jenkins,Kali Linux,Malw

【PYTHON OPENCV】Object detection using OpenCV DNN module using YOLO

155
1
0
00:22:10
05.05.2021

Source Code: 🤍 with ❤ by Edward Lance Lorilla Apache CXF,Ajax,Amazon Web Services,Angular Google Charts,Angular High Charts,Angular Material,Angular Material 7,Angular2,Angular4,Angular6,Angular7,Angular8,AngularJS,Angular CLI,Apache Tapestry,ASP.Net,Atomics,Aurelia,Axure RP,AWS Lambda,BabelJS,BabylonJS,BackboneJS,Bootstrap,Ngx Bootstrap,Bootstrap 4,Bulma,CakePHP,CherryPy,Codeigniter,CoffeeScript,CPanel,CSS,CSS Buttons,D3JS,DC.js,Django,Drupal,Electron,EmberJS,ExpressJS,ExtJS,ES6,Firebase,Flask,Adobe Flex,Flexbox,Foundation,Framework7,FuelPHP,GraphQL,Grav,Google Maps,Grunt,Gulp,GWT,GWT Google Charts,GWT High Charts,Highcharts,HTML,HTML5,HTTP,JasmineJS,JavaScript,Joomla,jQuery,jQueryUI,JSF,KnockoutJS,KoaJS,Laravel,LESS,LeafletJS,Lodash,Next.js,MathML,Magento Framework Material Design Lite,Materialize,MeanJS,Momentjs,Mootools,MVC Framework,Parallax Scrolling,PhantomJS,Phalcon,PHP,PHP-7,Prototype,Polymer,Pure.CSS,Requests,Redux,RichFaces,RIOT.JS,ReactJS,RequireJS RESTful Web Services,Ruby on Rails-2.1,Ruby on Rails,RxJS,SASS,Sencha Touch,script.aculo.us,SVG,Symfony,TurboGears,Typescript,TypeORM,Underscorejs,Vaadin,VBScript,VueJS,W3CSS Web Developer's Guide,Web Icons,Web2Py,WebGL,WebRTC,Web Services,Website Development,Web Sockets,Wordpress,XHTML,Yii,Zend Framework SCRIPTS,JavaScript,jQuery,jQueryUI,Lua,Perl,PHP,PHP-7,Python,Python-3,RSpec,Ruby,Sed,Tcl/Tk,Unix,VBScript,WEB DEVELOPMENT,Adaptive Software Development,Agile Methodology,Agile Data Science,Artificial Intelligence,Computer Programming,Inter Process Communication,C by Examples,Basics of Computers,Basics of Computers Science,Basic Electronics,Behavior Driven Development,Cloud Computing,Compiler Design,Computer Concepts,Computer Fundamentals,Computer Graphics, Computer Logical Organization,Computer Programming,Cryptography,Computer Networking,Data Mining,Data Structure & Algorithms,Design and Analysis of Algorithms,DBMS,Digital Circuits,Digital Image Processing,Discrete Mathematics,Distributed DBMS,Data Warehouse,E-Commerce,Embedded Systems,Estimation Techniques,Extreme Programming,Functional Programming,Graph Theory,HTTP,Human Computer Interface,Information Security and Cyber Law,Internet of Things (IoT),Internet Technologies,IPv4,IPv6,Image Processing with Java,Mgmt Information System,Microprocessor,Mobile Computing,Network Theory,OOAD,Operating System,Parallel Algorithm,Parallel Computer Architecture,Programming Methodologies,SEO Techniques,SOA,SOAP,Software Architecture Design,Software Engineering,S/W Development Life Cycle (SDLC),UDDI,UML, ,Artificial Intelligence with Python,Beautiful Soup,BioPython,Bokeh,Concurrency with Python,Cryptography with Python,Jupyter,Jython,Logistic Regression in Python,Matplotlib,Machine Learning with Python,MongoEngine,Numpy,Object Oriented Python,Peewee,PyGTK,PyQt,PyQt5,Python,Python-3,PyCharm,Python Blockchain,Python Data Access,Python Data Persistence,Python Deep Learning,Python Design Pattern,Python Digital Forensics,Python Web Scraping,Python Data Structure,Python Data Science,Python MongoDB,Python MySQL,Python Pillow,Python PostgreSQL,Python SQLite,Python Network Programming,PyTest,PyTorch,Python Text Processing,Python Forensics,Python Panda,Python Web Development Libraries,PySpark,rxpy,Seaborn,Scipy,Sympy,WxPython,Unix,Android,Aurelia,Cordova,Flutter,Google AMP,Ionic,iOS,iOS Development with Swift2,jQuery Mobile,Kotlin,Mobile Angular UI,Meteor,NativeScript,PhoneGap,React Native,SL4A,XamarinSockets,Apex,Arduino,Assembly,Awk,C Standard Library,Clojure,COBOL,C,C,C Standard Library,C#,Dart,D,Elixir,Elm,Erlang,Euphoria,Fortran,F#,Go Programing,Groovy,Haskell,Java,Java-8,Java Bean Utils,JCL,KDB+,LISP,LOLCODE,LOGO,MATLAB,Node.js,Objective C,OAuth2.0,Pascal,Parrot,CGI with PERL,Prolog,R Programming,Rexx Programming,Rust Programming,Scala,Scala Collection,Socket.io,Solidity,Swift,VB.Net,VBA,WebAssembly,DEVOPS,Ansible,Bugzilla,Chef,Consul,Docker,Gerrit,Git,Gitlab,Jira,Kubernetes,LogStash,Makefile,Mantis,Nagios,OpenShift,Puppet,Saltstack,ServiceNow,Scrapy,SVN,UNIX,Linux Admin,Ubuntu,Virtualization2.0,VersionOne,LATEST TECHNOLOGIES,Ansible,Apache Camel,Apache Flink,Bitcoin,Blockchain,Blue Prism,CloudRail,Docker,Elastic Search,Ethereum,OpenShift,Python Blockchain,Salesforce,TweetDeck,Unity,Virtualization2.0,TELECOM,5G,CDMA,FTTH,GPRS,GSM,i-Mode,LTE,NGN,SIP,Telecom Billing,Telecommunication Switching Systems and Networks (TSSN),UMTS,WAP,Wi-Fi,WiMAX,WML,EXAMS SYLLABUS,Bihar PSC Syllabus,CBSE Syllabus,CDS Syllabus,Chhattisgarh PSC Syllabus,Civil Services Exam Syllabus,GATE Exams Syllabus,IBPS PO Syllabus,Madhya Pradesh PSC Syllabus,NDA Syllabus,Rajasthan PSC Syllabus,SBI PO Syllabus,Uttar Pradesh PSC Syllabus,Agile Testing,Apache Bench,Balsamiq Mockups,Bugzilla,SEI CMMI,Computer Security,Concordion,Continuous Integration,Cucumber,Database Testing,Espresso Testing,Ethical Hacking,ETL Testing,Internet Security,Jenkins,Kali Linux,Malw

🐦 Detección de 20 objetos con modelo pre-entrenado usando DNN de OpenCV | Python

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00:14:07
26.09.2022

Hola, hola Omesitos, bienvenidos a un nuevo video mi nombre es Gaby. En este video vamos a usar el módulo de OpenCV DNN, para detectar varios objetos a la vez en una imagen, para ello estaremos usando una red pre entrenada, así que sin más... ¡Vamos a por ello!. CONVIÉRTETE EN MIEMBRO DEL CANAL ❤️: 🤍 👩‍💻 PROGRAMACIÓN AQUÍ: 🤍 VERSIONES USADAS EN ESTE VIDEOTUTORIAL: - Python 3.8.3 - opencv-contrib-python4.6.0 CONTENIDO: 0:00​ - Introducción 0:28 - ¡Vamos con la programación! 💻 1:03 - Instalación de OpenCV 2:22 - Activación del entorno virtual en VS Code 3:03​ - ¡A leer la arquitectura y pesos! 4:33 - Leer imagen de entrada 5:09 - ¡Preprocesamiento - Blob! 7:05 - 👨 ¡A detectar objetos! 👩 10:57 - Detectando objetos en video. LINK ARQUITECTURA Y PESOS: 🔗 🤍 REFERENCIAS: 🔗 🤍 🔗 🤍 🔗 🤍 🔗 🤍 🔗 🤍 MI WEB: 💜👩‍💻 🤍omes-va.com MIS REDES SOCIALES: ☑️INSTAGRAM: 🤍gaby_omes 🔗🤍 ☑️FACEBOOK: 🤍GabyOmes 🔗🤍

OpenCV Webinar 11: Chinese, Optimizing OpenCV DNN for RISC-V

111
5
0
01:06:26
23.11.2021

HAN Liutong, PhD student from Institute of Software, Chinese Academy of Sciences, talks about his work on optimizaing OpenCV DNN module for RISC-V.

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

635
15
14
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 Dnn object detection with YOLO

678
11
3
00:09:45
18.05.2020

สร้างโดย นายธีระพงษ์ เที่่ยงผดุง 🤍

18、Opencv的DNN模块

61
0
0
00:18:12
20.08.2020

Face Detection using DNN - ML4Face-detection Part-4

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15
00:13:06
20.12.2019

#deep learning #machine learning #AI This the second face detector that we'll cover in this series.Nueral networks and resnets are use extensively in almost all detector models. We'll cover: -Implementation of the algorithm -Test the performance on various types of images -Pros and Cons of the algorithm -Best scenarios to use this algorithm Link to ResNets paper and implementation - 🤍 Github repo - 🤍 Subscribe and follow me on other platforms to get updates and exciting content.I generally reply to messages on instagram. Instagram- 🤍 My Youtube Channel - 🤍 Github - 🤍 Twitter - 🤍 LinkedIn - 🤍

OpenCV - DNN

143
0
0
00:04:39
25.08.2019

Bản này nhận dạng tốt hơn cả.

[ OpenCV (python) 最佳中文教程 ] 18.Opencv的DNN模块

198
3
0
00:18:12
02.02.2020

中文Python OpenCV 教程 欢迎支持正版唐宇迪博士课程 🤍 购买正版课程,包含全部课件

Video result for OpenCV DNN Object Detection

205
3
0
00:00:17
20.05.2021

This video shows the result of object detection using the OpenCV DNN module.

Opencv 4 Deep neural network DNN module with Yolo-Tiny2 model

390
1
2
00:01:58
27.11.2018

🤍 I am working on a tutorial and code samples how to use Opencv 4 DNN module with various models trained by tensorflow and yolo, This concrete sample is my run with the camera over the Charles Bridge in Prague. The model is Yolo-Tiny2 (🤍 The FPS is 5 frame per second more or less( 250ms per image ) intel I7 CPU without any magic..

OpenCV DNN C++

330
7
0
00:08:52
11.07.2021

Using OpenCV DNN with a lot of models from Tensorflow, SSD Mobilenet, Mask R-CNN, Caffe, Dlib faces recognization, SVM. All detectors run on parallel threads and detect objects at the same time: + SSD mobilenet: Detects objects like persons, cars, animals... + Tensorflow: Detects faces. + Dlib: Recognizes person's faces. + SVM: Detects the traffic signs. It runs very smooth on Laptop Acer Nitro 5 (Core i7 9750H, GPU card NVIDIA Geforce GTX 1650).

Simple Opencv tutorial for yolo darknet object detection in DNN module

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0
00:17:09
16.04.2020

This tutorial will learn you how to use deep neural networks by Yolo Darknet to detect multiple classes of objects in OpenCV 4+ c. The code is under 100 lines of simple code. The code is using yolov3-tiny.weights of neural network and appropriate configuration yolov3-tiny.cfg loaded by opencv DNN module from contribution library. The code is presented as simple as possible, without the staff nice to have, but not necessary to understand the flow of the code. The step by step tutorial will describe how to load yolo model and evaluate in opencv dnn module up to display the result from neural network processing. You can detect multiple class like persons and more. The full description available here Full code included: 🤍 🤍 Updated news, post on Facebook page 🤍 Latest video yolo darknet opencv 🤍 Opencv tutorials 🤍 follow my Instagram 🤍

OpenCV Webinar 2: Chinese Language. How to speedup DNN at ARM, Tengine in OpenCV. by Mr. Qi LI

322
2
1
00:47:22
28.06.2020

In Chinese Language: Mr. Qi Li, who integrated Tengine with OpenCV, gave an introduction to Tengine, and how to contribute to OpenCV. - 第2期OpenCV Webinar邀请了OpenCV DNN在ARM上加速项目Tengine in OpenCV的项目负责人、OPEN AI LAB高级软件工程师李琦,为大家揭秘本次在端侧推理加速的功臣 - Tengine 推理框架,介绍Tengine是如何与OpenCV结合,本次结合对普通的开发者来说有什么实质意义,以及怎么去用OpenCV中的Tengine实现自己的模型在端侧的推理性能翻翻。

Face Detection DNN

108
1
0
00:00:11
05.04.2019

Open terminal and key in below the command: python face_detection_opencv_dnn.py videos\baby.mp4 source: 🤍

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

298
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3
00:07:58
26.05.2022

This video shows step by step tutorial on how to run yolov4 inference using the opencv-dnn-cuda module on Linux(Ubuntu 18.04). 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 #yolov4onlinux #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-dnn yolo realtime(on windows)

1036
1
0
00:00:22
03.01.2018

i7-2600 GTX1060(6GB) detail→ 🤍

B4A image classification with OpenCV DNN.

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2
00:00:09
15.05.2020

Test OpenCV 3.4.1 wrapper for B4A, with DNN image classification example ported from Java to B4A. Runs quite decent in a Xiaomi Mi A2 Lite.

opencv-dnn yolo realtime(on Ubuntu)

831
1
1
00:00:14
03.01.2018

i7-2600 GTX1060(6GB) detail→ 🤍

Face Detection Using Deep Learning by Code Warriors | OpenCV | DNN | Deep Learning

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00:11:52
11.05.2020

We are welcoming all of you on this tutorial. Recently, I came across the website 🤍 which has some of the greatest tutorials on OpenCV. While reading through its numerous articles, I found that OpenCV has its own Face Detection Neural Network with really high accuracy. So I decided to work on a project using this Neural Network from OpenCV. In this video I’ll discuss: Where this “hidden” deep learning face detector lives in the OpenCV library How you can perform face detection in images using OpenCV and deep learning Project Link - 🤍 Today’s tutorial is broken down into two parts. In the first part we’ll discuss the origin of the more accurate OpenCV face detectors and where they live inside the OpenCV library. From there I’ll demonstrate how you can perform face detection in images using OpenCV and deep learning. However, what most OpenCV users do not know is that Rybnikov has included a more accurate, deep learning-based face detector included in the official release of OpenCV (although it can be a bit hard to find if you don’t know where to look). The Caffe-based face detector can be found in the face_detector sub-directory of the 🤍 When using OpenCV’s deep neural network module with Caffe models, you’ll need two sets of files: The .prototxt file(s) which define the model architecture (i.e., the layers themselves) The .caffemodel file which contains the weights for the actual layers Both files are required when using models trained using Caffe for deep learning. However, you’ll only find the prototxt files here in the GitHub repo. Telegram Channel : 🤍 E-Mail : code.warriors.help🤍gmail.com Instagram Handle : 🤍 LinkedIn Mayank Bajaj : 🤍 Anup Mor : 🤍 Snehal Singh : 🤍 Gaurav Sharma : 🤍 Raj Bhensdadiya : 🤍 Yash Bajaj : 🤍 Paras Gang : 🤍

What is Blob & how to detect the Blobs using Python OpenCV ?

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00:06:46
02.07.2020

This video titled "What is Blob & how to detect the Blobs using Python OpenCV ?" explains what is Blob and how to detect it using Python OpenCV. A blob whose full form is a binary large object. Blobs are generally considered as images, audio, or video data. In computer, vision blob refers to a group of connected pixels or regions in a binary image that shares a common property. These regions are nothing but contours in OpenCV with some extra features like blob/contour orientation, centroid, color, Area, Mean, and standard deviation of the pixel values in the covered region, etc. The term "Large" in binary large objects indicates that only objects of a certain size are of interest and that the other "small" binary objects are usually noise. This is the next video in the Python OpenCV Crash Course. Later on, in the upcoming videos, we will see how can we build face detection, object detection types of Computer Vision Projects. OpenCV Documentation - 🤍 The AI University Website: 🤍theaiuniversity.com Get the "The AI University" Android App on Google Playstore Join this channel to get access to perks: 🤍 Links of Kindle & Machine Learning, Deep Learning & AI Books 1. Kindle 6" Display, 4GB, Wifi - 🤍 2. Introduction to Machine Learning with Python - 🤍 3. Machine Learning: The Absolute Beginner’s Guide to Learn and Understand Machine Learning From Beginners, Intermediate, Advanced, To Expert Concepts - 🤍 4. Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2 - 🤍 5. Hands-On Machine Learning with Scikit-Learn and TensorFlow - 🤍 6. Pattern Recognition and Machine Learning - 🤍 7. Deep Learning with Python - 🤍 8. Deep Learning(Adaptive Computation and Machine Learning series) - 🤍 9. Machine Learning: A Probabilistic Perspective - 🤍 FOLLOW ME ON: Twitter: 🤍 Facebook : 🤍 Instagram: 🤍 Telegram: 🤍 Tool for Keyword Research, Channel Health, Thumbnail Generation for your channel : 🤍 ▶ Check out my gear on Kit: 🤍 ▶ GITHUB REPO : 🤍 About this Channel: The AI University is a channel which is on a mission to democratize the Artificial Intelligence, Big Data Hadoop and Cloud Computing education to the entire world. The aim of this channel is to impart the knowledge to the data science, data analysis, data engineering and cloud architecture aspirants as well as providing advanced knowledge to the ones who already possess some of this knowledge. Please share, comment, like and subscribe if you liked this video. If you have any specific questions then you can comment on the comment section and I'll definitely try to get back to you. *Other AI, ML, Deep Learning, Augmented Reality related Video Series* Deploy Machine Learning Models as Web App using Flask & Docker on Azure Cloud - 🤍 Machine Learning Data Pre-processing & Data Wrangling using Python - 🤍 Machine Learning & Deep Learning Project - 🤍 Machine Learning Projects in HINDI - 🤍 Deep Learning Neural Network Tutorials - 🤍 Machine Learning & Deep Learning Bootcamp Series - 🤍 Machine Learning using Spark MLLib - 🤍 Augmented Reality Free Tutorial - 🤍 Data Engineering Full Hands-on Course - 🤍 Hadoop, Machine & Deep Learning on Azure Cloud Tutorial Series - 🤍 Natural Language Processing - 🤍 Develop Dashboard for Business Intelligence & Data Science(Plotly Dash Tutorial Series) - 🤍 Data Science Tip and Tricks and Career Advice - 🤍 Machine Learning, Deep Learning Maths(Matrix & Vector Operations) - 🤍 DISCLAIMER: This video and description may contain affiliate links, which means that if you click on one of the product links, I’ll receive a small commission. #BlobDetectionOpenCV #OpenCVProject #ComputerVision

YOLO object detection using Opencv with Python

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00:36:56
27.06.2019

Tutorial and source code: 🤍 We’re going to learn in this tutorial YOLO object detection. Yolo is a deep learning algorythm which came out on may 2016 and it became quickly so popular because it’s so fast compared with the previous deep learning algorythm. ➤ Full Videocourses: Object Detection: 🤍 ➤ Follow me on: Instagram: 🤍 LinkedIn: 🤍 ➤ For business inquiries: 🤍

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