Charles Cooper

Charles Cooper

1592084880

How to Install and Run Yolo on the Nvidia Jetson Nano (with GPU)

We’re going to learn in this tutorial how to install and run Yolo on the Nvidia Jetson Nano using its 128 cuda cores gpu.

All the steps described in this blog posts are available on the Video Tutorial, so you can easily watch the video where I show and explain everythin step by step.

Yolo is a really popular DNN (Deep Neural Network) object detection algorythm, which is really fast and works also on not so powerfull devices.

I explained in this post, how to run Yolo on the CPU (so the computer processor) using opencv, and I’m going to explain today how to run Yolo on the GPU (the graphic processor), to get more speed.

How to install YOLO V3?

Before showing the steps to the installation, I want to clarify what is Yolo and what is a Deep Neural Network.

YOLO is an Object Detection algorythm, and it’s the acronym of (You Only Look Once). An object detection algorythm need a DNN (Deep Neural Network) framework to run.

DARKNET is the DNN that was developed to run Yolo. And we’re going to see today how to install Darknet.

Let’s start with the installation.

Update the libraries

sudo apt-get update

Export Cuda path

export PATH=/usr/local/cuda-10.0/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-10.0/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}

Download Darknet and Yolo

git clone https://github.com/AlexeyAB/darknet
cd darknet
wget https://pjreddie.com/media/files/yolov3.weights
wget https://pjreddie.com/media/files/yolov3-tiny.weights

Enable the GPU

We need to Edit the Makefile to enable the GPU, Cuda and Opencv. Let’s edit the Makefile by typing.

sudo vi Makefile

Set the values:

GPU=1

CUDNN=1

OPENCV=1

and the rest leave it as it is.

Compile the Darknet

make

The installation is now completed.

How to run YOLO V3?

You can run Yolo from the Linux terminal.

Once you open the terminal you need first to access the Darknet folder. So just type:

cd darknet

Then you can choose one of the following line, depending of the detection you want to perform.

Image detection:

Edit “dog.jpg” with the path of your image.

./darknet detector test cfg/coco.data yolov3.cfg yolov3.weights -ext_output dog.jpg

Detection from Webcam:

The 0 at the end of the line is the index of the Webcam. So if you have more webcams, you can change the index (with 1, 2, and so on) to use a different webcam.

./darknet detector demo cfg/coco.data cfg/yolov3.cfg yolov3.weights -c 0

Detection from a Videofile:

Edit “test.mp4” with the path of your videofile.

./darknet detector demo cfg/coco.data cfg/yolov3.cfg yolov3.weights -ext_output test.mp4

For more and detailed info, you can check the darknet github page.

#machine-learning #developer

What is GEEK

Buddha Community

How to Install and Run Yolo on the Nvidia Jetson Nano (with GPU)
Melvin Sajith

Melvin Sajith

1641750233

How to install MediaPipe on the Jetson Nano and on all Jetson modules

 How to install MediaPipe on the Jetson Nano and on all Jetson modules - https://youtu.be/RAfkrusLnkM

In this Video I Will show how to install MediaPipe in Nvidia jetson modules and run an example program to make sure that it is working.

The normal way to install mediapipe in Linux is not working. So I have found a way to install mediapipe from source code. This way of installing is a little bit hard but it works very well in the Jetson modules.

#Jetson #nvidia  #python #programming #artificial-intelligence #robotics

Video Link - https://youtu.be/RAfkrusLnkM

 

Servo Node

Servo Node

1621611576

How To Install NVIDIA Graphics Drivers In Linux- Ubuntu/Debian/Fedora

This tutorial is subjected to those who have Linux installed on their desktop and want to install Nvidia graphics driver. Although, most of the newly released Linux distributions come with pre-installed Nvidia drivers, usually in form of Nouveau open-source graphics driver that supports Nvidia graphics cards. Means, if you install a Linux platform, you may require no additional drivers for your graphics card.

But, in case if you are a game lover and want to use as possible from your Nvidia graphics card, then you might need to install official Nvidia drivers for Linux. As already mentioned, most of the Linux platfroms offer proprietary driver package as a part of its standard repository, it’s much easier to install drivers on your desktop.

Alternatively, the users can also seek to download and install latest Nvidia Linux drivers from its official website as well. However, this require users to follow up some hands on measures.

How to install Nvidia graphics driver in Linux?
In order to install Nvidia graphics driver in Linux, you first need to do a number of tasks in prior, that includes:

Checking current VGA driver
Checking Nvidia Linux driver version
Checking current model of Nvidia VGA card
Install NVIDIA Graphics Drivers In Linux

#install nvidia graphics driver in linux #nvidia linux driver install #nvidia linux driver

Yogi Gurjar

1600307091

How to Install Laravel 8 on Windows 10 Xampp

How to install laravel 8 on windows 10. In this tutorial, i would love to share with you how to install laravel 8 on windows 10.

How to Install Laravel 8 on Windows 10 Xampp

Installing laravel 8 on windows 10 xampp server step by step:

  1. Step 1 – Prerequisiteto Install Composer On Windows
  2. Step 2 – Server Requirements For Laravel 8
  3. Step 3 – Installing Laravel On Windows 10 Xampp
  4. Step 4 – Start Development Server For Laravel 8

https://laratutorials.com/installing-laravel-8-on-windows-10-xampp/

#install laravel on windows xampp #how to install laravel in windows 10 xampp #install xampp on windows 10 laravel installation steps #laravel installation steps #how to run laravel project on localhost xampp

Charles Cooper

Charles Cooper

1592084880

How to Install and Run Yolo on the Nvidia Jetson Nano (with GPU)

We’re going to learn in this tutorial how to install and run Yolo on the Nvidia Jetson Nano using its 128 cuda cores gpu.

All the steps described in this blog posts are available on the Video Tutorial, so you can easily watch the video where I show and explain everythin step by step.

Yolo is a really popular DNN (Deep Neural Network) object detection algorythm, which is really fast and works also on not so powerfull devices.

I explained in this post, how to run Yolo on the CPU (so the computer processor) using opencv, and I’m going to explain today how to run Yolo on the GPU (the graphic processor), to get more speed.

How to install YOLO V3?

Before showing the steps to the installation, I want to clarify what is Yolo and what is a Deep Neural Network.

YOLO is an Object Detection algorythm, and it’s the acronym of (You Only Look Once). An object detection algorythm need a DNN (Deep Neural Network) framework to run.

DARKNET is the DNN that was developed to run Yolo. And we’re going to see today how to install Darknet.

Let’s start with the installation.

Update the libraries

sudo apt-get update

Export Cuda path

export PATH=/usr/local/cuda-10.0/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-10.0/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}

Download Darknet and Yolo

git clone https://github.com/AlexeyAB/darknet
cd darknet
wget https://pjreddie.com/media/files/yolov3.weights
wget https://pjreddie.com/media/files/yolov3-tiny.weights

Enable the GPU

We need to Edit the Makefile to enable the GPU, Cuda and Opencv. Let’s edit the Makefile by typing.

sudo vi Makefile

Set the values:

GPU=1

CUDNN=1

OPENCV=1

and the rest leave it as it is.

Compile the Darknet

make

The installation is now completed.

How to run YOLO V3?

You can run Yolo from the Linux terminal.

Once you open the terminal you need first to access the Darknet folder. So just type:

cd darknet

Then you can choose one of the following line, depending of the detection you want to perform.

Image detection:

Edit “dog.jpg” with the path of your image.

./darknet detector test cfg/coco.data yolov3.cfg yolov3.weights -ext_output dog.jpg

Detection from Webcam:

The 0 at the end of the line is the index of the Webcam. So if you have more webcams, you can change the index (with 1, 2, and so on) to use a different webcam.

./darknet detector demo cfg/coco.data cfg/yolov3.cfg yolov3.weights -c 0

Detection from a Videofile:

Edit “test.mp4” with the path of your videofile.

./darknet detector demo cfg/coco.data cfg/yolov3.cfg yolov3.weights -ext_output test.mp4

For more and detailed info, you can check the darknet github page.

#machine-learning #developer

Chet  Lubowitz

Chet Lubowitz

1595855400

How to install PgAdmin 4 on CentOS 8

pgAdmin is the leading graphical Open Source management, development and administration tool for PostgreSQLpgAdmin4 is a rewrite of the popular pgAdmin3 management tool for the PostgreSQL database.

In this tutorial, we are going to show you how to install pgAdmin4 in Server Mode as a web application using httpd and Wsgi module on CentOS 8.

Install pgAdmin4 on CentOS 8

**01-**To install pgAdmin4 on CentOS 8 we need to add an external repository, so execute the following command:

$ sudo rpm -i https://ftp.postgresql.org/pub/pgadmin/pgadmin4/yum/pgadmin4-redhat-repo-1-1.noarch.rpm

02- After we add the pgAdmin4 repository, let’s use the below command to install pgAdmin4 as server mode:

$ sudo dnf install pgadmin4-web

03- Before proceeding with the configuration of pgAdmin4, we need to install policycoreutils tool:

$ dnf install policycoreutils-python-utils  

04- Once we done installing pgAdmin4, we need to configure the pgAdmin4 by setting up the initial pgAdmin user account

#databases #linux #ubuntu #install pgadmin4 #install pgadmin4 centos #pgadmin #pgadmin 4 install #pgadmin 4 install centos #pgadmin4 #pgadmin4 install centos