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zrruziev / coco2yolo.md
Created March 22, 2023 04:45
perfect coco_to_yolo converter...

coco_to_yolo convertor

WARNING ⚠️ /path/to/imgname*.jpg: 1 duplicate labels removed
WARNING ⚠️ /path/to/imgname*.jpg: ignoring corrupt image/label: negative label values [ -0.0069444]
WARNING ⚠️ /path/to/imgname*.jpg: ignoring corrupt image/label: non-normalized or out of bounds coordinates [     1.0104]

When I converted coco_format_labels(json file) to yolo format(*.txt files) by using some libraries from github,\

@zrruziev
zrruziev / yolo_label_correction.md
Last active March 14, 2023 10:27
`yolov5` WARNING ⚠️ : duplicate labels removed; ignoring corrupt image/label: negative label values; ignoring corrupt image/label: non-normalized or out of bounds coordinates

Yolo label correction

While I was training yolov5 with my custom dataset I faced with these WARNINGS ⚠️:

WARNING ⚠️ /path/to/imgname*.jpg: 1 duplicate labels removed
WARNING ⚠️ /path/to/imgname*.jpg: ignoring corrupt image/label: negative label values [ -0.0069444]
WARNING ⚠️ /path/to/imgname*.jpg: ignoring corrupt image/label: non-normalized or out of bounds coordinates [     1.0104]
@zrruziev
zrruziev / daily git commands.md
Last active February 26, 2023 13:22
The easiest, smallest, and best git tutorial!

Step 1: Install Git

If you haven't installed Git already, you can download and install it from the official Git website: https://git-scm.com/downloads

Step 2: Create a new repository

To create a new Git repository, navigate to the directory where you want to store your project and run the following command:

git init
@zrruziev
zrruziev / jupyter_theme.md
Last active February 10, 2023 04:37
Change jupyter themes

Installation

pip install --upgrade jupyterthemes

List all available themes

jt -l
@zrruziev
zrruziev / How to change linux kernel versions.md
Last active January 25, 2023 14:43

Install the specific linux-kernel-version that you want

Check the currently installed kernel version on terminal by running the command

uname -r

Check the available kernel versions to install:




  


  




    


          
    

      

        
        

          

              @zrruziev
          

          

            
                zrruziev
                / NUMA node problem.md
            
            

              Last active
              April 20, 2024 14:04
            

              
                Fixing "successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero" problem
              
          

        

      

        

  

      

    
What is NUMA (Non-Uniformed Memory Access)


Non-Uniform Memory Access (NUMA) is one of the computer memory design methods used in multiprocessor systems, and the time to access the memory varies depending on the relative position between the memory and the processor. In the NUMA architecture, when a processor accesses its local memory, it is faster than when it accesses the remote memory. Remote memory refers to memory that is connected to another processor, and local memory refers to memory that is connected to its own processor.
In other words, it is a technology to increase memory access efficiency while using multiple processors on one motherboard. When a specific processor runs out of memory, it monopolizes the bus by itself, so other processors have to play. , and designate 'access only here', and call it a NUMA node.


1. Check Nodes


lspci | grep -i nvidia
  
01:00.0 VGA compatible controller: NVIDIA Corporation TU106 [GeForce RTX 2060 12GB] (rev a1)



  


  




    


          
    

      

        
        

          

              @zrruziev
          

          

            
                zrruziev
                / Nvidia_CUDA_cuDNN_nvidia-docker2.md
            
            

              Last active
              January 13, 2023 04:26
            

          

        

      

        

  

      

    
Nvidia, CUDA, cuDNN and nvidia-docker2 installation on Ubuntu 22.04.1 LTS


Installation steps of nvidia-driver, CUDA_Toolkit, cuDNN and nvidia-docker2 package which enables docker containers to use host's GPU


1. Check GPU


lspci | grep -i VGA


2. Nvidia Driver installation