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🚨 READ THE ENTIRE README.MD & ALL DOCUMENTS EVERYTHING CAREFULLY !!! 🚨

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🌟 Funding 🌟

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Support the Project ⭐

If you find this project useful, please give it a star! Your support is appreciated and helps keep the project growing.🌟

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Introduction

Welcome to the Assistive AimGuide project!
This tool is designed to enhance accessibility for gamers with physical disabilities by providing advanced AI-driven aiming assistance. It helps to level the playing field, allowing everyone to enjoy competitive and casual gaming environments.

🚨Important🚨: Please ensure you read the following documents before using the tool:

• Readme.md
• License.md
• Code_of_Conduct.md
• Security.md

🚀 Features

• 🎯 Adaptive Aim Assistance: Tailors aiming assistance to the specific needs of gamers with physical disabilities, using YOLOv5 and YOLOv8 detection models.
• 🔫 Precision Control: Allows for fine-tuning of aiming settings to ensure accessibility without overpowering gameplay.
• 🖼️ Customizable Zones: Enables users to define areas on the screen for the tool to assist with, adapting to various game layouts and preferences.
• 💻 Dynamic Performance Adjustment: Manages resolution and processing based on system performance to maintain smooth gameplay.
• 🤖 Arduino Leonardo (RECOMMENDED): Integrates with Arduino for additional customization and hardware-based controls.

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Discord Support

Join our Discord channel Assistive AimGuide for assistance, support, or to share your experience.

• Discord Link
• or Join to Support Fnbubbles420 Org & The Mission.
• Our community is growing be apart of something BIG!!

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🚨 Disclaimer

This tool is developed as an accessibility aid for gamers with disabilities to help them compete more effectively in games.
We advocate for fair play and accessibility in gaming and do not endorse cheating or the promotion of cheating in any form.
Use of this tool in online games is at your own risk. Please consult with game developers if unsure about compatibility with game policies.
This tool should be used primarily as an assistive device in environments that support inclusivity.

• PLEASE READ IMPORTANT

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Bubbles Advanced AI Anti Cheat Engine

BAAACE

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🌟 About Us

At FNBubbles420 Org, we are dedicated to supporting disabled gamers, developers, veterans, and streamers through various initiatives. One of our primary programs is Game Vision Aid, which aims to enhance accessibility and performance for gamers with visual impairments.

Game Vision Aid is coming soon — we are still testing and developing it to ensure it meets the highest standards for accessibility.

While the Assistive AimGuide is a separate project, it embodies our organization's dedication to leveraging innovative technologies to enhance accessibility and equality in gaming for those with disabilities. This commitment underlines our ongoing efforts to serve and uplift the community.

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💬 Words to Live By

"Life is a journey best traveled together; when we lift each other up, we rise as a community, stronger and more united. Every small act of kindness creates ripples that can change the world."
– Bubbles

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To learn more about what drives us, visit our Mission Page.
If you'd like to get involved or learn more about volunteering, visit our Volunteer Page.

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📥 How to Download the Repo (First-Time Users)

Click the link to read Instructions 📄.

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For AMD GPU SUPPORT click here

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Supported Languages on Readme.md

1. Nvidia

• Nvidia_Supported_Languages

2. AMD

• AMD_Supported_Languages

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• update_ultralytics.bat ALWAYS CHECK FOR UPDATES COUPLE TIME EVERY FEW WEEKS !!

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🛠 Requirements

To run the bot, ensure the following dependencies are installed:

• Python 3.11.6 – The required Python version for compatibility.
• OpenCV – For handling image capture and processing (pip install opencv-python).
• PyTorch – For deep learning and model inference (pip install torch).
• Cupy – For utilizing CUDA-based GPU acceleration (pip install cupy-cuda11x).
• BetterCam – For capturing and processing live game frames. Enhanced Advanced
• Comtypes – For interacting with the Windows API (pip install comtypes).

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LICENSE

This project is proprietary and all rights are reserved by the author.

Unauthorized copying, distribution, or modification of this project is strictly prohibited.

Unless You have written permission from the Developer or the FNBUBBLES420 ORG.

🛠️ Tested Environment

The project has been successfully tested on the following setup:

• Processor: Intel(R) Core(TM) i7-14700F @ 2.10 GHz
• GPU: NVIDIA GeForce RTX 4060 Ti
• Operating System: Windows 11
• Python Version: 3.11.6

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• Processor: AMD Ryzen 9 7900X 12-Core Processor @ 4.70 GHz
• GPU: DUEL GPU: "NVIDIA GeForce RTX 4060 Ti" "AMD Radeon"
• Operating System: Windows 11
• Python Version: 3.11.6

Works On

• Nvidia GPU
• AMD GPU
• CPU
• Multiple Monitor Support
• Mobile support

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File Structure

.
├── .github/                           # GitHub configuration files
├── Easy_Setup                         # Nvidia Easy Setup / Read, Follow Instructions in Terminal read the readme.md
├── Environtmental_Setup               # How The Environmental Variables The Correct Order
├── Supported_Languages                # Readme.md Supported Languages
├── banner/                            # Placeholder for banner or notice files
├── main_amd_scripts/                  # AMD_GPU - related script folder
│   └── dist/                          # Distribution files for ONNX script
│       ├── imgs/                      # Contains images used in the project
│       ├── models/                    # Contains ONNX model files
│       ├── pyarmor_runtime_000000/    # PyArmor runtime files for ONNX script (runtime for ONNX)
│       ├── pyarmor_runtime_0000001/   # Additional PyArmor runtime files for ONNX script
│       ├── ultralytics1/utils/        # Utility scripts from Ultralytics
│       ├── utils/                     # General utility scripts
│       ├── amd_requirements.txt       # Install Dependencies
│       ├── butter-scotch-cookies.txt  # Export Commands for models
│       ├── config-launcher.bat        # configuration launcher opens up in notepad
│       ├── config.py                  # Configuration file for ONNX script
│       ├── export.py                  # Python export script
│       ├── gameSelection.py           # Obfuscated game selection logic script
│       ├── launcher.bat               # Launcher for Main AMD
│       ├── main_amd.py                # Main AMD script
│       ├── readme.md                  # Main Readme.md for AMD SUPPORT
│       ├── readme2.md                 # Placing Pt Files
│       └── run-2.bat                  # Batch script to run the project FOR AMD GPUS
├── main_cpu_script/                   # CPU-related script folder
│   └── dist/                          # Distribution files for CPU script
│       ├── imgs/                      # Contains images used in the project
│       ├── models/                    # Contains PyTorch model files
│       ├── pyarmor_runtime_000000/    # PyArmor runtime files for CPU script
│       ├── pyarmor_runtime_0000001/   # Additional PyArmor runtime files for CPU script
│       ├── ultralytics1/utils/        # Utility scripts from Ultralytics
│       ├── utils/                     # General utility scripts
│       ├── butter-scotch-cookies.txt  # Export Commands for models
│       ├── config-launcher.bat        # configuration launcher opens up in notepad
│       ├── config.py                  # Configuration file for CPU script
│       ├── gameSelection.py           # Obfuscated game selection logic script
│       ├── launcher.bat               # Launcher for Main CPU
│       ├── main_cpu.py                # Main CPU script
│       ├── requirements.txt           # Dependencies for CPU script
│       └── readme.md                  # Placing Pt Files
├── main_onnx_script/                  # ONNX-related script folder
│   └── dist/                          # Distribution files for ONNX script
│       ├── imgs/                      # Contains images used in the project
│       ├── models/                    # Contains ONNX model files
│       ├── pyarmor_runtime_000000/    # PyArmor runtime files for ONNX script (runtime for ONNX)
│       ├── pyarmor_runtime_0000001/   # Additional PyArmor runtime files for ONNX script
│       ├── ultralytics1/utils/        # Utility scripts from Ultralytics
│       ├── utils/                     # General utility scripts
│       ├── butter-scotch-cookies.txt  # Export Commands for models
│       ├── config-launcher.bat        # configuration launcher opens up in notepad
│       ├── config.py                  # Configuration file for ONNX script
│       ├── export.py                  # Python export script
│       ├── gameSelection.py           # Obfuscated game selection logic script
│       ├── launcher.bat               # Launcher for Main ONNX
│       └── main_onnx.py               # Main ONNX script
│       └── readme.md                  # Placing Pt Files
├── main_tensorrt_script/              # TensorRT-related script folder
│   └── dist/                          # Distribution files for TensorRT script
│       ├── imgs/                      # Contains images used in the project
│       ├── models/                    # Contains TensorRT model files
│       ├── pyarmor_runtime_000000/    # PyArmor runtime files for TensorRT script (runtime for TensorRT)
│       ├── pyarmor_runtime_0000001/   # Additional PyArmor runtime files for TensorRT script
│       ├── ultralytics1/utils/        # Utility scripts from Ultralytics
│       ├── utils/                     # General utility scripts
│       ├── butter-scotch-cookies.txt  # Export Commands for models
│       ├── config-launcher.bat        # configuration launcher opens up in notepad
│       ├── config.py                  # Configuration file for TensorRT script
│       ├── export.py                  # Python export script
│       ├── gameSelection.py           # Obfuscated game selection logic script
│       ├── launcher.bat               # Launcher for Main TensorRT 
│       └── main_tensorrt.py           # Main TensorRT script
│       └── readme.md                  # Placing Pt Files
├── pt_models                          # PT MODELS
├── ADDITION.MD                        # Addition.md Creator Developer Join Our Discord Support The Mission
├── CODE_OF_CONDUCT.md                 # Code of conduct for the project
├── LICENSE.MD                         # Project license file
├── PLEASE-READ-IMPORTANT.md           # VERY IMPORTANT MD _ PLEASE-READ-IMPORTANT.md 
├── SECURITY.md                        # Security policy for the project
├── cudnn_instructions.js              # Instructions related to cuDNN
├── get_device.py                      # Lets you know if you installed CUDA
├── gitattributes                      # Git attributes for handling line endings
├── gitignore                          # Git ignore rules for excluding certain files
├── install_python.bat                 # Batch script to install Python 3.11.6
├── install_pytorch.bat                # NEWEST VERSION OF PYTORCH (Nvidia)
├── nodejs-instructions.ps1            # PowerShell script for Node.js instructions
├── readme.md                          # Project README file
├── nvidia_requirements.txt            # Python dependencies for the project
├── run.bat                            # Batch script to run the project
├── update_ultralytics.bat             # Batch script to update Ultralytics

CPU-Setup

AMD-Setup

🛠 Installation

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Installation and Running Instructions

Prerequisites

• Ensure Node.js is installed on your system. You can download it from Node.js v22.12.0 (Windows 64-bit).
  • During installation, if prompted, select "Add to PATH" by clicking Yes.

Installation Steps

1. Install Node.js Dependencies Navigate to the repository folder on your PC using the terminal and run:

npm install

Running the JavaScript Script

• Run the Application Once the dependencies are installed, run the JavaScript file using:

node cudnn-instructions.js

• Expected Output The script will provide instructions for downloading and installing cuDNN and related components for your system.

Additional Notes

• Make sure you are using Node.js v20.17.0 or later.
• Ensure that Node.js was added to your system's PATH during installation.

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How to Run the PowerShell Script (nodejs-instructions.ps1)

Step-by-Step Instructions:

1. Save the Script:

   • Save the PowerShell script as nodejs-instructions.ps1 in the desired directory.

2. Open PowerShell:

• Open PowerShell by searching for it in the Start Menu or pressing Win + X and selecting PowerShell.

3. Set Execution Policy (If Needed):

• If this is your first time running a PowerShell script, you may need to allow script execution. Run this command:

Set-ExecutionPolicy RemoteSigned -Scope CurrentUser

• This will allow scripts that are locally created to run while ensuring scripts from external sources must be signed.
• MAKE SURE TO TYPE YES OR Y IN THE FOR THE RESPONSE TO CONTINUE

4. Navigate to the Script Directory:

• Use the cd command to navigate to the folder where nodejs-instructions.ps1 is located. For example:

cd C:\Users\YourUsername\Desktop\Scripts

5. Run the Script:

• To run the script, type the following command:

./nodejs-instructions.ps1

6. Follow the Instructions:

• The script will guide you through the steps to install and verify Node.js, update npm, and run your JavaScript files.

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Key Additions:

• Mentioned selecting LTS for stability.
• Added a note about installing additional tools ( DO NOT INSTALL ANY ADDITIONAL TOOLS FROM NODE.JS )
• Included a step to update npm globally.
• Provided an example for the cd command to improve clarity.
• Added instructions on how to install project dependencies using npm install.
• Added clear instructions on how to run the nodejs-instructions.ps1 PowerShell script, including enabling script execution.

---

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2. Install dependencies: Ensure you have Python and pip installed. Then run:

pip install -r nvidia_requirements.txt

3. Configure settings:

Open the config.py file and adjust the following settings according to your preferences:

• screenShotHeight and screenShotWidth: Define the portion of the screen to be captured around the center.
• useMask, maskSide, maskWidth, and maskHeight: Set these to mask parts of the screen where a model or object might interfere (useful in third-person games or for large weapons).
• aaMovementAmp: Controls how smooth the aim is. Adjust based on your preference and game type.
• aaQuitKey: Default is 8, press this key to quit and shut down the auto-aim.
• aaActivateKey = CapsLock, press to toggle the autoaim
• confidence: Adjust detection confidence level for the target (default is 0.4).
• headshot_mode: Set to True to aim slightly upwards towards the head.
• cpsDisplay: Set to True if you want to display corrections per second in the terminal (for debugging purposes).
• visuals: Set to True to display what the bot "sees" (bounding boxes, etc.).
• centerOfScreen: Prioritize targets near the center of the screen for smarter target selection.
• onnxChoice: Choose between 2 (AMD for nvidia), or 3 (NVIDIA) when using ONNX models.
• model_path: Uncomment the correct path based on whether you're using a TensorRT engine or ONNX model.
  • Use v5.engine for TensorRT.
  • Use v5.onnx for ONNX.
• device: Set to 'cpu' or 'cuda' depending on whether you're running on CPU or GPU.
• fp16: Set to True to use FP16 for faster inference on supported GPUs.

4. Run the Bot:

After configuring the bot, navigate to the respective folder and start it by running:

• For the TensorRT bot, navigate to the main_tensorrt_script/dist/ folder and run:

cd main_tensorrt_script/dist/
python main_tensorrt.py

• For the ONNX bot, navigate to the main_onnx_script/dist/ folder and run:

cd main_onnx_script/dist/
python main_onnx.py

Usage Instructions

Activation

• Start/Stop: Use the Caps Lock key to toggle the bot on and off based on your game settings.

Adjustments

• Aim Adjustment: The bot automatically detects targets and prioritizes those near the center of the screen. It adjusts the aim smoothly. Adjust aim behavior through aaMovementAmp and other settings in config.py.
• Speed Values for Aim Adjustment:
  • Slow: 0.2 - 0.4
  • Medium: 0.5 - 0.7
  • Fast: 0.8 - 1.0
  • Very Fast: 1.1 - 1.5+

Special Modes

• Headshot Mode: Enable this mode to make the bot aim slightly upwards to target heads by setting headshot_mode to True.

Quitting

• Exit: Press the '8' key to stop and exit the bot.

🔧 Configuration Options

Modify settings in the config.py file to customize bot behavior:

• Auto Aim Movement: Change the aaMovementAmp value to control how smoothly the bot adjusts aim.
• Headshot Mode: Toggle headshot prioritization with headshot_mode.
• Screen Resolution: Adjust the aim area using screenShotWidth and screenShotHeight.
• Masking: Configure useMask, maskSide, maskWidth, and maskHeight to ignore certain screen areas.
• Quit Key: Set aaQuitKey to customize the key used to quit the bot (default is 8).
• Activation Key: Use Caps Lock to toggle the bot on/off.
• Confidence Level: Adjust the target detection confidence using the confidence setting.
• Visual Feedback: Enable visual overlays with visuals to see what the bot detects.
• Center Targeting: Use centerOfScreen to prioritize center-screen targets.
• ONNX Provider: Choose between AMD or NVIDIA execution with onnxChoice.
• Model Path: Specify the model file path in model_path, supporting .engine or .onnx.
• Device: Set execution to 'cpu' or 'cuda' with device.
• FP16 Mode: Enable fp16 for faster processing on compatible GPUs.

🚨 Legal and Compliance

• This tool is intended for educational and accessibility purposes within environments that support inclusivity.
• We do not endorse or promote cheating. Use of this tool in violation of game terms may result in bans or penalties.
• For any concerns about compatibility with game policies, consult game developers.

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🚀 NVIDIA CUDA Installation Guide

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DO EVERY STEP AND FOLLOW EVERY STEP OF THE NVIDIA INSTALLATION GUIDE OR IT WON'T WORK PROPERLY

• FOR AMD USERS MAKE SURE YOU FOLLOW THE GUIDE FOR AMD GPUS

For AMD GPU SUPPORT click here

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1. Download the NVIDIA CUDA Toolkit 11.8

First, download the CUDA Toolkit 11.8 from the official NVIDIA website:

👉 Nvidia CUDA Toolkit 11.8 - DOWNLOAD HERE

2. Install the CUDA Toolkit

• After downloading, open the installer (.exe) and follow the instructions provided by the installer.
• Make sure to select the following components during installation:
  • CUDA Toolkit
  • CUDA Samples
  • CUDA Documentation (optional)

3. Verify the Installation

• After the installation completes, open the cmd.exe terminal and run the following command to ensure that CUDA has been installed correctly:

nvcc --version

This will display the installed CUDA version.

4. Install Cupy

Run the following command in your terminal to install Cupy:

pip install cupy-cuda11x

5. CUDNN Installation 🧩

Download cuDNN (CUDA Deep Neural Network library) from the NVIDIA website:

👉 Download CUDNN. (Requires an NVIDIA account – it's free).

6. Unzip and Relocate 📁➡️

Open the .zip cuDNN file and move all the folders/files to the location where the CUDA Toolkit is installed on your machine, typically:

C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8

7. Get TensorRT 8.6 GA 🔽

Download TensorRT 8.6 GA.

8. Unzip and Relocate 📁➡️

Open the .zip TensorRT file and move all the folders/files to the CUDA Toolkit folder, typically located at:

C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8

9. Python TensorRT Installation 🎡

Once all the files are copied, run the following command to install TensorRT for Python:

pip install "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\python\tensorrt-8.6.1-cp311-none-win_amd64.whl"

🚨 Note: If this step doesn’t work, double-check that the .whl file matches your Python version (e.g., cp311 is for Python 3.11). Just locate the correct .whl file in the python folder and replace the path accordingly.

10. Set Your Environment Variables 🌎

Add the following paths to your environment variables:

• system path

C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\lib
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\libnvvp
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\bin

Setting Up CUDA 11.8 with cuDNN on Windows

Once you have CUDA 11.8 installed and cuDNN properly configured, you need to set up your environment via cmd.exe to ensure that the system uses the correct version of CUDA (especially if multiple CUDA versions are installed).

Steps to Set Up CUDA 11.8 Using cmd.exe

1. Set the CUDA Path in cmd.exe

You need to add the CUDA 11.8 binaries to the environment variables in the current cmd.exe session.

Open cmd.exe and run the following commands:

• DO each one Separately

set PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\bin;%PATH%
set PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\libnvvp;%PATH%
set PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\extras\CUPTI\lib64;%PATH%

These commands add the CUDA 11.8 binary, lib, and CUPTI paths to your system's current session. Adjust the paths as necessary depending on your installation directory.

2. Verify the CUDA Version After setting the paths, you can verify that your system is using CUDA 11.8 by running:

nvcc --version

This should display the details of CUDA 11.8. If it shows a different version, check the paths and ensure the proper version is set.

3. Set the Environment Variables for a Persistent Session If you want to ensure CUDA 11.8 is used every time you open cmd.exe, you can add these paths to your system environment variables permanently:

4. Open Control Panel -> System -> Advanced System Settings. Click on Environment Variables. Under System variables, select Path and click Edit. Add the following entries at the top of the list:

C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\bin
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\libnvvp
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\extras\CUPTI\lib64

This ensures that CUDA 11.8 is prioritized when running CUDA applications, even on systems with multiple CUDA versions.

4. Set CUDA Environment Variables for cuDNN If you're using cuDNN, ensure the cudnn64_8.dll is also in your system path:

set PATH=C:\tools\cuda\bin;%PATH%

This should properly set up CUDA 11.8 to be used for your projects via cmd.exe.

Additional Information

• Ensure that your GPU drivers are up to date.
• You can check CUDA compatibility with other software (e.g., PyTorch or TensorFlow) by referring to their documentation for specific versions supported by CUDA 11.8.

Environmental Variable Setup

import torch

print(torch.cuda.is_available())  # This will return True if CUDA is available
print(torch.version.cuda)  # This will print the CUDA version being used
print(torch.cuda.get_device_name(0))  # This will print the name of the GPU, e.g., 'NVIDIA GeForce RTX GPU Model'

run the get_device.py to see if you installed it correctly

🛠 Run Script run.bat

The run.bat script is a batch file to help you install all the required dependencies for this project. Below is the content of the file and the steps it will execute:

@echo off
echo Installing ONNX Runtime (GPU)...
pip install onnxruntime-gpu
echo Press enter to continue with the rest of the dependency installs
pause

echo Installing NumPy...
pip install numpy
echo Press enter to continue with the rest of the dependency installs
pause

echo Installing comtypes...
pip install comtypes
echo Press enter to continue with the rest of the dependency installs
pause

echo Installing OpenCV (opencv-python)...
pip install opencv-python
echo Press enter to continue with the rest of the dependency installs
pause

echo Installing pandas...
pip install pandas
echo Press enter to continue with the rest of the dependency installs
pause

echo Installing bettercam...
pip install bettercam
echo Press enter to continue with the rest of the dependency installs
pause

echo Installing onnx...
pip install onnx
echo Press enter to continue with the rest of the dependency installs
pause

echo Installing PyWin32...
pip install pywin32
echo Press enter to continue with the rest of the dependency installs
pause

echo Installing Dill...
pip install dill
echo Press enter to continue with the rest of the dependency installs
pause

echo Installing CuPy (GPU accelerated array library for CUDA 11.8)...
pip install cupy-cuda11x
echo Press enter to continue with the rest of the dependency installs
pause

echo Installing psutil...
pip install psutil
echo Press enter to continue with the rest of the dependency installs
pause

echo Installing colorama...
pip install colorama
echo Press enter to continue with the rest of the dependency installs
pause

echo Installing ultralytics...
pip install ultralytics
echo Press enter to continue with the rest of the dependency installs
pause

echo Installing PyAutoGUI...
pip install PyAutoGUI
echo Press enter to continue with the rest of the dependency installs
pause

echo Installing PyGetWindow...
pip install PyGetWindow
echo Press enter to continue with the rest of the dependency installs
pause

echo Installing pyyaml...
pip install pyyaml
echo Press enter to continue with the rest of the dependency installs
pause

echo Installing tqdm...
pip install tqdm
echo Press enter to continue with the rest of the dependency installs
pause

echo Installing matplotlib...
pip install matplotlib
echo Press enter to continue with the rest of the dependency installs
pause

echo Installing seaborn...
pip install seaborn
echo Press enter to continue with the rest of the dependency installs
pause

echo Installing requests...
pip install requests
echo Press enter to continue with the rest of the dependency installs
pause

echo Installing ipython...
pip install ipython
echo Press enter to continue with the rest of the dependency installs
pause

echo Installing dxcam...
pip install dxcam
echo Press enter to continue with the rest of the dependency installs
pause

echo Installing pyarmor...
pip install pyarmor
echo Press enter to continue with the rest of the dependency installs
pause

echo Installing serial...
pip install serial
echo Press enter to continue with the rest of the dependency installs
pause

echo Installing onnx-simplifier...
pip install onnx-simplifier
echo Press enter to continue with the rest of the dependency installs
pause

echo Installing onnxruntime...
pip install onnxruntime
echo Press enter to continue with the rest of the dependency installs
pause

echo MAKE SURE TO HAVE THE WHL DOWNLOADED BEFORE YOU CONTINUE!!!
pause
echo Click the link to download the WHL: press ctrl then left click with mouse
echo https://github.com/cupy/cupy/releases/download/v13.3.0/cupy_cuda11x-13.3.0-cp311-cp311-win_amd64.whl
pause

echo Installing CuPy from WHL...
pip install https://github.com/cupy/cupy/releases/download/v13.3.0/cupy_cuda11x-13.3.0-cp311-cp311-win_amd64.whl
pause

echo All packages installed successfully!
pause

How to Use the run.bat Script

1. Download the Required Files:

   • Ensure you have downloaded the WHL file for CuPy from the following link: Download CuPy WHL

2. Run the Batch File:

   • Execute the run.bat file to automatically install all necessary Python dependencies for this project.

   • The script will pause after each step so you can verify the installation. Simply press any key to continue after each pause.

   To execute the batch file, you can use:

   ./run.bat
   

🚀 Visual Studio 2022 Community Edition Installation Guide

This guide will help you download and install Visual Studio 2022 Community Edition with the Desktop Development with C++ workload for C and C++ development.

📥 Step 1: Download Visual Studio

Click the following link to download Visual Studio 2022 Community Edition:
👉 Download Visual Studio 2022 Community Edition

🛠 Step 2: Installing Visual Studio

1. Once the installer is downloaded, run the installer.
2. In the Visual Studio Installer, select the Workloads tab.

🖥 Step 3: Select Workload for C++ Development

To set up C++ development, ensure you select the Desktop development with C++ workload:

1. In the Workloads tab, check the option Desktop development with C++.
   • This will install the necessary tools for C++ programming, including compilers, libraries, and debugging tools.
2. Click Install to begin the installation process.

🛠 System Requirements Visual Studio 2022

Make sure your system meets the minimum requirements for Visual Studio 2022:

• OS: Windows 10 or higher.
• Processor: Quad-core processor or better.
• RAM: 8 GB of RAM (16 GB recommended).
• Disk Space: Minimum 20 GB free space.

🛑 Troubleshooting

If you encounter any issues during installation, refer to the official troubleshooting guide:

• Visual Studio Installation Troubleshooting

Now you're ready to start developing C and C++ applications in Visual Studio 2022! 🎉

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