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--- |
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license: apache-2.0 |
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language: |
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- en |
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tags: |
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- image-processing |
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- deep-learning |
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- AI |
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--- |
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--- |
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# IMageDucHaiten |
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**Version:** `V1.1.2` |
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## Table of Contents |
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- [Recent Updates](#recent-updates) |
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- [Introduction](#introduction) |
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- [Key Features](#key-features) |
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- [Installation](#installation) |
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- [Option 1: Full Package Installation via Direct Download](#option-1-full-package-installation-via-direct-download) |
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- [Option 2: Full Package Installation via Git Clone](#option-2-full-package-installation-via-git-clone) |
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- [Option 3: Manual Installation by Downloading Individual Files](#option-3-manual-installation-by-downloading-individual-files) |
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- [Usage](#usage) |
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- [Running the Application via Command Line (CMD)](#running-the-application-via-command-line-cmd) |
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- [Running the Application via Visual Studio Code](#running-the-application-via-visual-studio-code) |
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- [Installing Visual Studio Code](#installing-visual-studio-code) |
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- [Community and Support](#community-and-support) |
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- [Support and Contributions](#support-and-contributions) |
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## Recent Updates |
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### Version V1.1.2 |
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Version `V1.1.2` introduces significant optimizations and new features, especially in the **Image To Caption** module. The key enhancements include: |
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- **Added Bit Precision Options**: Users can now select between different bit precision levels when processing images: |
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- **4-bit**: Requires at least 20GB RAM and 12GB VRAM. |
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- **8-bit**: Requires at least 20GB RAM and 16GB VRAM. |
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- **16-bit**: Requires at least 50GB RAM and 24GB VRAM. |
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- **32-bit**: Although the previous version required 40GB VRAM for 32-bit float32, this update optimizes it to run even with 24GB VRAM, though at significantly reduced speeds. This lower VRAM option is not recommended for performance-critical tasks. |
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> **NOTE**: Although optimization has been made to allow GPUs with lower VRAM to run at higher bit precision, the speed will be significantly reduced. |
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## Introduction |
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**IMageDucHaiten** is a powerful tool specifically designed for AI professionals to assist in the preparation of image data for training generative AI models. Version `V1.1.2` offers a suite of automated and flexible tools for processing, tagging, and captioning images, making the data preparation process more efficient and streamlined. |
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Whether you're an AI researcher, data engineer, or someone who enjoys working with images, **IMageDucHaiten** can be an invaluable tool. It not only excels in supporting AI data preparation but is also accessible and beneficial to anyone looking to work with images effortlessly and effectively. |
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## Key Features |
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- **Image Converter**: Convert image formats to match the requirements of your AI model, supporting a wide range of formats such as PNG, JPG, GIF, BMP, and more. |
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- **Image Filter**: Filter and remove images that do not meet quality criteria such as size and resolution, ensuring a clean dataset for training. |
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- **Rotate & Flip**: Rotate and flip images to create various training data variations, enhancing dataset diversity. |
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- **Image Error Fix**: Automatically detect and fix errors in images, reducing the risk of using incomplete data. |
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- **Image To Tag**: Automatically tag images, optimizing the data labeling process for AI models. |
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- **Image To Caption**: Automatically generate captions, providing context to images, useful in image recognition and captioning tasks. |
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- **Photo Fantasy**: Create artistic effects on images, useful for data augmentation or enhancing creative content. |
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## Installation |
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To install and set up **IMageDucHaiten**, you have three options: |
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### Option 1: Full Package Installation via Direct Download |
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1. **Download the Full Package**: |
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- Download the full package from the following link: |
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[IMageDucHaiten-Full.zip](https://huggingface.co/DucHaiten/IMageDucHaiten-Full/tree/main) |
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2. **Extract the Package**: |
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- Extract the contents of the `.zip` file to your desired location. |
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3. **Install Visual Studio Code (if not installed)**: |
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- Download and install Visual Studio Code from [here](https://code.visualstudio.com/). |
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4. **Activate the Virtual Environment**: |
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- Open the extracted folder in Visual Studio Code by selecting `File > Open Folder` and navigating to the extracted folder. |
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- Open the integrated terminal within Visual Studio Code by selecting `View > Terminal`. |
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- Activate the pre-configured virtual environment: |
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- On **Windows**: |
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```bash |
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.\venv\Scripts\activate |
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``` |
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- On **macOS/Linux**: |
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```bash |
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source venv/bin/activate |
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``` |
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5. **Run the Application**: |
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- After activating the virtual environment, you can start the application by running: |
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```bashF |
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python main.py |
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``` |
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### Option 2: Full Package Installation via Git Clone |
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1. **Install Git and Git LFS**: |
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- Ensure Git is installed on your system. If not, download and install it from [Git's official site](https://git-scm.com/downloads) and [Git lfs](https://git-lfs.com/) |
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- Install Git LFS (Large File Storage) by running: |
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```bash |
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git lfs install |
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``` |
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2. **Clone the Repository**: |
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- Use Git to clone the repository with all necessary files: |
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```bash |
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git clone https://huggingface.co/DucHaiten/IMageDucHaiten |
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``` |
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3. **Open the Project in Visual Studio Code**: |
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- If you haven't installed Visual Studio Code, download and install it from [here](https://code.visualstudio.com/). |
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- Open Visual Studio Code, then select `File > Open Folder` and navigate to the cloned folder. |
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4. **Activate the Virtual Environment**: |
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- Open the integrated terminal by selecting `View > Terminal`. |
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- Activate the virtual environment: |
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- On **Windows**: |
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```bash |
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.\venv\Scripts\activate |
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``` |
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- On **macOS/Linux**: |
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```bash |
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source venv/bin/activate |
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``` |
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5. **Run the Application**: |
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- Start the application by running: |
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```bash |
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python main.py |
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``` |
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### Option 3: Manual Installation by Downloading Individual Files |
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1. **Download the Files Manually**: |
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- Download individual files and directories from the repository as needed. |
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2. **Set up a Virtual Environment**: |
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- Create and activate a virtual environment: |
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- On **Windows**: |
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```bash |
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python -m venv venv |
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.\venv\Scripts\activate |
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``` |
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- On **macOS/Linux**: |
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```bash |
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python3 -m venv venv |
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source venv/bin/activate |
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``` |
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3. **Install Python Dependencies**: |
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- Install the required Python packages using `requirements.txt`: |
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```bash |
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pip install -r requirements.txt |
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``` |
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4. **Install External Dependencies** (Ghostscript, ImageMagick, Visual C++ Redistributable): |
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- Follow the instructions provided earlier to ensure all dependencies are properly installed. |
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5. **Open the Project in Visual Studio Code**: |
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- If you haven't installed Visual Studio Code, download and install it from [here](https://code.visualstudio.com/). |
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- Open Visual Studio Code, then select `File > Open Folder` and navigate to the project folder. |
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6. **Run the Application**: |
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- Open the integrated terminal by selecting `View > Terminal`. |
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- Activate the virtual environment, then start the application by running: |
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```bash |
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python main.py |
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``` |
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## Usage |
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After completing the installation, you can run **IMageDucHaiten** as follows: |
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### Running the Application via Command Line (CMD) |
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1. **Activate the Virtual Environment**: |
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- On **Windows**: |
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```bash |
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.\venv\Scripts\activate |
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``` |
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- On **macOS/Linux**: |
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```bash |
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source venv/bin/activate |
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``` |
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2. **Run the Application**: |
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- In the terminal, navigate to the folder where `main.py` is located. |
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- Execute the following command to start the application: |
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```bash |
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python main.py |
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``` |
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### Running the Application via Visual Studio Code |
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1. **Open the Project in Visual Studio Code**: |
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- Launch Visual Studio Code. |
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- Open the project folder by selecting `File > Open Folder` and navigating to the folder where `main.py` is located. |
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2. **Activate the Virtual Environment**: |
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- Open the integrated terminal within Visual Studio Code by selecting `View > Terminal`. |
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- Activate the virtual environment: |
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- On **Windows**: |
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```bash |
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.\venv\Scripts\activate |
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``` |
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- On **macOS/Linux**: |
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```bash |
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source venv/bin/activate |
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``` |
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3. **Run the Application**: |
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- In the terminal, start the application by running: |
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```bash |
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python main.py |
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``` |
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- Alternatively, you can press **F5** to run the application with debugging. |
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### Installing Visual Studio Code |
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If you don't have Visual Studio Code installed, follow these steps: |
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1. **Download Visual Studio Code**: |
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- Go to [Visual Studio Code's official site](https://code.visualstudio.com/). |
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- Download the appropriate version for your operating system. |
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2. **Install Visual Studio Code**: |
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- Run the installer and follow the on-screen instructions to complete the installation. |
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3. **Install the Python Extension**: |
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- Open Visual Studio Code and go to the **Extensions** view by clicking on the square icon in the sidebar or pressing `Ctrl+Shift+X`. |
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- Search for "Python" and install the extension provided by Microsoft. |
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## Community and Support |
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Join our community to stay updated, share your experiences, and get support from other users: |
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- **Discord Server**: Join our Discord community for discussions, support, and updates. |
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- [Join Discord](https://discord.gg/vKEW6jqa49) |
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## Support and Contributions |
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If you find **IMageDucHaiten** useful and would like to support the project, consider making a donation or becoming a patron. Your contributions help in maintaining and improving the project: |
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- **PayPal**: You can make a one-time donation through PayPal. |
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- [Donate via PayPal](https://www.paypal.com/paypalme/duchaiten) |
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- **Patreon**: Become a patron and support ongoing development with monthly contributions. |
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- [Support on Patreon](https://www.patreon.com/duchaitenreal) |
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Thank you for your support! |
