Installation - Ktiseos-Nyx/Dataset-Tools GitHub Wiki

Installation

Getting Dataset-Tools up and running is simple. You can install it directly using pip, which is the recommended method for most users.

Recommended Method: `pip` Install

This method installs the application and all its dependencies automatically.

Ensure you have Python 3.10 or newer. You can download it from python.org.
Open your terminal or command prompt.
Install the tool with a single command:
```
pip install dataset-tools
```
Once installed, you can run the application by typing:
```
dataset-tools
```

Developer Setup

If you want to contribute to the project, test new features, or run the application directly from the source code, follow these steps.

1. Prerequisites

Python: You need Python 3.10 or newer.
Git: You need Git to clone the repository. You can get it from git-scm.com.
(Optional) uv: We recommend using uv for faster package management. You can find installation instructions at astral.sh/docs/uv/install.sh.

2. Cloning the Repository

Open your terminal and clone the repository to your local machine:

git clone https://github.com/Ktiseos-Nyx/Dataset-Tools.git
cd Dataset-Tools

3. Installing Dependencies

The project's dependencies are listed in the requirements.txt file.

Using uv (Recommended):
```
uv pip install -r requirements.txt
```
Using pip:
```
pip install -r requirements.txt
```

Note for Linux Users (Especially Debian/Ubuntu):

The graphical interface for Dataset-Tools depends on PyQt6. On some Linux systems, pip may not automatically install the required system-level libraries. If you encounter errors related to libxcb or other missing libraries after installation, you may need to install them manually using your system's package manager.

For Debian/Ubuntu-based systems, run the following command:

sudo apt update
sudo apt install libxcb-xinerama0 libxcb-icccm4 libxcb-image0 libxcb-keysyms1 libxcb-render-util0 libxcb-shape0 libxkbcommon-x11-0 libgl1-mesa-glx

(Package names may differ on other distributions.)

4. Running from Source

After installing the dependencies, you can run the application from the root of the cloned directory with:

python -m dataset_tools