INSTALLATION.md

📦 Installation

🤖 PIP installation

CeLux offers two installation options tailored to your system's capabilities:

1. CPU-Only Version: For systems without CUDA-capable GPUs.
2. CUDA (GPU) Version: For systems with NVIDIA GPUs supporting CUDA.

🖥️ CPU-Only Installation

Install the CPU version of CeLux using pip:

pip install celux

Note: The CPU version only supports CPU operations. Attempting to use GPU features with this version will result in an error.

🖥️ CUDA (GPU) Installation

Install the CUDA version of CeLux using pip:

pip install celux-cuda

Note: The CUDA version requires a CUDA-capable GPU and the corresponding Torch-Cuda installation.

🔄 Both Packages Import as celux

Regardless of the installation choice, both packages are imported using the same module name:

import celux #as cx

This design ensures a seamless transition between CPU and CUDA versions without changing your import statements.

🛠️ Building from Source

While CeLux is easily installable via pip, you might want to build it from source for customization or contributing purposes.

1. Clone the Repository:

   git clone https://github.com/Trentonom0r3/celux.git
   cd celux

2. Install Dependencies:

   Ensure all prerequisites are installed. You can use vcpkg for managing dependencies on Windows.

3. Configure the Project with CMake:

   cmake -B build -S . -DCMAKE_BUILD_TYPE=Release

   Windows Users: If using Vcpkg, include the toolchain file:

   cmake -B build -S . -DCMAKE_BUILD_TYPE=Release -DCMAKE_TOOLCHAIN_FILE=<path_to_vcpkg>/scripts/buildsystems/vcpkg.cmake

4. Build the Project:

   cmake --build build --config Release

5. Install the Package:

   cmake --install build

6. Set Up Environment Variables:

   Ensure FFmpeg binaries and other dependencies are in your system's PATH. On Unix systems, you might need to set LD_LIBRARY_PATH or DYLD_LIBRARY_PATH.