Name | Version |
---|---|
Python | 3.9 |
To run the project in a Python virtual environment, run the following commands:
python -m venv venv
Install the dependencies:
pip install -r requirements.txt
If you have an NVIDIA GPU, you can install the CUDA toolkit and cuDNN to enable GPU support. If you don't have an NVIDIA GPU, skip the following steps.
- Download and install CUDA 12.1 for Windows
- Download and install Visual Studio with C++ build tools
- In the Visual Studio Installer, under Workloads, select Desktop development with C++
- or Under Individual components, select MSVC v... - VS 20.. C++ x64/x86 build tools (not sure if that works. i selected the full c++ bundle)
- Proceed with the installation
- Download cuDNN (any compatible version)
- Create an NVIDIA developer account if you don't have one
- Extract the cuDNN zip file
- Copy the files from the
bin
folder toC:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.1\bin
- Copy the files from the
include
folder toC:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.1\include
- Copy the files from the
lib\x64
folder toC:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.1\lib\x64
- Copy the files from the
- Download the dependencies using:
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121