# Get Started ## Prerequisites In this section we demonstrate how to prepare an environment with PyTorch. We ran our experiments with PyTorch 2.3.0, CUDA 11.8, Python 3.10 and Ubuntu 18.04. We recommend using the same configuration to avoid environment conflicts. **Note:** If you are experienced with PyTorch and have already installed it, just skip this part and jump to the [next section](##installation). Otherwise, you can follow these steps for the preparation. **Step 0.** Download and install [Anaconda](https://www.anaconda.com/download#downloads) or [Miniconda](https://docs.conda.io/en/latest/miniconda.html) from the official website. **Step 1.** Create a conda environment and activate it. ```shell conda create --name depthmaster python==3.10 conda activate depthmaster ``` **Step 2.** Install PyTorch following [official instructions](https://pytorch.org/get-started/locally/), e.g. ```shell pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118 ``` ## Installation We recommend that users follow our practices for installation. **Step 1.** Clone repository. ```shell git clone https://github.com/indu1ge/DepthMaster.git cd DepthMaster ``` **Step 2.** Install requirements. ```shell pip3 install -U xformers --index-url https://download.pytorch.org/whl/cu118 pip install opencv-python transformers matplotlib safetensors accelerate tensorboard datasets scipy einops pytorch_lightning omegaconf diffusers peft pip3 install h5py scikit-image tqdm bitsandbytes wandb tabulate ``` Download checkpoints for [Stable Diffusion v2](https://huggingface.co/stabilityai/stable-diffusion-2/tree/main).