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Wan2.1 Installation Script for Mac (tested on Mini M2)

This repository contains an installation script for setting up Wan2.1, a powerful AI-driven Text-to-Video (T2V) framework. Wan2.1 uses deep learning models to generate videos from text prompts, allowing for a seamless creation process.

While the main Wan2.1 repository contains the model and code for video generation, this repository provides an easy way to set up the environment, install dependencies, and get started with generating videos.

Features

  • Text-to-Video Generation: Create videos based on text descriptions.
  • AI-powered: Uses deep learning models to transform prompts into video sequences.
  • Customizable Prompts: Adjust the description, video size, and number of frames to generate different types of videos.
  • Simple Installation: Easily set up the environment with minimal steps using a bash script.

Setup Guide

The installation script automates the setup process for installing Wan2.1 and all the required dependencies. To get started, follow these steps:

  1. Clone this repository: 
    git clone https://github.com/yourusername/wan2.1-install.git
cd wan2.1-install
  2. Run the installation script: This will clone the Wan2.1 repository, create a Python virtual environment, install dependencies, and download the necessary model checkpoints. 
    ./install_wan.sh
  3. Generate videos: Once the installation is complete, you can generate videos by running the following command: 
    python generate.py --prompt "A sunset on the beach with waves crashing" --frame_num 120 --size "720*1280" --ckpt_dir ./Wan2.1-T2V-1.3B --save_file ./video.mp4
    This will generate a 120-frame video and save it as video.mp4 in the current directory.

Requirements

  • Python 3.7+
  • pip
  • Homebrew (for macOS users)
  • Xcode command line tools (macOS)
  • Hugging Face CLI for model downloading

License

This script is provided for ease of installation and use of the Wan2.1 framework. Wan2.1 is a third-party project and is licensed under its own terms (please refer to the original repository for more details).