Skip to content

Latest commit

ย 

History

39 Commits

Folders and files

NameName
Last commit message
Last commit date
ย 
ย 
ย 
ย 
ย 
ย 
ย 
ย 
ย 
ย 
ย 
ย 
ย 
ย 
ย 
ย 
ย 
ย 
ย 
ย 
ย 
ย 
ย 
ย 
ย 
ย 

Repository files navigation

Text to Video Ghibli style ๐ŸŽž๏ธ (Text2Video-Ghibli-style)

GitHub Stars Badge

huggingface-hub accelerate torch transformers torchvision diffusers gradio License: MIT

Introduction

Transform text into captivating videos with the enchanting aesthetic of Studio Ghibli. This project leverages a fine-tuned zeroscope_v2_576w model to generate high-quality, Ghibli-inspired video content from text prompts. Built upon the foundation of MotionDirector, it includes optimized code and enhanced stability for seamless performance. ๐ŸŒŸ

Key Features

  • ๐ŸŽจ Generate videos in the iconic Studio Ghibli art style
  • โšก Optimized for efficiency with fine-tuned zeroscope_v2_576w
  • ๐Ÿ› ๏ธ User-friendly notebooks for training and inference
  • ๐ŸŒ Interactive Gradio demo for real-time video generation
  • ๐Ÿ”ง Enhanced stability and performance over the original MotionDirector

Notebook

Explore the project with our comprehensive notebook:

Training Notebook:

Open In Colab Open in SageMaker Open in Deepnote JupyterLab Open in Gradient Open in Binder View on GitHub Open In Kaggle

Inference Notebook:

Open In Colab Open in SageMaker Open in Deepnote JupyterLab Open in Gradient Open in Binder View on GitHub Open In Kaggle

Dataset

You can explore more in this HuggingFace Dataset available at the given link for further details: HuggingFace Dataset.

The model is trained on a curated dataset inspired by Studio Ghibli's visual style, ensuring authentic and high-quality video outputs. Details are available in the dataset processing script. ๐Ÿ“Š

Base Model

This project builds upon the zeroscope_v2_576w model, fine-tuned with LoRA for Ghibli-style video generation, forked from MotionDirector. ๐Ÿš€

Demonstration

Experience the magic of Ghibli-style video generation:

  • HuggingFace Space: HuggingFace Space Demo

  • Demo GUI:
    Gradio Demo

To run the Gradio app locally (localhost:7860):

python apps/gradio_app.py

Getting Started

Setup Instructions

Step 1: Clone the Repository

Clone the project repository and navigate to the project directory:

git clone https://github.com/danhtran2mind/Text2Video-Ghibli-style.git
cd Text2Video-Ghibli-style

Step 2: Install Dependencies

Install the required Python packages:

pip install -r requirements/requirements.txt

Step 3: Configure the Environment

Run the following scripts to set up the project:

  • Install Third-Party Dependencies
    python scripts/setup_third_party.py
  • Download Model Checkpoints
    python scripts/download_ckpts.py
  • Prepare Dataset (Optional, for Training)
    python scripts/process_dataset.py

Usage

Training

  • To train the model:
python src/text2video_ghibli_style/train.py
  • Training Hyperparameters Refer to the Training Documents for detailed hyperparameters used in fine-tuning the model. โš™๏ธ

Inference

To generate videos using the trained model:

python src/text2video_ghibli_style/inference.py

Inference Samples

Prompt Video
A dog is running with Ghibli style Example 1 gif
A girl is walking with Ghibli style Example 2 gif
Studio Ghibli style. Young man contemplates, walks away from ivy-covered yellow building. Example 3 gif
Studio Ghibli style. Two women walk down coastal village path toward sea, passing colorful houses, sailboats visible. Example 4 gif

Environment

Project Description

This repository is trained from GitHub Repo, a fork of GitHub Repo, with numerous bug fixes and rewritten code for improved performance and stability. You can download the zeroscope_v2_576w model from the HuggingFace: cerspense/zeroscope_v2_576w. Explore more models on HuggingFace Hub.

About

This repository is trained from [MotionDirector](https://github.com/danhtran2mind/MotionDirector), a fork of [Showlab's MotionDirector](https://github.com/showlab/MotionDirector).

Topics

Resources

Stars

1 star

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages