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. ๐
- ๐จ Generate videos in the iconic Studio Ghibli art style
- โก Optimized for efficiency with fine-tuned zeroscope_v2_576w
- ๐ ๏ธ User-friendly notebooks for training and inference
- ๐ Interactive Gradio demo for real-time video generation
- ๐ง Enhanced stability and performance over the original MotionDirector
Explore the project with our comprehensive notebook:
You can explore more in this HuggingFace Dataset available at the given link for further details: .
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. ๐
This project builds upon the zeroscope_v2_576w model, fine-tuned with LoRA for Ghibli-style video generation, forked from MotionDirector. ๐
Experience the magic of Ghibli-style video generation:
To run the Gradio app locally (localhost:7860):
python apps/gradio_app.pyClone the project repository and navigate to the project directory:
git clone https://github.com/danhtran2mind/Text2Video-Ghibli-style.git
cd Text2Video-Ghibli-styleInstall the required Python packages:
pip install -r requirements/requirements.txtRun 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
- 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. โ๏ธ
To generate videos using the trained model:
python src/text2video_ghibli_style/inference.py- Python: 3.10 or higher
- Key Libraries: See requirements_compatible.txt for compatible versions
This repository is trained from , a fork of
, with numerous bug fixes and rewritten code for improved performance and stability. You can download the
zeroscope_v2_576w model from the . Explore more models on
.