Image Tokenizer encode visuals.
Project description
ImageTokenizer: Unified Image and Video Tokenization
Welcome to the ImageTokenizer repository! 🎉 This Python package is designed to simplify the process of image and video tokenization, a crucial step for various applications such as image/video generation and understanding. We provide a variety of popular tokenizers with a simple and unified interface, making your coding experience seamless and efficient. 🛠️
Features
- Unified Interface: A consistent API for all supported tokenizers.
- Extensive Support: Covers a range of popular image and video tokenizers.
- Easy Integration: Quick setup and integration with your projects.
Supported Tokenizers
Here's a list of the current supported image tokenizers:
- OmniTokenizer: Versatile tokenizer capable of handling both images and videos.
- OpenMagvit2: An open-source version of Magvit2, renowned for its excellent results.
Getting Started
To get started with ImageTokenizer, follow these simple steps:
Installation
You can install ImageTokenizer using pip:
pip install imagetokenizer
Usage
Here's a quick example of how to use OmniTokenizer:
from imagetokenizer import OmniTokenizer
# Initialize the tokenizer
image_tokenizer = OmniTokenizer()
# Tokenize an image
image_tokens = image_tokenizer.encode("path_to_your_image.jpg")
# Print the tokens
print(image_tokens)
image = image_tokenizer.decode(image_tokens)
Documentation
For more detailed information and examples, please refer to our official documentation.
Contributing
We welcome contributions! If you have an idea for a new tokenizer or want to improve existing ones, feel free to submit a pull request or create an issue. 🔧
License
ImageTokenizer is open-source and available under the MIT License.
Community
- Join our Slack Channel to discuss and collaborate.
- Follow us on Twitter for updates and news.
Acknowledgements
We would like to thank all the contributors and the community for their support and feedback. 🙏
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