
omnihuman
AI model that understands text & humanoids.
Stars: 92

OmniHuman is an AI model designed to understand humanoids and text. It provides functionalities to process images and videos, generating text descriptions for human actions depicted in the visual content. The tool offers support for various tasks related to human pose recognition and action understanding. Users can easily integrate OmniHuman into their projects to enhance the capabilities of their applications in recognizing and interpreting human actions in images and videos.
README:
[!IMPORTANT]
pip install omnihuman
or install editable from source
git clone https://github.com/mdsrqbl/omnihuman.git
cd omnihuman
pip install -e .
import omnihuman
import PIL.Image
text = "Raise both hands and clap overhead."
frames = omnihuman.read_frames("path/to/image.jpg") # (1, channels, height, width)
# frames = omnihuman.read_frames("path/to/video.mp4") # (n_frames, channels, height, width)
# model = omnihuman.OmniHuman()
# frames = model.generate_video(text, frames)
PIL.Image.fromarray(frames[-1].permute(1,2,0).numpy()).show()
Full documentation is available at omnihuman.readTheDocs.io.
@misc{mdsr2024omnihuman,
author = {Mudassar Iqbal},
title = {OmniHuman: AI model that understands text and humanoids.},
year = {2024},
publisher = {GitHub},
howpublished = {\url{https://github.com/mdsrqbl/omnihuman}}
}
This project is licensed under Apache License 2.0 - see the LICENSE file for details.
You are permitted to use the library & models, create modified versions, or incorporate pieces of the code into your own work. Your product or research, whether commercial or non-commercial, must provide appropriate credit to the original author(s) by citing this repository & research papers. And although it follows common sense, you can not steal namespace and must put in the effort to give your work an original name.
Stay tuned for research papers!
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