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  1. .github/README.md +47 -0
  2. README.md +19 -47
.github/README.md ADDED
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+ <div align="center">
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+ <h1>Semantic Diffusion Posterior Sampling for Cardiac Ultrasound Dehazing</h1>
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+ <p>
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+ <a href="https://arxiv.org/abs/0000.0000"><img src="https://img.shields.io/badge/arXiv-0000.0000-b31b1b.svg?logo=arXiv" alt="arXiv"></a>
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+ <a href="https://huggingface.co/collections/tristan-deep/semantic-diffusion-posterior-sampling-for-cardiac-ultrasound-68a70559a7f719c7e6bd5788"><img src="https://img.shields.io/badge/🤗%20Hugging%20Face-Model-orange" alt="Hugging Face Model"></a>
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+ <a href="https://keras.io/"><img src="https://img.shields.io/badge/Keras-EE4C2C?logo=keras&logoColor=white" alt="Keras"></a>
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+ </p>
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+ <h3>
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+ <a href="https://tristan-deep.github.io/">Tristan Stevens</a> &nbsp;|&nbsp;
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+ <a href="https://oisinnolan.github.io/">Oisín Nolan</a> &nbsp;|&nbsp;
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+ <a href="https://www.tue.nl/en/research/researchers/ruud-van-sloun">Ruud van Sloun</a>
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+ </h3>
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+ <p>Eindhoven University of Technology, the Netherlands</p>
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+ </div>
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+
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+ <p align="center">
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+ <img src="./paper/animation.gif" alt="Cardiac Ultrasound Dehazing Animation" style="max-width: 100%; height: auto;">
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+ </p>
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+
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+ ### Installation
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+
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+ The algorithm is implemented using Keras with JAX backend. Furthermore it heavily relies on the [zea ultrasound library](https://github.com/tue-bmd/zea).
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+
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+ Either install the following in your Python environment, or use the [Dockerfile](./Dockerfile) provided in this repository.
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+
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+ ```bash
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+ # requires Python>=3.10
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+ pip install tyro optuna zea==0.0.4
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+ pip install -U "jax[cuda12]"
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+ ```
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+
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+ > [!NOTE]
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+ > Although the code was primarily tested with JAX as the Keras backend, TensorFlow and PyTorch should also work.
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+
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+ ### Running the algorithm
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+
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+ Some example images are downloaded in the [./assets](./assets) folder. The models are automatically downloaded from the [Hugging Face Model Hub](https://huggingface.co/collections/tristan-deep/semantic-diffusion-posterior-sampling-for-cardiac-ultrasound-68a70559a7f719c7e6bd5788).
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+
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+ ```bash
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+ python main.py --input-folder ./assets --output-folder ./temp
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+ ```
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+
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+ Alternatively, you can use the Gradio app provided in this repository to interact with the model via a web interface. To launch the app, run:
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+
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+ ```bash
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+ python app.py
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+ ```
README.md CHANGED
@@ -1,47 +1,19 @@
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- <div align="center">
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- <h1>Semantic Diffusion Posterior Sampling for Cardiac Ultrasound Dehazing</h1>
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- <p>
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- <a href="https://arxiv.org/abs/0000.0000"><img src="https://img.shields.io/badge/arXiv-0000.0000-b31b1b.svg?logo=arXiv" alt="arXiv"></a>
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- <a href="https://huggingface.co/collections/tristan-deep/semantic-diffusion-posterior-sampling-for-cardiac-ultrasound-68a70559a7f719c7e6bd5788"><img src="https://img.shields.io/badge/🤗%20Hugging%20Face-Model-orange" alt="Hugging Face Model"></a>
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- <a href="https://keras.io/"><img src="https://img.shields.io/badge/Keras-EE4C2C?logo=keras&logoColor=white" alt="Keras"></a>
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- </p>
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- <h3>
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- <a href="https://tristan-deep.github.io/">Tristan Stevens</a> &nbsp;|&nbsp;
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- <a href="https://oisinnolan.github.io/">Oisín Nolan</a> &nbsp;|&nbsp;
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- <a href="https://www.tue.nl/en/research/researchers/ruud-van-sloun">Ruud van Sloun</a>
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- </h3>
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- <p>Eindhoven University of Technology, the Netherlands</p>
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- </div>
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-
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- <p align="center">
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- <img src="./paper/animation.gif" alt="Cardiac Ultrasound Dehazing Animation" style="max-width: 100%; height: auto;">
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- </p>
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-
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- ### Installation
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-
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- The algorithm is implemented using Keras with JAX backend. Furthermore it heavily relies on the [zea ultrasound library](https://github.com/tue-bmd/zea).
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-
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- Either install the following in your Python environment, or use the [Dockerfile](./Dockerfile) provided in this repository.
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-
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- ```bash
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- # requires Python>=3.10
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- pip install tyro optuna zea==0.0.4
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- pip install -U "jax[cuda12]"
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- ```
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-
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- > [!NOTE]
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- > Although the code was primarily tested with JAX as the Keras backend, TensorFlow and PyTorch should also work.
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-
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- ### Running the algorithm
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-
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- Some example images are downloaded in the [./assets](./assets) folder. The models are automatically downloaded from the [Hugging Face Model Hub](https://huggingface.co/collections/tristan-deep/semantic-diffusion-posterior-sampling-for-cardiac-ultrasound-68a70559a7f719c7e6bd5788).
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-
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- ```bash
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- python main.py --input-folder ./assets --output-folder ./temp
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- ```
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-
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- Alternatively, you can use the Gradio app provided in this repository to interact with the model via a web interface. To launch the app, run:
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-
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- ```bash
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- python app.py
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- ```
 
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+ ---
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+ title: "Semantic Diffusion Posterior Sampling for Cardiac Ultrasound Dehazing"
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+ emoji: "🫀"
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+ colorFrom: "red"
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+ colorTo: "purple"
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+ sdk: "gradio"
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+ sdk_version: "5.43.1"
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+ app_file: app.py
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+ pinned: false
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+ tags:
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+ - diffusion
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+ - ultrasound
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+ - dehazing
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+ - keras
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+ - jax
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+ - medical-imaging
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+ - huggingface
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+ author: Tristan Stevens, Oisín Nolan, Ruud van Sloun
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+ ---