Image-Synthesis-with-Class-Aware-Semantic-Diffusion-Models-for-Surgical-Scene-Segmentation

Training: See <a href="/YihangZHO/Image-Synthesis-with-Class-Aware-Semantic-Diffusion-Models-for-Surgical-Scene-Segmentation/blob/main/train.ipynb"> train.ipynb
Generation / Testing: See <a href="/YihangZHO/Image-Synthesis-with-Class-Aware-Semantic-Diffusion-Models-for-Surgical-Scene-Segmentation/blob/main/test.ipynb"> test.ipynb

Official code for the paper: Image Synthesis with Class-Aware Semantic Diffusion Models for Surgical Scene Segmentation

📁 Datasets & Resources

Our model is built upon the following excellent open-source projects:

🤗 Hugging Face Diffusers – the baseline of this project and code for mask synthesis is based on its implementation of Stable Diffusion
🧠 Semantic Diffusion Model by Weilun Wang – semantic-aware conditioning framework

We thank the authors for their contributions to the open-source community.

Feel free to open an issue or contact us if you have any questions.
Pull requests are welcome!

Name		Name	Last commit message	Last commit date
Latest commit History 15 Commits
.DS_Store		.DS_Store
LICENSE		LICENSE
README.md		README.md
cholecSegClasses.json		cholecSegClasses.json
conv.py		conv.py
image_dataset.py		image_dataset.py
image_gen.py		image_gen.py
linear.py		linear.py
mask_only_dataset.py		mask_only_dataset.py
pipeline_ddim.py		pipeline_ddim.py
pipeline_ddpm.py		pipeline_ddpm.py
requirements.txt		requirements.txt
test.ipynb		test.ipynb
train.ipynb		train.ipynb
train_colab.py		train_colab.py
unet_2d.py		unet_2d.py