I present a demo showcasing retinal vessel segmentation using the U-Net model, which is a well-known and widely used model in medical image segmentation. The model was trained on the DRIVE dataset, and the training process was conducted on Google Colab. The demo itself was built using Streamlit and deployed using localtunnel.
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This model is not currently available via any of the supported third-party Inference Providers, and
the HF Inference API does not support keras models with pipeline type image-segmentation