OCULARNet

--- license: mit pipeline_tag: image-segmentation --- # Retinal Artery-Vein Segmentation Models ## Available checkpoints We present the OCULARNet model, a base UNet encoder - (256, 128, 64, 32) layer size - coupled with a RepVGG-B3 decoder loaded from `segmentation_models_pytorch` for retinal artery-vein segmentation. Datasets, training and inference details can be found in our [GitHub repository](`https://github.com/GonzaloPlaaza/OCULAR`). ## Usage ```python import torch device = torch.device('cuda:0' if use_cuda else 'cpu') checkpoint = torch.load("OCULARNet.pth", map_location=device) if "model_state_dict" in checkpoint: state_dict = checkpoint["model_state_dict"] else: state_dict = checkpoint model.load_state_dict(state_dict)