gplazaarriola/OCULARNet-nano

A lightweight ensemble version, OCULARNet-nano (base UNet + RepVGG-A0), from the full OCULARNet model for retinal artery-vein segmentation.

Datasets, training and inference details can be found in our GitHub repository.

Usage

import torch
device = torch.device('cuda:0' if use_cuda else 'cpu')

models = []
for fold in range(1, 6):
  checkpoint = torch.load(f"nano_f{fold}.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)
  model.to(device)

  models.append(model)