metadata
license: mit
task_categories:
- image-segmentation
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)