| --- |
| 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](`https://github.com/GonzaloPlaaza/OCULAR`). |
|
|
| ## Usage |
|
|
| ```python |
| 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) |
