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unet_tte
StanfordShahLab/unet_tte
unet_tte is a machine learning model from StanfordShahLab. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
This is a PyTorch Lightning .ckpt checkpoint for a SwinUNETR model trained on chest CT images with TTE objective.
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At a glance
- License
- apache-2.0
- Model type
- model_3d
- Access
- Public
- Created
- Apr 29, 2025
- Updated
- Apr 29, 2025
- SHA
- f015a1bb
Model card
From the Hugging Face model README
SwinUNETR Checkpoint
This is a PyTorch Lightning .ckpt checkpoint for a SwinUNETR model trained on chest CT images with TTE objective.
Usage
A quickstart script is below.
import torch
from src.networks import SwinUNETRForClassification
swin_unetr_params = {
"img_size": (224, 224, 224),
"in_channels": 1,
"out_channels": 2,
"feature_size": 48,
"drop_rate": 0.0,
"attn_drop_rate": 0.0,
"dropout_path_rate": 0.0,
"use_checkpoint": True,
}
model = SwinUNETRForClassification(
swin_unetr_params=swin_unetr_params, num_classes=2
).to(device)
state_dict = torch.load(
loadmodel_path, map_location=f"cuda:{torch.cuda.current_device()}"
)
model.load_state_dict(state_dict)
For detailed instructions please follow the README in Github repo.
- Type
- model_3d
- License
- apache-2.0
- Created
- Apr 29, 2025
- Updated
- Apr 29, 2025