Image Classification
timm
Safetensors
PyTorch
brain-mri
tumor-detection
out-of-distribution
medical-imaging
benchmark
Instructions to use Fatihaybasn/brainmri-ood-convnext-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use Fatihaybasn/brainmri-ood-convnext-tiny with timm:
import timm model = timm.create_model("hf_hub:Fatihaybasn/brainmri-ood-convnext-tiny", pretrained=True) - Notebooks
- Google Colab
- Kaggle
| { | |
| "project": "Brain MRI Tumor vs No-Tumor - OOD Generalization (10 Models)", | |
| "architecture": "convnext_tiny", | |
| "variant": "convnext_tiny", | |
| "num_classes": 2, | |
| "id2label": { | |
| "0": "no_tumor", | |
| "1": "tumor" | |
| }, | |
| "label2id": { | |
| "no_tumor": 0, | |
| "tumor": 1 | |
| }, | |
| "input_size": 224, | |
| "preprocessing": { | |
| "square_pad": true, | |
| "resize": [ | |
| 224, | |
| 224 | |
| ], | |
| "mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "std": [ | |
| 0.229, | |
| 0.224, | |
| 0.225 | |
| ] | |
| }, | |
| "decision_threshold": 0.5, | |
| "augmentation_strength": 0.0, | |
| "github_repository": "https://github.com/fatihaybsn/BrainMRI-OOD-10Models", | |
| "github_commit": "a9920408189230b886773a64d113eb35bcba1971", | |
| "original_checkpoint_sha256": "7d2d6b607ae902afb66af2a24355af39d2c29e1da3edb5c3c71db03bb12a5feb", | |
| "safetensors_sha256": "bae49603e33d7cdb2c1d923fce5ad7997762dfb7c1b2332d72a8f2e8394b357d", | |
| "metrics": { | |
| "accuracy": 0.7746695358130956, | |
| "auc": 0.9603446906820836, | |
| "f1": 0.7155607295304619, | |
| "recall_sensitivity": 0.5570996978851964, | |
| "precision": 1.0, | |
| "kappa": 0.5527336353188359 | |
| } | |
| } | |