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
File size: 1,167 Bytes
0661b82 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 | {
"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
}
}
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