Trained on ISIC 2017 Task 1 lesion-boundary masks. Educational project — not diagnostic-grade, not a medical device.
Model Card
By Ashraf, published under mit, revision fabc3db482aa.
Trained on ISIC 2017 Task 1 lesion-boundary masks. Educational project — not diagnostic-grade, not a medical device.
Read Ashraf's full model card
Skin Lesion Segmentation (U-Net, ResNet34 encoder)
Trained on ISIC 2017 Task 1 lesion-boundary masks. Educational project — not diagnostic-grade, not a medical device.
Load
import segmentation_models_pytorch as smp, torch
from huggingface_hub import hf_hub_download
model = smp.Unet(encoder_name="resnet34", encoder_weights=None, in_channels=3, classes=1)
weights_path = hf_hub_download(repo_id="Farhan2000/skin-lesion-segmentation-unet", filename="model.pth")
model.load_state_dict(torch.load(weights_path, map_location="cpu"))
model.eval()
Mean validation Dice: 0.8520
Identity and Version
- Repository
- Farhan2000/skin-lesion-segmentation-unet
- Publisher
- Ashraf
- Task
- Not stated by the source
- Modality
- Other
- Library
- Not stated by the source
- Parameters
- Not stated by the source
- Languages
- Not stated by the source
- Revision
- fabc3db482aa45ad47232f70a0ce85c6180f7647
- First published
- 2026-09-18
- Last updated
- 2026-09-18
Files and Weights
3 files, 97.9 MB in total. The weights are 1 file totalling 97.9 MB in pth.
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| model.pth | Weights | 97.9 MB | ccb8d5e95999 |
| README.md | Documentation | 735 B | — |
| .gitattributes | Repository | 1.5 KB | — |
License and Download
- License
- mit
- Access
- Open weights, no gate
- Download size
- 97.9 MB
Released by Ashraf through its official repository on Hugging Face. Read the license.
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 97.9 MB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About skin-lesion-segmentation-unet
Can I use skin-lesion-segmentation-unet commercially?
Yes. skin-lesion-segmentation-unet is released under MIT License. The MIT License is a short permissive license. It permits commercial use, modification and redistribution, provided the copyright notice and permission notice are included.