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isic-segformer
mahnoor-2722/isic-segformer
isic-segformer is a image segmentation model from mahnoor-2722. Use it for the image segmentation task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
Pixel-level skin lesion segmentation model fine-tuned on ISIC 2018 Task 1.
Access
Public
Updated Sep 1, 2026
Repo size
14.9 MB
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Repo makeup
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.pth14.9 MB · 100%
At a glance
- Task
- Image Segmentation
- Library
- transformers
- License
- mit
- Access
- Public
- Created
- Aug 29, 2026
- Updated
- Sep 1, 2026
- SHA
- 2d8c48d7
Model card
From the Hugging Face model README
ISIC Skin Lesion Segmentation — SegFormer (MiT-B0)
Pixel-level skin lesion segmentation model fine-tuned on ISIC 2018 Task 1.
Model Details
- Architecture: SegFormer (NVIDIA MiT-B0)
- Task: Binary medical image segmentation (lesion vs background)
- Framework: PyTorch + Hugging Face Transformers
- Input size: 256 × 256
- Output: Lesion probability mask
- Parameters: ~3.7M
Performance (ISIC 2018)
| Metric | Score |
|---|---|
| Test Dice | 90.32% |
| Test IoU | 82.50% |
Compared against a from-scratch U-Net baseline (85.26% Dice).
Files
best_segformer_isic2018.pth— fine-tuned weights
How to Load
from transformers import SegformerForSemanticSegmentation
from huggingface_hub import hf_hub_download
import torch
model = SegformerForSemanticSegmentation.from_pretrained(
"nvidia/mit-b0",
num_labels=1,
ignore_mismatched_sizes=True
)
path = hf_hub_download(
"mahnoor-2722/isic-segformer",
"best_segformer_isic2018.pth"
)
model.load_state_dict(torch.load(path, map_location="cpu"))
model.eval()
- Task
- Image Segmentation
- Library
- transformers
- License
- mit
- Created
- Aug 29, 2026
- Updated
- Sep 1, 2026