Transformers
TensorBoard
Safetensors
PyTorch
English
SegformerForSemanticSegmentation
semantic-segmentation
segformer
agricultural-cv
Eval Results (legacy)
Instructions to use mujerry/corm-fusarium-segformer-mit-b0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mujerry/corm-fusarium-segformer-mit-b0 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mujerry/corm-fusarium-segformer-mit-b0", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Segformer Corm & Damage Segmentation Model
This repository contains weights and comprehensive logs for experiment segformer_run_2026-06-24_11-25.
Model Summary
- Architecture Type: Segformer (
nvidia/mit-b0) - Input Channels: RGB
- Classes: - Class 0: Background
- Class 1: Damage
- Class 2: Corm
Best Metric Deliverables
- Validation Mean IoU:
0.9278693459984201 - Validation Damage IoU:
0.8253293380141987 - Validation Corm IoU:
0.9605193726057429
Metric Curves
Below are the training performance plots generated for this run:

- Downloads last month
- 563
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support
Evaluation results
- Best Val Mean IoUself-reported0.928
- Best Val Damage-Class IoUself-reported0.825
- Best Val Corm-Class IoUself-reported0.961