Downloads · 30 days
0
geonusaf-unetformer-r18-random-fold1
sugam24/geonusaf-unetformer-r18-random-fold1
geonusaf-unetformer-r18-random-fold1 is a machine learning model from sugam24. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for pytorch.
Kathmandu Valley land-use segmentation, 6 classes, ignoreindex=255.
Access
Public
Updated Aug 17, 2026
Repo size
1.6 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.pt188 MB · 98%
At a glance
- Library
- pytorch
- Access
- Public
- Created
- Aug 17, 2026
- Updated
- Aug 17, 2026
- SHA
- 9555fe61
Model card
From the Hugging Face model README
GeoNUSAF - UNetFormer (ResNet-18) - random split, fold 1
Kathmandu Valley land-use segmentation, 6 classes, ignore_index=255.
| field | value |
|---|---|
| architecture | UNetFormer, timm resnet18 encoder (ImageNet), global-local attention decoder |
| split mode | random |
| fold | 1 of 3 |
| seed | 42 |
| input | 512x512, ImageNet norm, effective GSD 0.586 m/px |
| classes | Residential, Road, River, Forest, UnusedLand, Agricultural |
| lr (dec/enc) | 0.0006 / 6e-05, AdamW wd 0.0001 |
| aux head weight | 0.4 |
| best epoch | 33 |
| val mIoU | 0.5148 |
| val mF1 | 0.6640 |
| val OA | 0.7774 |
| val kappa | 0.6427 |
Per-class (validation)
| class | IoU | F1 |
|---|---|---|
| Residential | 0.8252 | 0.9042 |
| Road | 0.3881 | 0.5592 |
| River | 0.4677 | 0.6373 |
| Forest | 0.6327 | 0.7750 |
| UnusedLand | 0.3101 | 0.4734 |
| Agricultural | 0.4652 | 0.6350 |
Split caveat: block is sequence-block CV using an export-order proxy, not spatial CV.
Architecture is an independent implementation of Wang et al. (2022), ISPRS J. Photogramm. Remote Sens. 190:196-214 (the reference repo is GPL-3.0).
Checkpoint best.pt holds model_state plus cfg and metrics.
- Library
- pytorch
- Created
- Aug 17, 2026
- Updated
- Aug 17, 2026