| license: apache-2.0 | |
| library_name: pytorch | |
| tags: | |
| - remote-sensing | |
| - disaster-mapping | |
| - oil-spill | |
| - sar | |
| - segmentation | |
| # unet.pth — AnyDisasterMapping demo checkpoint (oil_spill) | |
| Task-checkpoint for the [AnyDisasterMapping](https://github.com/SyedRafiAhmedGIS/AnyDisasterMapping) model zoo (`unet` key, oil-spill SAR segmentation, 3-class). | |
| - Architecture: UNet, 28.96M params | |
| - Training: 3 epochs on tiny synthetic smoke tiles (64x64, 8 samples), CPU smoke run | |
| - Test metrics (synthetic split): OA 5.10% / mIoU 4.18% — demo / pipeline-plumbing quality, NOT production accuracy | |
| - Purpose: end-to-end validation of the weights distribution pipeline. Replace with real trained weights later by uploading a new unet.pth + refreshed SHA256SUMS. | |
| ## Download | |
| python tools/download_weights.py --list | |
| python tools/download_weights.py --model unet | |
| Checksums in SHA256SUMS (sha256sum format), auto-verified on download. | |