Image Segmentation
PyTorch
timm
unet
regnetz_d8
segmentation-models-pytorch
remote-sensing
sentinel-2
multispectral
cloud-detection
Instructions to use Burdenthrive/cloud-detection-unet-regnetzd8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use Burdenthrive/cloud-detection-unet-regnetzd8 with timm:
import timm model = timm.create_model("hf_hub:Burdenthrive/cloud-detection-unet-regnetzd8", pretrained=True) - Notebooks
- Google Colab
- Kaggle
Invalid JSON:Unexpected token 'N', ..."weights": None,
"... is not valid JSON
| { | |
| "task": "image-segmentation", | |
| "model_name": "unet-regnetz-d8", | |
| "model_kwargs": { | |
| "encoder_name": "tu-regnetz_d8", | |
| "encoder_weights": None, | |
| "in_channels": 13, | |
| "num_classes": 4 | |
| }, | |
| "classes": ["clear", "thick cloud", "thin cloud", "cloud shadow"] | |
| } | |