Image Segmentation
Transformers
Safetensors
remote-sensing
earth-observation
open-vocabulary
clip
sam3
semantic-segmentation
Instructions to use Dingyi111/SegEarth-OV with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dingyi111/SegEarth-OV with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="Dingyi111/SegEarth-OV")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Dingyi111/SegEarth-OV", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "version": "OV", | |
| "backbone": "CLIP", | |
| "model_id": "openai/clip-vit-base-patch16", | |
| "vit_type": "ViT-B/16", | |
| "featup": "jbu_one", | |
| "featup_weights": "weights/featup/xclip_jbu_one_million_aid.ckpt", | |
| "cls_token_lambda": -0.3, | |
| "logit_scale": 50.0, | |
| "clip_types": [ | |
| "CLIP", | |
| "OpenCLIP", | |
| "MetaCLIP", | |
| "RemoteCLIP", | |
| "GeoRSCLIP", | |
| "SkyCLIP", | |
| "BLIP", | |
| "ALIP" | |
| ], | |
| "local_backbone": "weights/backbone/clip-vit-base-patch16" | |
| } |