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
File size: 460 Bytes
fabc606 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | {
"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"
} |