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: 1,133 Bytes
fabc606 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | #!/usr/bin/env python3
"""Test all SegEarth pipelines load correctly. Run: conda activate ifedit && python test_pipelines.py [OV|OV-2|OV-3]"""
import sys
def main():
from pipeline import SegEarthPipeline
device = sys.argv[2] if len(sys.argv) > 2 else "cuda"
variants = [("OV", device), ("OV-2", device), ("OV-3", device)]
if len(sys.argv) > 1:
want = sys.argv[1]
variants = [(v, d) for v, d in variants if v == want]
if not variants:
print(f"Unknown variant: {want}")
sys.exit(1)
for variant, device in variants:
print(f"Loading {variant}...", end=" ", flush=True)
try:
pipe = SegEarthPipeline(variant=variant, device=device)
print("OK")
except ImportError as e:
if "sam3" in str(e) and variant == "OV-3":
print("SKIP (sam3 not installed)")
else:
print(f"FAIL: {e}")
raise
except Exception as e:
print(f"FAIL: {e}")
raise
print("All pipelines loaded successfully.")
if __name__ == "__main__":
main()
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