Image Segmentation
Transformers
English
clipseg
segmentation
construction
drywall
quality-assurance
text-conditioned
binary-mask
Instructions to use youngPhilosopher/drywall-qa-clipseg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use youngPhilosopher/drywall-qa-clipseg with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="youngPhilosopher/drywall-qa-clipseg")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("youngPhilosopher/drywall-qa-clipseg", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 54ad80f2959e7bedda1e37bac930551f7d2743e80f5701e1125a753063dc517b
- Size of remote file:
- 4.9 MB
- SHA256:
- 048c3df1a28bd8b633df91f1fd161389d9dca37582be2cc3a8b6aa938fddec00
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