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
| [project] | |
| name = "ai" | |
| version = "0.1.0" | |
| description = "Add your description here" | |
| readme = "README.md" | |
| requires-python = ">=3.11" | |
| dependencies = [ | |
| "diagrams>=0.25.1", | |
| "hf-cli>=0.1", | |
| "matplotlib>=3.10.8", | |
| "numpy>=2.4.4", | |
| "pillow>=12.2.0", | |
| "pycocotools>=2.0.11", | |
| "pyyaml>=6.0.3", | |
| "roboflow>=1.3.1", | |
| "scikit-learn>=1.8.0", | |
| "supervision>=0.27.0.post2", | |
| "torch>=2.11.0", | |
| "torchvision>=0.26.0", | |
| "tqdm>=4.67.3", | |
| "transformers>=5.5.3", | |
| ] | |