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
Upload README.md with huggingface_hub
Browse files
README.md
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<p align="center">
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<h1 align="center">Prompted Segmentation for Drywall QA</h1>
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<p align="center">
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---
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license: mit
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language:
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- en
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tags:
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- clipseg
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- segmentation
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- construction
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- drywall
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- quality-assurance
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- text-conditioned
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- binary-mask
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library_name: transformers
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base_model: CIDAS/clipseg-rd64-refined
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pipeline_tag: image-segmentation
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datasets:
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- roboflow/drywall-join-detect
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- roboflow/cracks-3ii36
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metrics:
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- iou
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- dice
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---
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<p align="center">
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<h1 align="center">Prompted Segmentation for Drywall QA</h1>
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<p align="center">
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