Instructions to use CIDAS/clipseg-rd64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CIDAS/clipseg-rd64 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="CIDAS/clipseg-rd64")# Load model directly from transformers import AutoProcessor, CLIPSegForImageSegmentation processor = AutoProcessor.from_pretrained("CIDAS/clipseg-rd64") model = CLIPSegForImageSegmentation.from_pretrained("CIDAS/clipseg-rd64") - Notebooks
- Google Colab
- Kaggle
metadata
license: apache-2.0
tags:
- vision
- image-segmentation
inference: false
CLIPSeg model
CLIPSeg model with reduce dimension 64. It was introduced in the paper Image Segmentation Using Text and Image Prompts by Lüddecke et al. and first released in this repository.
Intended use cases
This model is intended for zero-shot and one-shot image segmentation.
Usage
Refer to the documentation.