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CLIPSeg model with reduce dimension 64, refined (using a more complex convolution). It was introduced in the paper Image Segmentation Using Text and Image Prompts by Lüddecke et al. and first released in this repository.
Fuente del modelo
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CLIPSeg model with reduce dimension 64, refined (using a more complex convolution). It was introduced in the paper Image Segmentation Using Text and Image Prompts by Lüddecke et al. and first released in this repository.
This model is intended for zero-shot and one-shot image segmentation.
Fuentes
1 fuenteVerificado 8 sept
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2 extractos--- license: apache-2.0 tags: - vision - image-segmentation inference: false --- # CLIPSeg model CLIPSeg model with reduce dimension 64, refined (using a more complex convolution). It was introduced in the paper [Image Segmentation Using Text and Image Prompts](https://arxiv.org/abs/2112.10003) by Lüddecke et al. and first released in [this repository](https://github.com/timojl/clipseg). # Intended use cases This model is intended for zero-shot and one-shot image segmentation. # Usage Refer to the [documentation](https://huggingface.co/docs/transformers/main/en/model_doc/clipseg).
Refer to the documentation.
Source context: 2 downloads · 0 likes · Pipeline image-segmentation · Repo Trauma27/clipseg-rd64-refined
