Image Segmentation
Transformers
English
Chinese
remote sensing
vision language model
semi-supervised
Instructions to use fluorites/SemiEarth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fluorites/SemiEarth with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="fluorites/SemiEarth")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("fluorites/SemiEarth", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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---
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license: apache-2.0
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---
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license: apache-2.0
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datasets:
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- fluorites/SemiEarth
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base_model:
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- Qwen/Qwen-VL
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- facebook/dinov2
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pipeline_tag: image-segmentation
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library_name: transformers
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tags:
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- remote sensing
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- vision language model
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- semi-supervised
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language:
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- en
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- zh
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metrics:
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- miou
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new_version: fluorites/SemiEarth-v1.0
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---
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# Citation
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If you find it useful, please consider citing:
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```
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@article{wang2026vision,
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title = {Vision-Language Model Purified Semi-Supervised Semantic Segmentation for Remote Sensing Images},
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author = {Wang, Shanwen and Sun, Xin and Hong, Danfeng and Zhou, Fei},
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journal = {arXiv preprint arXiv:2602.00202},
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year = {2026},
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month = feb,
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note = {Available at \url{https://arxiv.org/abs/2602.00202}}
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}
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```
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