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
| license: apache-2.0 | |
| datasets: | |
| - fluorites/SemiEarth | |
| base_model: | |
| - Qwen/Qwen-VL | |
| - facebook/dinov2 | |
| pipeline_tag: image-segmentation | |
| library_name: transformers | |
| tags: | |
| - remote sensing | |
| - vision language model | |
| - semi-supervised | |
| language: | |
| - en | |
| - zh | |
| metrics: | |
| - miou | |
| new_version: fluorites/SemiEarth-v1.0 | |
| # Citation | |
| If you find it useful, please consider citing: | |
| ``` | |
| @article{wang2026vision, | |
| title = {Vision-Language Model Purified Semi-Supervised Semantic Segmentation for Remote Sensing Images}, | |
| author = {Wang, Shanwen and Sun, Xin and Hong, Danfeng and Zhou, Fei}, | |
| journal = {arXiv preprint arXiv:2602.00202}, | |
| year = {2026}, | |
| month = feb, | |
| note = {Available at \url{https://arxiv.org/abs/2602.00202}} | |
| } | |
| ``` |