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SegFormer model fine-tuned on AROI
SegFormer model fine-tuned on AROI dataset AROI: Annotated Retinal OCT Images Database.
Disclaimer: The team releasing SegFormer did not write a model card for this model so this model card has been written by the Hugging Face team.
Model description
SegFormer consists of a hierarchical Transformer encoder and a lightweight all-MLP decode head to achieve great results on semantic segmentation benchmarks such as ADE20K and Cityscapes. The hierarchical Transformer is first pre-trained on ImageNet-1k, after which a decode head is added and fine-tuned altogether on a downstream dataset.
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# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("coralexbadea/Segformer_OCT_Retina") model = SegformerForSemanticSegmentation.from_pretrained("coralexbadea/Segformer_OCT_Retina")