Update README.md

README.md

@@ -82,7 +82,7 @@ The FLAIR models is a collection of semantic segmentation models initially devel
 The distributed pre-trained model differ in their :
 - input modalities : RVB (true colours), RVBI (true colours + infrared), RVBIE (true colours + infrared + elevation)
 - model architecture : U-Net with a Resnet-34 encoder, Deeplab
-- class nomenclature : 12 or 15 land cover classes
+- target class nomenclature : 12 or 15 land cover classes
 - dataset for training : [FLAIR dataset](https://huggingface.co/datasets/IGNF/FLAIR) or the increased version of this dataset FLAIR-INC.
 
 
@@ -90,24 +90,7 @@ The distributed pre-trained model differ in their :
 The general characteristics of this specific model *FLAIR-INC_RVBIE_resnet34_unet_15cl_norm* are :
 * RVBIE images (true colours + infrared + elevation)
 * U-Net with a Resnet-34 encoder
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+* 15 class nomenclature [building,pervious_surface,impervious_surface,bare_soil,water,coniferous,deciduous,brushwood,vineyard,herbaceous,agricultural_land,plowed_land,swimming pool,snow,greenhouse]