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README.md

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-Models used in training for parts of OntoUML Image Taxonomy Extractor (OITE)
-The second dataset consists of the 643 OntoUML images[source](https://doi.org/10.1007/978-3-031-17995-2_1), 643 randomly picked class diagrams and 643 randomly picked non-UML images, taken from the dataset of the paper “Multiclass classification of four types of UML diagrams from images using deep learning" [link](https://doi.org/10.5281/zenodo.4595957 
+Dataset used in training for parts of OntoUML Image Taxonomy Extractor (OITE)
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+This dataset consists of the 643 OntoUML images[source](https://doi.org/10.1007/978-3-031-17995-2_1), 643 randomly picked class diagrams and 643 randomly picked non-UML images, taken from the dataset of the paper “Multiclass classification of four types of UML diagrams from images using deep learning" [link](https://doi.org/10.5281/zenodo.4595957 
 ). In my paper this dataset is referred to as the 3-class dataset. 
 See: https://github.com/SimeonKaishev/OntoUML_IMG_Converter