Update README.md

README.md

@@ -42,7 +42,7 @@ The DENTEX provides three hierarchically annotated datasets that facilitate vari
 
 The DENTEX 2023 dataset comprises three types of data: (a) partially annotated quadrant data, (b) partially annotated quadrant-enumeration data, and (c) fully annotated quadrant-enumeration-diagnosis data. The first two types of data are intended for training and development purposes, while the third type is used for training and evaluations.
 
-To comply with standard machine learning practices, the fully annotated third dataset, consisting of 1005 panoramic X-rays, is partitioned into training, validation, and testing subsets, comprising 705, 50, and 250 images, respectively. Ground truth labels are provided only for the training data, while the validation data is provided without associated ground truth, and the testing data is kept hidden from participants.
+To comply with standard machine learning practices, the fully annotated third dataset, consisting of 1005 panoramic X-rays, is partitioned into training, validation, and testing subsets, comprising 705, 50, and 250 images, respectively. Ground truth labels are provided only for the training data, while the validation data is provided without associated ground truth, and the testing data is kept hidden from participants. But, now all the ground truth data is available for researchers.
 
 Note: The datasets are fully identical to the data used for our baseline method, named HierarchicalDet. Therefore, please visit the [MICCAI paper](https://conferences.miccai.org/2023/papers/205-Paper2550.html) and the [GitHub repository](https://github.com/ibrahimethemhamamci/DENTEX) of HierarchicalDet (Diffusion-Based Hierarchical Multi-Label Object Detection to Analyze Panoramic Dental X-rays) for more info.