Update app.py

app.py

@@ -381,6 +381,8 @@ def build_ui():
             f"""
             # Amaze
             Dataset: https://huggingface.co/datasets/piekenius123/Amaze  
+            Amaze is a benchmark for Edting-as-Reasoning task (EAR). It features four maze shapes: circle, hexagon, square, and triangle. Each sample provides: an unmarked maze image (original_img), a maze image with start and end points marked (m_original_img), a blue solution path image (sol_img), a binary path mask (mask_img), a cell segmentation map (cell_map), and metadata (JSON) for describing the maze structure and difficulty.
+            The test set covers various sizes from 3×3 to 16×16 (50 samples for each size), while the training set mainly consists of 3×3 mazes (1024 samples), and validation set consists of 3×3 mazes (256 samples). 
             Browse samples by **shape / split / maze size**, then view images + metadata.
             """
         )