Update README.md

README.md

@@ -92,7 +92,7 @@ size_categories:
 <!-- Provide a quick summary of the dataset. -->
 
 This is the version of the SelvaBox dataset that has been pre-processed and presented in our SelvaBox paper.
-The dataset is made of 14 rasters resampled at 4.5 cm GSD, from three different countries: Brazil, Ecuador and Panama. It comprises over 83 000 human bounding box annotations for tropical tree crowns in dense canopies.
+The dataset is made of 14 rasters resampled at 4.5 cm GSD, from three different countries: Brazil, Ecuador and Panama. These rasters were tiled into more than 2400 images. It comprises over 83 000 unique human bounding box annotations for tropical tree crowns in dense canopies.
 
 ## Dataset Details
 
@@ -103,6 +103,7 @@ The dataset is made of 14 rasters resampled at 4.5 cm GSD, from three different
 Training tiles are 3555x3555 pixels, while validation and test tiles are 1777x1777 pixels, equivalent to 80x80 meters spatial extent. There is 50% overlap between train and validation tiles, and 75% between test tiles (to ensure that the largest trees of 50+ meters in diameter will fit entirely in at least one tile).
 The table below summarizes the information on the three splits. Note that the # Annotations reported is larger than 83000 due to the overlap between tiles, which duplicates annotations. 
 There is also a similar effect regarding the # Tiles: there are more test tiles than train or valid but that's because of the 75% overlap between tiles, compared to 50%.
+The 'Geographic Area % of total dataset column' more accurately describes how much data was assigned to each split.
 
 | Split | Tile Size (px) | Tile Size (m) | Overlap | # Tiles | # Annotations | Geographic Area % of total dataset|
 | ----- | -------------- | ------------- | ------- | ------- | ------------- | ------------------- |