Update README.md

README.md

@@ -40,7 +40,7 @@ tags:
 
 
 ### Dataset Summary
-The dataset contains over 18,000 images of homes damaged by wildfire between 2020 and 2022 in California, USA, captured by the California Department of Forestry and Fire Protection (Cal Fire) during the damage assessment process. The dataset spans across more than 18 wildfire events, including the 2020 August Complex Fire, the first recorded "gigafire" event in California where the area burned exceeded 1 million acres. Each image, corresponding to a built structure, is classified by government damage assessors into 5 different categories: No Damage, Affected (1-9%), Minor (10-25%), Major (26-50%), and Destroyed (>50%). While over 57,000 structures were evaluated during the damage assessment process, only about 18,000 contains images; additional data about the structures, such as the street address or structure materials, for both those with and without corresponding images can be accessed in the "Additional Attribute Data" file.
+The dataset contains over 18,000 images of homes damaged by wildfire between 2020 and 2022 in California, USA, captured by the California Department of Forestry and Fire Protection (Cal Fire) during the damage assessment process. The dataset spans across more than 18 wildfire events, including the 2020 August Complex Fire, the first recorded "gigafire" event in California where the area burned exceeded 1 million acres. Each image, corresponding to a built structure, is classified by government damage assessors into 6 different categories: Inaccessible (image taken but no assessment made), No Damage, Affected (1-9%), Minor (10-25%), Major (26-50%), and Destroyed (>50%). While over 57,000 structures were evaluated during the damage assessment process, only about 18,000 contains images; additional data about the structures, such as the street address or structure materials, for both those with and without corresponding images can be accessed in the "Additional Attribute Data" file.
 
 The 18 wildfire events captured in the dataset are:
 
@@ -80,9 +80,10 @@ Class Label Mappings:
 {
   "affected": 0,
   "destroyed": 1,
-  "major": 2,
-  "minor": 3,
-  "no_damage": 4,
+  "inaccessible": 2,
+  "major": 3,
+  "minor": 4,
+  "no_damage": 5,
 }
 ```