Update README.md

README.md

@@ -22,10 +22,36 @@ The Fruits30 dataset is a collection of images featuring 30 different types of f
 - **Total Images:** 856
 
 ## Classes:
-1. Apple
-2. Banana
-3. Orange
-4. 
+"0" : "acerolas"  
+"1" : "apples"  
+"2" : "apricots"  
+"3" : "avocados"  
+"4" : "bananas"  
+"5" : "blackberries",
+"6" : "blueberries",
+"7" : "cantaloupes",
+"8" : "cherries",
+"9" : "coconuts",
+"10" : "figs",
+"11" : "grapefruits",
+"12" : "grapes",
+"13" : "guava",
+"14" : "kiwifruit",
+"15" : "lemons",
+"16" : "limes",
+"17" : "mangos",
+"18" : "olives",
+"19" : "oranges",
+"20" : "passionfruit",
+"21" : "peaches",
+"22" : "pears",
+"23" : "pineapples",
+"24" : "plums",
+"25" : "pomegranates",
+"26" : "raspberries",
+"27" : "strawberries",
+"28" : "tomatoes",
+"29" : "watermelons"
 
 ## Preprocessing:
 Images have undergone preprocessing to maintain consistency and facilitate model training. Preprocessing steps may include resizing, normalization, and other enhancements.
@@ -34,7 +60,7 @@ Images have undergone preprocessing to maintain consistency and facilitate model
 The Fruits30 dataset is suitable for tasks such as image classification, object recognition, and machine learning model training within the domain of fruit identification.
 
 ## Sources:
-Include any relevant sources or references regarding the dataset's origin or licensing.
+Croudsource.
 
 ## Note:
 Ensure proper attribution and compliance with the dataset's licensing terms when using it for research or development purposes.