Update README.md

README.md

@@ -121,9 +121,19 @@ This means:
 - The model is usually correct when it makes predictions  
 - It misses many objects especially harder or less frequent ones  
 
-Performance varied significantly across classes. Common classes such as "Vehicle" achieved higher precision and recall, while underrepresented classes like "Bicycle" and "Car" performed poorly due to limited training samples.
+Common classes such as "Vehicle" achieved higher precision and recall, while underrepresented classes like "Bicycle" and "Car" performed poorly due to limited training samples.
 This made it so that the performance differences across classes were influenced by class imbalance, with larger classes performing more reliably.
 
+Performance varied across classes, as shown in the table below:
+
+| Class | Relative Performance |
+|------|--------------------|
+| Vehicle | High |
+| Bicycle Lane | Moderate |
+| Shared Lane | Moderate |
+| Cyclist | Low |
+| Bicycle | Very Low |
+
 ---
 
 ### Example Predictions