Update README.md

README.md

@@ -25,24 +25,35 @@ for result in results:
     result.show()
 ```
 
+## ✅ Supported Classes (Labels)
+
+The model can detect and distinguish between the following three states:
+```python
+Falling: Active falling motion or a person on the ground after a fall.
+
+Sitting: People sitting on chairs, benches, or floor.
+
+Standing: People in an upright, standing position.
+```
+
 ## 📊 Model Information
 ```python
-    Architecture: YOLOv11 (Ultralytics)
+Architecture: YOLOv11 (Ultralytics)
 
-    Task: Object Detection (Fall Detection)
+Task: Object Detection (Fall Detection)
 
-    Input Resolution: 640x640 pixels
+Input Resolution: 640x640 pixels
 
-    Inference Speed: Optimized for real-time applications
+Inference Speed: Optimized for real-time applications
 ```
 
 ## 🎯 Target Applications
 ```python
-    Elderly Safety: Automated fall detection for home or nursing home environments.
+Elderly Safety: Automated fall detection for home or nursing home environments.
 
-    Occupational Health: Monitoring falls in hazardous work zones or construction sites.
+Occupational Health: Monitoring falls in hazardous work zones or construction sites.
 
-    Healthcare Support: Providing an extra layer of monitoring for patient rooms.
+Healthcare Support: Providing an extra layer of monitoring for patient rooms.
 ```
 
 ## 🛠 Training Details