Update app.py

app.py

@@ -18,11 +18,17 @@ REF_IMAGE_FACE_WIDTH = 120  # pixels
 FOCAL_LENGTH = (REF_IMAGE_FACE_WIDTH * KNOWN_DISTANCE) / KNOWN_FACE_WIDTH
 SCALING_FACTOR = 2.0  # Adjust based on real-world testing
 
+# Previous state storage
+previous_people = {}
+THRESHOLD_DISTANCE_CHANGE = 50  # cm
+
 # Function to Process Frame & Detect Faces
 def process_frame(image: np.ndarray) -> List[Dict]:
+    global previous_people
     results = model(image)
     frame_width = image.shape[1]
-    people = []
+    current_people = {}
+    detected_people = []
     
     for idx, result in enumerate(results):
         for i, box in enumerate(result.boxes):
@@ -48,14 +54,34 @@ def process_frame(image: np.ndarray) -> List[Dict]:
                 else:
                     estimated_distance = -1  # Error case
                 
-                people.append({
-                    f"person{i+1}": {
-                        "distance": round(estimated_distance, 1),
-                        "position": position
-                    }
-                })
+                person_id = f"person{i+1}"
+                current_people[person_id] = {
+                    "distance": round(estimated_distance, 1),
+                    "position": position
+                }
+    
+    # Compare with previous state
+    if previous_people:
+        changes_detected = False
+        for person_id, data in current_people.items():
+            prev_data = previous_people.get(person_id)
+            if not prev_data or abs(prev_data["distance"] - data["distance"]) > THRESHOLD_DISTANCE_CHANGE or prev_data["position"] != data["position"]:
+                changes_detected = True
+                break
+        
+        # Check if any person entered or left
+        if set(current_people.keys()) != set(previous_people.keys()):
+            changes_detected = True
+        
+        if not changes_detected:
+            return []
+    
+    previous_people = current_people.copy()
+    
+    for person_id, data in current_people.items():
+        detected_people.append({person_id: data})
     
-    return people
+    return detected_people
 
 @app.post("/detect")
 async def detect_faces(file: UploadFile = File(...)):