Update app.py

app.py

@@ -26,13 +26,12 @@ detected_people_history = deque(maxlen=MAX_HISTORY)
 
 DISTANCE_THRESHOLD = 30  # cm
 
-
 @app.post("/detect")
 async def detect_faces(file: UploadFile = File(...)):
     # Read the image and decode it efficiently
     contents = await file.read()
     image_np = np.frombuffer(contents, np.uint8)
-    frame = cv2.imdecode(image_np, cv2.IMREAD_REDUCED_COLOR_2)  # Faster decoding
+    frame = cv2.imdecode(image_np, cv2.IMREAD_COLOR)  # Decode image correctly
 
     # Resize frame for faster inference
     h, w, _ = frame.shape
@@ -45,7 +44,7 @@ async def detect_faces(file: UploadFile = File(...)):
     change_detected = False
     person_id = 1
 
-    frame_width = resized_frame.shape[1]
+    frame_width = frame.shape[1]  # Use the original frame width
 
     for result in results:
         for box in result.boxes.data.tolist():  # Convert tensor to list
@@ -56,7 +55,7 @@ async def detect_faces(file: UploadFile = File(...)):
                 center_x = (x1 + x2) // 2
                 face_width_pixels = x2 - x1
 
-                # Determine position (Left, Center, Right)
+                # Determine position (Left, Center, Right) using original frame width
                 if center_x < frame_width // 3:
                     position = "Left"
                 elif center_x > 2 * frame_width // 3:
@@ -96,3 +95,5 @@ async def detect_faces(file: UploadFile = File(...)):
     else:
         return {"people": []}  # No significant change detected
 
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=8000)