Update app.py

app.py

@@ -1,41 +1,33 @@
 import gradio as gr
-import mediapipe as mp
 import numpy as np
+from ultralytics import YOLO
 
-mp_face = mp.solutions.face_detection
-face_detection = mp_face.FaceDetection(model_selection=0, min_detection_confidence=0.5)
+# Use lightweight face model
+model = YOLO("yolov8n.pt")  # lightweight model
 
 def detect_faces(image):
     image_np = np.array(image)
-    results = face_detection.process(image_np)
 
-    faces = []
-
-    if results.detections:
-        for detection in results.detections:
-            bbox = detection.location_data.relative_bounding_box
+    results = model(image_np)
 
-            h, w, _ = image_np.shape
-
-            xmin = int(bbox.xmin * w)
-            ymin = int(bbox.ymin * h)
-            width = int(bbox.width * w)
-            height = int(bbox.height * h)
+    faces = []
 
-            xmax = xmin + width
-            ymax = ymin + height
+    for r in results:
+        boxes = r.boxes.xyxy.cpu().numpy()
 
+        for box in boxes:
+            xmin, ymin, xmax, ymax = box
             cx = (xmin + xmax) / 2
             cy = (ymin + ymax) / 2
 
             faces.append({
-                "cx": cx,
-                "cy": cy,
+                "cx": float(cx),
+                "cy": float(cy),
                 "box": {
-                    "xmin": xmin,
-                    "ymin": ymin,
-                    "xmax": xmax,
-                    "ymax": ymax
+                    "xmin": float(xmin),
+                    "ymin": float(ymin),
+                    "xmax": float(xmax),
+                    "ymax": float(ymax)
                 }
             })