Update app.py

app.py

@@ -7,17 +7,32 @@ import gradio as gr
 # model = Yolov4(weight_path="best.pt", class_name_path='coco_classes.txt')
 
 
-from ultralytics import YOLO
+# from ultralytics import YOLO
 
 # Load a model
-model = YOLO("best.pt")  # load a custom model
+# model = YOLO("best.pt")  # load a custom model
 
 # Predict with the model
 # results = model("image.jpg", save = True)  # predict on an image
 
+face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
 
-def gradio_wrapper(img):
-    global model
+def detect_faces(frame):
+    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
+    print(f"Detected {len(faces)} faces")
+    return len(faces)
+
+def detect_faces_in_video():
+    success, frame = camera.read()
+    if success:
+        num_faces = detect_faces(frame)
+        return int(num_faces)
+    else:
+        return None
+
+"""def gradio_wrapper(img):
+    global face_cascade
     #print(np.shape(img))
     results = model.predict(img)  # predict on an image
     try:
@@ -31,9 +46,11 @@ def gradio_wrapper(img):
     return cv2.putText(img, text,(00, 185), cv2.FONT_HERSHEY_SIMPLEX, 1, 
                   (0, 0, 255),  2, cv2.LINE_AA, False)
     # return results
+
+"""
   
 demo = gr.Interface(
-    gradio_wrapper,
+    detect_faces_in_video,
     #gr.Image(source="webcam", streaming=True, flip=True),
     gr.Image(source="webcam", streaming=True),
     "image",