Update app.py

app.py

@@ -7,11 +7,11 @@ from PIL import Image
 import numpy as np
 from transformers import pipeline
 
+
 pipe = pipeline("image-classification", model="NTQAI/pedestrian_gender_recognition")
 model_path = hf_hub_download(repo_id="arnabdhar/YOLOv8-Face-Detection", filename="model.pt")
 model = YOLO(model_path)
 
-
 def detect_faces(image):
     output = model(image)
     results = Detections.from_ultralytics(output[0])
@@ -20,8 +20,6 @@ def detect_faces(image):
     for i in results:
         im = cv2.rectangle(im, (int(i[0][0]),int(i[0][1])), (int(i[0][2]),int(i[0][3])), (0,0,255), 2)
 
-    label_out = pipe(image)
-
     image_np = np.array(image)
     gray_image = cv2.cvtColor(image_np, cv2.COLOR_RGB2GRAY)
     face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_frontalface_default.xml")
@@ -29,6 +27,8 @@ def detect_faces(image):
     for (x, y, w, h) in faces:
         cv2.rectangle(image_np, (x, y), (x+w, y+h), (0, 255, 0), 2)
     
+    label_out = pipe(image)
+    
     return (image_np,im,label_out[0]['label'])
 
 interface = gr.Interface(