Update app.py

app.py

@@ -1,13 +1,36 @@
 import gradio as gr
+import cv2
+import numpy as np
 
-def snap(image, video):
-    return [video]
+# Load the pre-trained Haar Cascade classifier for face detection
+face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
 
+def detect_faces(image, video):
+    # Read the video frame-by-frame
+    frame = video
+
+    # Convert the frame to an OpenCV-compatible format
+    if isinstance(frame, np.ndarray):
+        # Convert to grayscale for face detection
+        gray = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)
+
+        # Perform face detection
+        faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))
+
+        # Draw rectangles around detected faces
+        for (x, y, w, h) in faces:
+            cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
+
+    return [frame]
+
+# Gradio interface setup for face detection on live video feed
 demo = gr.Interface(
-    snap,
-    [gr.Video(sources=["webcam"])],
+    detect_faces,
+    [gr.Image(), gr.Video(sources=["webcam"])],
     ["video"],
+    title="Live Webcam Face Detection",
+    description="Displays the live feed from your webcam and detects faces in real-time."
 )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()