Update app.py

app.py

@@ -1,26 +1,36 @@
 import cv2
 import numpy as np
 import streamlit as st
-
 from camera_input_live import camera_input_live
 
-"# Streamlit camera input live Demo"
-"## Try holding a qr code in front of your webcam"
+# Load Haarcascade for face detection
+cascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
+
+# Streamlit app title
+st.title("Live Object Detection with Camera")
+st.subheader("Hold your face in front of the webcam to see real-time detection.")
 
+# Capture live camera input
 image = camera_input_live()
 
 if image is not None:
-    st.image(image)
+    # Display the captured image
+    st.image(image, caption="Live Camera Input", use_column_width=True)
+
+    # Convert the image to OpenCV format
     bytes_data = image.getvalue()
     cv2_img = cv2.imdecode(np.frombuffer(bytes_data, np.uint8), cv2.IMREAD_COLOR)
 
-    detector = cv2.QRCodeDetector()
+    # Convert to grayscale for face detection
+    gray = cv2.cvtColor(cv2_img, cv2.COLOR_BGR2GRAY)
+
+    # Detect faces in the image
+    faces = cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=3)
 
-    data, bbox, straight_qrcode = detector.detectAndDecode(cv2_img)
+    # Draw rectangles around detected faces
+    for (x, y, w, h) in faces:
+        cv2.rectangle(cv2_img, (x, y), (x + w, y + h), (0, 255, 0), 3)
+        cv2.putText(cv2_img, "Face", (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 255, 0), 2)
 
-    if data:
-        st.write("# Found QR code")
-        st.write(data)
-        with st.expander("Show details"):
-            st.write("BBox:", bbox)
-            st.write("Straight QR code:", straight_qrcode)
+    # Display the annotated image
+    st.image(cv2_img, channels="BGR", caption="Detected Faces", use_column_width=True)