Create app.py

app.py

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+import streamlit as st
+import cv2
+import numpy as np
+
+def detect_face(image):
+    face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
+    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+    faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))
+    for (x, y, w, h) in faces:
+        cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2)
+    return image
+
+st.title("Face Detection App")
+
+uploaded_image = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
+if uploaded_image is not None:
+    image = cv2.imdecode(np.fromstring(uploaded_image.read(), np.uint8), 1)
+    st.image(image, caption="Uploaded Image", use_column_width=True)
+    
+    if st.button("Detect Faces"):
+        result_image = detect_face(image)
+        st.image(result_image, caption="Image with Detected Faces", use_column_width=True)
+
+st.write("This is a simple face detection app using Streamlit and OpenCV.")