Create app.py

app.py

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+import cv2
+import gradio as gr
+import numpy as np
+
+# Load Haar cascade
+face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
+
+def detect_faces(image, scale):
+    gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
+    faces = face_cascade.detectMultiScale(gray, scale, 4)
+    for (x, y, w, h) in faces:
+        cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2)
+    return image
+
+iface = gr.Interface(
+    fn=detect_faces,
+    inputs=[
+        gr.Image(type="numpy", label="Upload Image"),
+        gr.Slider(1.00, 2.00, value=1.1, step=0.01, label="Scale Factor"),
+    ],
+    outputs=gr.Image(type="numpy", label="Detected Faces"),
+    title="Face Detection with Haar Cascade",
+    description="Adjust the scale factor using the slider to improve face detection accuracy or speed."
+)
+
+iface.launch()