Create app.py

app.py

@@ -0,0 +1,43 @@
+import gradio as gr
+import face_recognition
+import numpy as np
+from PIL import Image, ImageDraw
+
+def recognize_faces(image):
+    # Convert uploaded image to RGB
+    image_rgb = np.array(image.convert("RGB"))
+
+    # Detect face locations and encodings
+    face_locations = face_recognition.face_locations(image_rgb)
+    face_encodings = face_recognition.face_encodings(image_rgb, face_locations)
+
+    # Draw bounding boxes
+    pil_image = Image.fromarray(image_rgb)
+    draw = ImageDraw.Draw(pil_image)
+
+    for (top, right, bottom, left), face_encoding in zip(face_locations, face_encodings):
+        name = "Unknown"  # Placeholder — can later be replaced with real matching logic
+
+        # Draw box
+        draw.rectangle(((left, top), (right, bottom)), outline=(0, 255, 0), width=3)
+
+        # Label below the face
+        text_width, text_height = draw.textsize(name)
+        draw.rectangle(((left, bottom - text_height - 10), (right, bottom)), fill=(0, 255, 0))
+        draw.text((left + 6, bottom - text_height - 5), name, fill=(0, 0, 0))
+
+    del draw
+    return pil_image
+
+
+# Gradio Interface
+demo = gr.Interface(
+    fn=recognize_faces,
+    inputs=gr.Image(type="pil", label="Upload an image"),
+    outputs=gr.Image(label="Detected Faces"),
+    title="Face Recognition (Future-Ready)",
+    description="Uploads an image, detects faces, and labels them as Unknown. Can be extended for identity recognition later.",
+)
+
+if __name__ == "__main__":
+    demo.launch()