app.py

app.py

@@ -312,4 +312,4 @@ output = gr.outputs.Image(type="pil", label="Detected Objects with Class Categor
 title = "Object Detection With RetinaNet"
 description = "Upload an Image or take one from examples to localize objects present in an image, and at the same time, classify them into different categories"
 
-gr.Interface(fn=predict, inputs = input, outputs = output, examples=coco_image, allow_flagging=False, analytics_enabled=False, title=title, description=description, article="Space By: <u><a href='https://github.com/robotjellyzone'><b>Kavya Bisht</b></a></u> \n Based on notebook <a href='https://keras.io/examples/vision/retinanet/'><b>this notebook</b></a>").launch(enable_queue=True, debug=True)
+gr.Interface(fn=predict, inputs = input, outputs = output, examples=coco_image, allow_flagging=False, analytics_enabled=False, title=title, description=description, article="<center>Space By: <u><a href='https://github.com/robotjellyzone'><b>Kavya Bisht</b></a></u> \n Based on notebook <a href='https://keras.io/examples/vision/retinanet/'><b>this notebook</b></a></center>").launch(enable_queue=True, debug=True)