Added examples

app.py

@@ -25,6 +25,7 @@ def predict_image(img):
 image = gr.inputs.Image(shape=(224, 224))
 label = gr.outputs.Label(num_top_classes=3)
 article="<p style='text-align: center; font-weight:bold;'>Model based on the VGG-16 CNN</p>"
+examples = ['battery.jpeg', 'clothes.jpeg', 'plastic.jpg']
 
 gr.Interface(fn=predict_image, inputs=image,  title="Garbage Classifier VGG-16",
-    description="This is a Garbage Classification Model Trained using VGG-16 architecture. Deployed to Hugging Face using Gradio.", outputs=label, article=article, enable_queue=True, interpretation='default').launch(share="True")
+    description="This is a Garbage Classification Model Trained using VGG-16 architecture. Deployed to Hugging Face using Gradio.", outputs=label, examples=examples, article=article, enable_queue=True, interpretation='default').launch(share="True")