Updated

app.py

@@ -51,4 +51,8 @@ if choice == 'Detection':
             preds = tokenizer.batch_decode(output_ids, skip_special_tokens=True)
             preds = [pred.strip() for pred in preds]
             return preds
-        st.success(predict_step(our_image))
+        st.success(predict_step(our_image))
+elif choice == 'About':
+	st.subheader("About Image Captioning App")
+	st.markdown("Built with Streamlit by [Soumen Sarker](https://soumen-sarker-personal-site.streamlit.app/)")
+	st.markdown("Demo applicaton of the following model [credit](https://huggingface.co/nlpconnect/vit-gpt2-image-captioning/)")