Added some changes

app.py

@@ -59,21 +59,16 @@ eval_col4.metric("mAP 0.5:0.95", "62.63%")
 uploaded_file = st.file_uploader("Choose a ship imagery")
 if uploaded_file is not None:
     st.image(uploaded_file, caption='Image to predict')
-    folder_path = st.text_input("Image path")
+    folder_path = st.text_input("Image path",
+                                help="This field the image path field that the model will predict the object inside the image that we have uploaded",
+                                placeholder="Copy the path of image to this field")
 
 prediction = st.button("Predict")
 if prediction:
     ship_model = torch.hub.load('ultralytics/yolov5', 'custom', path="best.pt", force_reload=True)
-    # results = ship_model(f"C:/Users/bilva/YOLOv5/ship_test/{uploaded_file.name}")
     results = ship_model(f"{folder_path}")
     with st.spinner("Loading..."):
         time.sleep(3.5)
         st.success("Done!")
     st.image(np.squeeze(results.render()))
     results.print()
-    # with st.echo():
-    #     st.text(f"results.print()")
-    # st.markdown(results.print())
-    # for percent_progress in range (100):
-    #     time.sleep(0.1)
-    #     progress.progress(percent_progress + 1)