Update app.py

app.py

@@ -37,7 +37,7 @@ BASE_LOCATION = [0, 23]
 RULES = """<h1 style="margin-bottom: 0.5em">OSV-5M (plonk)</h1>
 <center style="margin-bottom: 1em; margin-top: 1em"><img width="256" alt="Rotating globe" src="https://upload.wikimedia.org/wikipedia/commons/6/6b/Rotating_globe.gif"></center>
 <h2 style="margin-top: 0.5em"> Instructions </h2>
-<h3 style="margin-bottom: 0.5em"> Click on the map 🗺️ (left) to the location at which you think the image 🖼️ (right) was captured!<br>Click "Select" to finalize your selection and then "Next" to move to the next image.</h3>
+<h3 style="margin-bottom: 0.5em"> Click at the location 🗺️ (left) where you think the image 🖼️ (right) was captured!<br>Click "Select" to finalize your selection and then "Next" to move to the next image.</h3>
 
 <h2> AI Competitors </h2>
 <h3 style="margin-bottom: 0.5em"> You will compete against two AIs: <b>Plonk-AI</b> (our best model) and Baseline-AI (a simpler approach).<br> These AIs have not been trained on any of the images you will see; in fact, they haven't seen anything within a <b>1km radius</b> of them.<br> Like you, the AIs will need to pick up on geographic clues to pinpoint the locations of the images.</h3>
@@ -562,7 +562,7 @@ if __name__ == "__main__":
         with gr.Row():
             select_button = gr.Button("Select", elem_id='latlon_btn', visible=False)
             next_button = gr.Button("Next", visible=False, elem_id='next')
-        perf = gr.Dataframe(value=None, visible=False, label='Average Performance')
+        perf = gr.Dataframe(value=None, visible=False, label='Average Performance (so far)')
         text_end = gr.Markdown("", visible=False)
     
         coords = gr.Textbox(value="-1", label="Latitude, Longitude", visible=False, elem_id='coords-tbox')