Update app.py

app.py

@@ -60,8 +60,8 @@ if __name__ == "__main__":
         
         width, height = gold_standard_img.size
       
-        gold_standard_img.save('gold_standard.png', dpi=(600, 600), quality=95)
-        best_parse_img.save('best_parse.png', dpi=(600, 600), quality=95)
+        gold_standard_img.save('gold_standard.png')
+        best_parse_img.save('best_parse.png')
         
         gold_standard_img_png = Image.open("gold_standard.png")
         best_parse_img_png = Image.open("best_parse.png")
@@ -74,7 +74,7 @@ if __name__ == "__main__":
         description="Demo for the repository - [weakly-supervised-parsing](https://github.com/Nickil21/weakly-supervised-parsing) (ACL Findings 2022)",
         theme="default",
         article="""<h4 class='text-lg font-semibold my-2'>Note</h4>
-        - We use a strong supervised parsing model `benepar_en3` which is based on T5-small to compute the gold parse.<br>
+        - We use a strong supervised parsing model `benepar_en3` which is based on T5-small to compute the reference parse.<br>
         - Sentence F1 score corresponds to the macro F1 score.
         """,
         allow_flagging="never",
@@ -84,7 +84,7 @@ if __name__ == "__main__":
             gradio.inputs.Radio(["inside", "outside", "inside-outside"], default="inside", label="Choose Model"),
         ],
         outputs=[
-            gradio.outputs.Image(label="Gold Parse Tree", type="pil"),
+            gradio.outputs.Image(label="Reference Parse Tree (BeNePar)", type="pil"),
             gradio.outputs.Image(label="Predicted Parse Tree", type="pil"),
             gradio.outputs.Textbox(label="F1 score"),
         ],