Update app.py

app.py

@@ -60,7 +60,7 @@ examples = [
 demo_mask = gr.Interface(fn=inference_mask1, 
                    inputs=[gr.ImageMask(brush_radius=8, label="prompt (提示图)"), gr.Image(label="img1 (测试图1)"), gr.Image(label="img2 (测试图2)")], 
                     #outputs=[gr.Image(shape=(448, 448), label="output1 (输出图1)"), gr.Image(shape=(448, 448), label="output2 (输出图2)")],
-                    outputs=[gr.Image(label="output1 (输出图1)").style(height=384, width=384), gr.Image(label="output2 (输出图2)").style(height=384, width=384)],
+                    outputs=[gr.Image(label="output1 (输出图1)").style(height=224, width=224), gr.Image(label="output2 (输出图2)").style(height=224, width=224)],
                     #outputs=gr.Gallery(label="outputs (输出图)"),
                     examples=examples,
                     #title="SegGPT for Any Segmentation<br>(Painter Inside)",
@@ -69,7 +69,8 @@ demo_mask = gr.Interface(fn=inference_mask1,
                     Or, upload by yourself: <br>\
                     1. Upload images to be tested to 'img1' and/or 'img2'. <br>2. Upload a prompt image to 'prompt' and draw a mask.  <br>\
                             Tips: The more accurate you annotate, the more accurate the model predicts.;) <br>\
-                            💎： Examples below were never trained and are randomly selected for testing in the wild. <br>\
+                            <br> \
+                            💎: Examples below were never trained and are randomly selected for testing in the wild. <br>\
                             💎: Current UI interface just unleashes a small part of the capabilities of SegGPT, i.e., 1-shot case. \
 </p>",
                    cache_examples=False,