Update app.py

app.py

@@ -83,9 +83,11 @@ i = gr.inputs.Image(shape=(112, 112))
 o = gr.outputs.Image()
 
 examples = [["img1.jpg"], ["img2.jpg"]]
-title = None #"Left Ventricle Segmentation"
+title = "Example: Echocardiogram Segmentation" #"Left Ventricle Segmentation"
 description = "This semantic segmentation model identifies the left ventricle in echocardiogram images."
 # videos. Accurate evaluation of the motion and size of the left ventricle is crucial for the assessment of cardiac function and ejection fraction. In this interface, the user inputs apical-4-chamber images from echocardiography videos and the model will output a prediction of the localization of the left ventricle in blue. This model was trained on the publicly released EchoNet-Dynamic dataset of 10k echocardiogram videos with 20k expert annotations of the left ventricle and published as part of ‘Video-based AI for beat-to-beat assessment of cardiac function’ by Ouyang et al. in Nature, 2020."
 thumbnail = "https://raw.githubusercontent.com/gradio-app/hub-echonet/master/thumbnail.png"
+
+article = "<div style='text-align: center;'><a href='https://pubmed.ncbi.nlm.nih.gov/31993508/' target='_blank'>Deep learning interpretation of echocardiograms</a> | <center><img src='https://visitor-badge.glitch.me/badge?page_id=example_space_cvpr' alt='visitor badge'></center></div>"
 gr.Interface(segment, i, o, examples=examples, allow_flagging=False, analytics_enabled=False,
-	title=title, description=description, thumbnail=thumbnail).launch()
+	title=title, description=description, thumbnail=thumbnail,article=article).launch(enable_queue=True)