Update app.py

app.py

@@ -6,7 +6,7 @@ import os
 
 ## Where to store flagged data
 HF_TOKEN = os.getenv('HF_TOKEN')
-hf_writer = gr.HuggingFaceDatasetSaver(HF_TOKEN, "Crowd-sourced images")
+hf_writer = gr.HuggingFaceDatasetSaver(HF_TOKEN, "Crowd sourced images")
 
 # Load your trained model
 model = YOLO('best.pt')
@@ -68,7 +68,8 @@ platform = gr.Interface( fn = predict,
                         providing an additional layer of analysis for consideration in conjunction with the clinician's expertise. 
                         Users are encouraged to interpret the algorithm's output in conjunction with their clinical judgment, 
                         and the tool should be viewed as a supplementary resource rather than a standalone diagnostic solution.
-                        """ )
+                        """,
+                       thumbnail = "thumbnail.jpg")
 
 
 platform.launch(inline=True,share=True)