Update app.py

app.py

@@ -33,20 +33,7 @@ def stream_data(value1,path,value2):
     
 
 disease_classes = ['COPD','Healthy', 'Other']
-import base64
 
-background_image = """
-<style>
-[data-testid="stAppViewContainer"] > .main {
-    background-image: url("https://drive.usercontent.google.com/download?id=1zlU0ccwqMWiJON5NnPuD_WrcnJB084GD");
-    background-size: 100vw 100vh;  # This sets the size to cover 100% of the viewport width and height
-    background-position: center;  
-    background-repeat: no-repeat;
-}
-</style>
-"""
-
-st.markdown(background_image, unsafe_allow_html=True)
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 processor = AutoProcessor.from_pretrained("MIT/ast-finetuned-audioset-10-10-0.4593")
 model = ASTModel.from_pretrained("MIT/ast-finetuned-audioset-10-10-0.4593")# audio file is decoded on the fly
@@ -76,6 +63,21 @@ def extract_features(path, device):
     last_hidden_states = outputs.last_hidden_state.squeeze().mean(axis=0).to("cpu").numpy()
     return last_hidden_states
 
+
+
+
+background_image = """
+<style>
+[data-testid="stAppViewContainer"] > .main {
+    background-image: url("https://i.imghippo.com/files/VPJrh1723986413.jpg");
+    background-size: 100vw 100vh;  # This sets the size to cover 100% of the viewport width and height
+    background-position: center;  
+    background-repeat: no-repeat;
+}
+</style>
+"""
+
+st.markdown(background_image, unsafe_allow_html=True)
 st.title('One-Step Respiratory Disease Classifier using Digital Stethoscope Sound')