Update app.py

app.py

@@ -12,7 +12,7 @@ model = AutoModelForImageClassification.from_pretrained("Amite5h/convnext-tiny-f
 
 st.title("EuroSAT Detection")
 
-file_name = st.file_uploader("Upload a hot dog candidate image")
+file_name = st.file_uploader("Upload a geospatial image")
 
 if file_name is not None:
     col1, col2 = st.columns(2)
@@ -25,7 +25,7 @@ if file_name is not None:
     image_tensor = extractor(images=image, return_tensors="pt")["pixel_values"]
     predictions = model(image_tensor)
 
-    predicted_probabilities = torch.softmax(outputs.logits, dim=1)[0]
+    predicted_probabilities = torch.softmax(predictions.logits, dim=1)[0]
     predicted_labels = model.config.id2label
     
     # Create a dictionary of labels and probabilities