Update app.py

app.py

@@ -30,13 +30,26 @@ def classify_mammogram(img):
 
 # Streamlit app
 st.title("Breast Cancer Detection App")
-st.write("Upload an image of a mammogram(an x-ray image of the breast), and the model will predict whether it is benign or malignant.")
+st.write("Upload an image of a mammogram(an X-ray image of the breast), and the model will predict whether it is benign or malignant.")
+
+
+uploaded_file = st.file_uploader("Upload an image...", type=["jpg", "jpeg", "png"])
+
+if uploaded_file is not None:
+    image = Image.open(uploaded_file)
+    st.image(image, caption='Uploaded Image.', use_column_width=True)
+    st.write("Classifying...")
+    
+    classification_result = classify_mammogram(image)
+    st.write(classification_result)
+
 st.write(
     """
     <div style='display: flex; justify-content: space-between;'>
         <div style='width: 48%;'>
             <p style='font-size: 18px; font-weight: bold;'>Malignant</p>
             <p style='font-size: 16px;'>
+                Definition: very virulent or infectious.
                 Non-suspicious: The AI is confident that no suspicious signs are present.<br>
                 High risk: The AI is confident that the results are highly suspicious.<br>
                 Indeterminate: The AI is uncertain and not confident in making a definitive classification.
@@ -45,6 +58,7 @@ st.write(
         <div style='width: 48%;'>
             <p style='font-size: 18px; font-weight: bold;'>Benign</p>
             <p style='font-size: 16px;'>
+                Definition: Not harmful in effect
                 Suspicious: AI is not that confident. Further Supervision is needed.<br>
                 Non-Suspicious: AI is confident that there is nothing to worry about.<br>
                 No Risk: AI is confident. No direct supervision is needed.
@@ -55,16 +69,6 @@ st.write(
     unsafe_allow_html=True
 )
 
-uploaded_file = st.file_uploader("Upload an image...", type=["jpg", "jpeg", "png"])
-
-if uploaded_file is not None:
-    image = Image.open(uploaded_file)
-    st.image(image, caption='Uploaded Image.', use_column_width=True)
-    st.write("Classifying...")
-    
-    classification_result = classify_mammogram(image)
-    st.write(classification_result)
-
 # Educational content
 st.markdown("### Learn More About Breast Cancer")
 st.markdown("""