GUI Finalized

app.py

@@ -23,7 +23,7 @@ def predict_single_image(image_path, model, target_size=(128, 128)):
     # display(probabilities)
 
     # Determine the predicted class label
-    predicted_class = "positive" if probabilities[0][0] > 0.5 else "negative"
+    predicted_class = "POSITIVE" if probabilities[0][0] > 0.5 else "NEGATIVE"
 
     return predicted_class, probabilities[0][0]
 
@@ -38,23 +38,35 @@ def classify_lung_cancer(img):
     # Print the prediction
     # print('Predicted Label:', predicted_label)
     # print('Confidence:', confidence)
-    return f"Prediction: {predicted_label}\n(Confidence: {confidence:.2f})"
+    if confidence < 0.5:
+        confidence = abs(1 - confidence)
+    return (predicted_label, confidence)
 
 
 # Streamlit app
 st.title("Lung Cancer Classification")
 st.write(
-    "Upload an image and the model will classify it as positive or negative for lung cancer."
+    "Upload an image and click 'Classify' to predict if it's positive or negative for lung cancer."
 )
 
+# Display the uploaded image
 uploaded_image = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
 
-if uploaded_image is not None:
-    # Display the uploaded image
-    st.image(uploaded_image, caption="Uploaded Image.", use_column_width=True)
-
-    # Classify the uploaded image
-    if st.button("Classify"):
+# Classify the uploaded image
+if st.button("Classify"):
+    if uploaded_image is not None:
         predicted_label, confidence = classify_lung_cancer(uploaded_image)
-        st.write(f"Prediction: {predicted_label}")
+
+        # Style the prediction text
+        if predicted_label == "POSITIVE":
+            prediction_style = "color: red; font-size: 24px; text-transform: uppercase; border: 2px solid red;"
+        else:
+            prediction_style = "color: green; font-size: 24px; text-transform: uppercase; border: 2px solid green;"
+
+        st.markdown(
+            f"<p style='{prediction_style}'>Prediction: {predicted_label}</p>",
+            unsafe_allow_html=True,
+        )
         st.write(f"Confidence: {confidence:.2f}")
+        st.progress(int(confidence * 100))
+        st.image(uploaded_image, caption="Uploaded Image.", use_column_width=True)