Update app.py

app.py

@@ -16,7 +16,10 @@ def detect_cancer(img):
     pred = model.predict(img)
     #Convert the "numpy.ndarray" object to a simple numebr
     prediction = round(float(pred))
-    return prediction
+    if prediction == 0:
+        return("Congratulation! you don't have breast cancer")
+    else:
+        return("Unfortunately! you have breast cancer. Kindly consult a doctor!")
 
 
     
@@ -33,15 +36,19 @@ def main():
 
     h2 = "Enter the following values to know the status of your health"
     st.write(h2)
-    loaded_img = st.file_uploader(label=color["Upload the Histopathological Image patch of breast"],
+    loaded_img = st.file_uploader(label="Upload the Histopathological Image patch of breast",
                      type=None, accept_multiple_files=False,
                      key="Img_upload_key", 
                      label_visibility="visible")
 
-    if uploaded_file is not None:
-    # Convert the file to TensorFlow image.
-    loaded_img = np.asarray(bytearray(loaded_img.read()), dtype=np.uint8)
-    img = load_img(loaded_img, target_size=(50,50))
-    prediction = detect_cancer(img)
+    if loaded_img is not None:
+        # Convert the file to TensorFlow image.
+        loaded_img = np.asarray(bytearray(loaded_img.read()), dtype=np.uint8)
+        img = load_img(loaded_img, target_size=(50,50))
     
-
+    if st.button(label='Show the Test Results'):
+        prediction = detect_cancer(img)
+        st.success(prediction)
+    
+if __name__ == '__main__':
+    main()