Update app.py

app.py

@@ -37,6 +37,9 @@ load_img = LoadImage(image_only=True)
 #SET CLASSES
 class_names = CLASSES
 
+#SILENCE STREAMIT WARNING
+st.set_option('deprecation.showPyplotGlobalUse', False)
+
 #SET STREAMLIT SESSION STATES
 if 'clicked_pp' not in st.session_state:
     st.session_state.clicked_pp = False
@@ -86,8 +89,8 @@ with st.container():
                     x_value_pred = st.sidebar.slider('Move the slider to adjust the sagittal cut ', bounds_pred[0][0], bounds_pred[0][1], mean([bounds_pred[0][0], bounds_pred[0][1]]))
                     z_value_pred = st.sidebar.slider('Move the slider to adjust the axial cut ', bounds_pred[2][0], bounds_pred[2][1], mean([bounds_pred[2][0], bounds_pred[2][1]]))
 
-                    fig = plotting.plot_img(pred_image, cmap="grey", cut_coords=(x_value_pred,y_value_pred,z_value_pred), black_bg=True)
-                    st.pyplot(fig)
+                    plotting.plot_img(pred_image, cmap="grey", cut_coords=(x_value_pred,y_value_pred,z_value_pred), black_bg=True)
+                    st.pyplot()
 
             else:
                 with st.container():
@@ -138,8 +141,8 @@ with st.container():
                     with pred_col:
                         st.write(f"### Probability: :{color_prob}[{predicted_probability:.2f}%]")   
 
-                    fig = plotting.plot_img(pred_image, cmap="grey", cut_coords=(x_value_pred,y_value_pred,z_value_pred), black_bg=True)
-                    st.pyplot(fig)
+                    plotting.plot_img(pred_image, cmap="grey", cut_coords=(x_value_pred,y_value_pred,z_value_pred), black_bg=True)
+                    st.pyplot()
     
         else:
             raw_image = nib.load(hf_hub_download(repo_id= "rootstrap-org/Alzheimer-Classifier-Demo", repo_type="dataset", subfolder="raw", filename = img_path + ".nii"))
@@ -151,5 +154,5 @@ with st.container():
             x_value_raw = st.sidebar.slider('Move the slider to adjust the sagittal cut', bounds_raw[0][0], bounds_raw[0][1], mean([bounds_raw[0][0], bounds_raw[0][1]]))
             z_value_raw = st.sidebar.slider('Move the slider to adjust the axial cut', bounds_raw[2][0], bounds_raw[2][1], mean([bounds_raw[2][0], bounds_raw[2][1]]))
 
-            fig = plotting.plot_img(raw_image, cmap = "grey", cut_coords=(x_value_raw,y_value_raw,z_value_raw), black_bg=True)
-            st.pyplot(fig)
+            plotting.plot_img(raw_image, cmap = "grey", cut_coords=(x_value_raw,y_value_raw,z_value_raw), black_bg=True)
+            st.pyplot()