Update app.py

app.py

@@ -37,7 +37,7 @@ with tab1:
     components.html(
     """
         <div style="position: fixed; bottom: 0; left: 0; right: 0; text-align: center; font-size: 15px; color: gray;">
-        Tous droits réservés © Décembre 2023 Tayawelba Dawaï Hesed
+        Tous droits réservés © Février 2024 Tayawelba Dawaï Hesed
         </div>
         """,
         height=50 
@@ -49,53 +49,41 @@ with tab2:
     st.header("Prédiction")
     #st.markdown("<h1 style='text-align: center;'>Prédiction</h1>", unsafe_allow_html=True)
     st.sidebar.header("Paramètre pour la prédiction")
-    num_images = st.sidebar.number_input("Nombre d'images à prédire", min_value=1, max_value=10, value=1)
-    upload_files = st.sidebar.file_uploader("Télécharger les fichiers", type=['jpg', 'jpeg', 'png'], accept_multiple_files=True, key="upload")
+    upload_file = st.sidebar.file_uploader("Télécharger le fichier", type=['jpg', 'jpeg', 'png'], key="upload")
     generate_pred = st.sidebar.button("Predict")
 
     # Main
-    if upload_files:
-        # Check if the number of uploaded files matches the number input
-        if len(upload_files) != num_images:
-            st.error(f"Veuillez télécharger exactement {num_images} image(s).")
-        else:
-            # Display uploaded images
-            st.header("Images téléchargées")
-            cols = st.columns(num_images)
-            for i, file in enumerate(upload_files):
-                cols[i].image(file, caption=f"Image {i+1}", use_column_width=True)
-
-            # Predict labels
-            if generate_pred:
-                # Preprocess images
-                test_images = [image.load_img(file, target_size=(64, 64)) for file in upload_files]
-                image_arrays = [img_to_array(img) for img in test_images]
-                image_arrays = np.array(image_arrays)
-
-                # Make predictions
-                predictions = model.predict(image_arrays)
-                classes = np.argmax(predictions, axis=1)
-                labels = [key for key, value in covid_classes.items() if value in classes]
-
-                # Display results in a table
-                st.header("Résultats de la prédiction")
-                table_data = []
-                for i, (file, label) in enumerate(zip(upload_files, labels)):
-                    # Resize image for table display
-                    img = Image.open(file)
-                    img = img.resize((64, 64))
-                    table_data.append([f"Image {i+1}", label])
-                st.table(table_data)
+    if upload_file:
+        # Display uploaded image
+        st.header("Image téléchargée")
+        st.image(upload_file, caption="Image", use_column_width=True)
+
+        # Predict label
+        if generate_pred:
+            # Preprocess image
+            test_image = image.load_img(upload_file, target_size=(64, 64))
+            image_array = img_to_array(test_image)
+            image_array = np.expand_dims(image_array, axis=0)
+
+            # Make prediction
+            prediction = model.predict(image_array)
+            classe = np.argmax(prediction, axis=1)
+            label = [key for key, value in covid_classes.items() if value == classe][0]
+
+            # Display result
+            st.header("Résultat de la prédiction")
+            st.write(f"L'image est classée comme {label}.")
 
     components.html(
         """
         <div style="position: fixed; bottom: 0; left: 0; right: 0; text-align: center; font-size: 15px; color: gray;">
-        Tous droits réservés © Décembre 2023 Tayawelba Dawaï Hesed
+        Tous droits réservés © Février 2024 Tayawelba Dawaï Hesed
         </div>
         """,
         height=70 
     )
 
+
 with tab3:
     # Définir les informations de contact
     name = "TAYAWELBA DAWAI Hesed"
@@ -121,7 +109,7 @@ with tab3:
     components.html(
     """
     <div style="position: fixed; bottom: 0; left: 0; right: 0; text-align: center; font-size: 15px; color: gray;">
-    Tous droits réservés © Décembre 2023 Tayawelba Dawaï Hesed
+    Tous droits réservés © Février 2024 Tayawelba Dawaï Hesed
     </div>
     """,
     height=20