Update app.py

app.py

@@ -23,28 +23,30 @@ class_names = ['Palm', 'Others']
 model = tf.keras.models.load_model('model')
 
 #Generate_pred = st.button("Generate Prediction")
-
-with st.form("form", clear_on_submit=True):
-    uploaded_file = st.file_uploader("Upload image files", type="jpg", accept_multiple_files=True)
-    if uploaded_file is not None:
-        st.image(uploaded_file, width=100)
-    
-    submitted = st.form_submit_button("Click to generate prediction")
+uploaded_file = None
+while (uploaded_file is not None):
+    st.image(uploaded_file, width=100)
+    with st.form("form", clear_on_submit=True):
+        uploaded_file = st.file_uploader("Upload image files", type="jpg", accept_multiple_files=True)
+        if uploaded_file is not None:
+            st.image(uploaded_file, width=100)
         
-    if submitted and uploaded_file is not None:
-        st.write("Predicting!")
+        submitted = st.form_submit_button("Toggle here to predict or to delete the data")
+            
+        if submitted and uploaded_file is not None:
+            
+            
+    
+            for file in uploaded_file:
+                img = Image.open(file)
+                img_array = img_to_array(img)
+                img_array = tf.expand_dims(img_array, axis = 0) # Create a batch
+                processed_image = preprocess_input(img_array)
         
-
-        for file in uploaded_file:
-            img = Image.open(file)
-            img_array = img_to_array(img)
-            img_array = tf.expand_dims(img_array, axis = 0) # Create a batch
-            processed_image = preprocess_input(img_array)
+                predictions = model.predict(processed_image)
+                score = predictions[0]
+                st.markdown("Predicted class of the image {} is : {}".format(file, class_names[np.argmax(score)]))
     
-            predictions = model.predict(processed_image)
-            score = predictions[0]
-            st.markdown("Predicted class of the image {} is : {}".format(file, class_names[np.argmax(score)]))
-
-        uploaded_file = None
+            uploaded_file = None