Update app.py

app.py

@@ -1,4 +1,7 @@
 import streamlit as st
+from random import randint
+from .session_state import get_session_state
+
 import cv2
 import pandas
 from PIL import Image
@@ -22,13 +25,24 @@ img_width = 224
 class_names = ['Palm', 'Others']
 model = tf.keras.models.load_model('model')
 
+state = get_session_state()
+if not state.widget_key:
+    state.widget_key = str(randint(1000, 100000000))
+
+uploaded_file = st.file_uploader(
+    "Choose a file", accept_multiple_files=True, key=state.widget_key)
+
+if st.button('clear uploaded_file'):
+    state.widget_key = str(randint(1000, 100000000))
+state.sync()
+
 #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)
+#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("Toggle here to predict or to delete the data")
+#    submitted = st.form_submit_button("Toggle here to predict or to delete the data")
             
     #    if submitted and uploaded_file is not None: