Update app.py

app.py

@@ -2,4 +2,24 @@ import streamlit as st
 import tensorflow as tf
 from PIL import Image
 import cv2
-model = tf.saved_model.load("best_saved_model") #Loading the saved model
+model = tf.saved_model.load("best_saved_model") #Loading the saved model
+
+def process_img(img_path):
+    img = cv2.imread(img_path)       # reading the image 
+    #copy_img = img.copy()            # save a copy of image to plot result
+    img = cv2.resize(img,(640,640))  # resize the image as reqired for the model input
+    copy_img = img.copy()
+    img = img/255                    # Normalizing the picel value 
+    img = img.astype("float32")      # Convert the format double to format float
+    img = np.expand_dims(img,axis=0) # exapanding dimension to add batch
+    return img,copy_img
+
+st.title("Table Extract")
+file_name = st.file_uploader("Upload a repport image")
+
+if file_name is not None:
+    col1, col2 = st.columns(2)
+
+    image = Image.open(file_name)
+    col1.image(image, use_column_width=True)
+