Update app.py

app.py

@@ -1,4 +1,5 @@
 import streamlit as st
+import tensorflow as tf
 from PIL import ImageOps, Image
 import os                        # To work with operation system commands
 import cv2                       # To process images
@@ -63,15 +64,16 @@ def Sort_Digits(result2) :
 
 raw_plate = ('raw_plate.png')
 
-def FINAL(img_path) :
+def FINAL(img) :
     '''
     A pipeline for all parts of phase 3.
     start with a car image.
     result is digits and char on car plate.
     '''
     # Read car image ( STEP-1 )
-    img = cv2.imread(img_path)
-    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+    #img = cv2.imread(img)
+    #img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+    img = Image.open(img).convert('RGB')
 
     # First prediction -> Detect car-plate ( STEP-2 )
     result1, _ = Detect_Plate(img)
@@ -83,7 +85,7 @@ def FINAL(img_path) :
     img2 = img[round(pts[1]):round(pts[3]), round(pts[0]):round(pts[2])]
 
     # Resize plate to feed to second model ( STEP-4 )
-    img2 = cv2.resize(img2, dsize=(120, 70))
+    img2 = tf.image.resize(img2, (120, 70))
 
     # Second prediction -> Detect digits in plate
     result2, _ = Detect_Digits(img2)
@@ -104,8 +106,8 @@ img = st.file_uploader('', type=['jpeg', 'jpg', 'png'])
 
 # display image
 if img is not None:
-    image = Image.open(img)
+    image = Image.open(img).convert('RGB')
     st.image(image, use_column_width=True)
 
 
-st.write(FINAL(Image.open(img)))
+st.write(FINAL(img))