Update app.py

app.py

@@ -8,7 +8,11 @@ import numpy as np
 model = load_model('sudoku_net.h5')
 
 def preprocess(image):
-    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) 
+    if len(image.shape) == 2:
+        gray = image  # No need to convert, it's already grayscale
+    else:
+    # Convert RGB image to grayscale using OpenCV
+        gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY) 
 #     blur = cv2.GaussianBlur(gray, (3,3),6) 
     blur = cv2.bilateralFilter(gray,9,75,75)
     threshold_img = cv2.adaptiveThreshold(blur,255,1,1,11,2)
@@ -167,10 +171,10 @@ def main():
     if uploaded_file is not None:
         col1, col2 = st.columns(2)
         col1.subheader("Sudoku Puzzle:")
-        puzzle = cv2.imread(uploaded_file)
-        # puzzle = Image.open(uploaded_file)
+        # puzzle = cv2.imread(uploaded_file)
+        puzzle = Image.open(uploaded_file)
         col1.image(puzzle, use_column_width=True)
-        # puzzle = np.asarray(puzzle)
+        puzzle = np.asarray(puzzle)
         
         # Resizing puzzle to be solved
         puzzle = cv2.resize(puzzle, (450,450))
@@ -192,7 +196,13 @@ def main():
             su_pts2 = np.float32([[0,0],[450,0],[0,450],[450,450]])
             su_matrix = cv2.getPerspectiveTransform(su_pts1,su_pts2)  
             su_imagewrap = cv2.warpPerspective(puzzle,su_matrix,(450,450))
-            su_imagewrap =cv2.cvtColor(su_imagewrap, cv2.COLOR_BGR2GRAY)
+            
+            # su_imagewrap =cv2.cvtColor(su_imagewrap, cv2.COLOR_BGR2GRAY)
+            if len(su_imagewrap.shape) == 2:
+                su_imagewrap = su_imagewrap  # No need to convert, it's already grayscale
+            else:
+                # Convert RGB image to grayscale using OpenCV
+                su_imagewrap = cv2.cvtColor(su_imagewrap, cv2.COLOR_RGB2GRAY)
             _, su_imagewrap = cv2.threshold(su_imagewrap, 127, 255, cv2.THRESH_BINARY)
 
         sudoku_cell = splitcells(su_imagewrap)