Upload app.py

app.py

@@ -28,9 +28,17 @@ model = models.load_model('tf_model.h5')
 def preprocess_image(image):
     # Resize the image
     image = cv2.resize(image, IMG_SIZE)
-    
-    # Convert the image to RGB
-    image = cv2.cvtColor(image, cv2.COLOR_GRAY2RGB)
+
+    # Check if the image is grayscale
+    if len(image.shape) == 2:
+        # Convert grayscale image to RGB
+        image = cv2.cvtColor(image, cv2.COLOR_GRAY2RGB)
+    elif image.shape[2] == 4:
+        # Convert RGBA image to RGB
+        image = cv2.cvtColor(image, cv2.COLOR_RGBA2RGB)
+    elif image.shape[2] > 3:
+        # Extract only the first 3 channels (assuming RGB or BGR format)
+        image = image[:, :, :3]
 
     # Convert the image to float32 and normalize
     image = image.astype('float32') / 255.0
@@ -40,8 +48,6 @@ def preprocess_image(image):
     
     return image
 
-
- 
 def main():
     st.title("Character Recognition")
     st.write("Upload an image and the model will predict the character")