Update app.py

app.py

@@ -1,16 +1,20 @@
 import gradio as gr
-from tensorflow.keras.models import load_model
+from keras.models import load_model
 import keras.backend as K
 import cv2
 import numpy as np
 
-# Define the custom loss function
-def ctc_lambda_func(args):
-    y_pred, labels, input_length, label_length = args
-    return K.ctc_batch_cost(labels, y_pred, input_length, label_length)
+# # Define the custom loss function
+# def ctc_lambda_func(args):
+#     y_pred, labels, input_length, label_length = args
+#     return K.ctc_batch_cost(labels, y_pred, input_length, label_length)
+
+# # Load the model, providing the custom loss function in the custom_objects dictionary
+# loaded_model = load_model('Text_recognizer_Using_CRNN_model.keras', custom_objects={'ctc': ctc_lambda_func},safe_mode=False)
+char_list = "!\"#&'()*+,-./0123456789:;?ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz"
+
+model = load_model('Text_recognizer_Using_CRNN.h5')
 
-# Load the model, providing the custom loss function in the custom_objects dictionary
-loaded_model = load_model('Text_recognizer_Using_CRNN_model.keras', custom_objects={'ctc': ctc_lambda_func},safe_mode=False)
 
 def process_image(img):
     """