Update app.py

app.py

@@ -2,29 +2,26 @@
 import gradio as gr
 import numpy as np
 import tensorflow as tf
-import tensorflow_hub as hub
 import cv2
 
-# Register KerasLayer from TensorFlow Hub
-tf.keras.utils.get_custom_objects().update({'KerasLayer': hub.KerasLayer})
+# Load class labels from the text file
+train_info = []
+with open('labelwithspace.txt', 'r') as file:
+    train_info = [line.strip() for line in file.readlines()]
 
-# Attempt to load the model with custom objects
+# Attempt to load the model
 try:
-    model = tf.keras.models.load_model('bird_model4.h5', custom_objects={'KerasLayer': hub.KerasLayer})
+    # Load the model from the .h5 file
+    model = tf.keras.models.load_model('bird_model4.h5')
 except Exception as e:
     print("Error loading the model:", e)
     exit()
 
-# Load class labels from the text file
-train_info = []
-with open('labelwithspace.txt', 'r') as file:
-    train_info = [line.strip() for line in file.readlines()]
-
 # Function to preprocess the image and make predictions
 def predict_image(image):
-    # Resize the image to 224x224 and normalize pixel values
+    # Resize and normalize the image
     img = cv2.resize(image, (224, 224))
-    img = img / 255.0
+    img = img / 255.0  # Normalize to [0, 1] range
 
     # Make predictions
     predictions = model.predict(img[np.newaxis, ...])[0]