Update app.py

app.py

@@ -4,26 +4,30 @@ import numpy as np
 import tensorflow as tf
 import tensorflow_hub as hub
 import cv2
+import os
+
+# Path to the model file and label file
+model_path = os.path.join(os.getcwd(), 'bird_model4.h5')
+label_file_path = os.path.join(os.getcwd(), 'labelwithspace.txt')
 
 # Register KerasLayer from TensorFlow Hub
 tf.keras.utils.get_custom_objects().update({'KerasLayer': hub.KerasLayer})
 
-# Load the model using the Functional API
+# Load the model with custom objects
 try:
-    # Load the model with custom objects
-    model = tf.keras.models.load_model('bird_model4.h5', custom_objects={'KerasLayer': hub.KerasLayer})
+    model = tf.keras.models.load_model(model_path, custom_objects={'KerasLayer': hub.KerasLayer})
 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:
+with open(label_file_path, '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 and normalize the image
+    # Resize the image to 224x224 and normalize pixel values
     img = cv2.resize(image, (224, 224))
     img = img / 255.0