Update app.py

app.py

@@ -108,6 +108,7 @@ from tensorflow.keras.preprocessing import image as keras_image
 from PIL import Image
 import numpy as np
 import logging
+import os
 
 # Set up logging
 logging.basicConfig(level=logging.DEBUG)
@@ -115,14 +116,24 @@ logging.basicConfig(level=logging.DEBUG)
 # Initialize the model variable
 model = None
 
-# Load the trained model
-try:
-    model_path = './model1_kera.h5'  # Replace with the actual path to your model file
-    logging.info(f"Loading model from: {model_path}")
-    model = tf.keras.models.load_model(model_path)
-    logging.info("Model loaded successfully.")
-except Exception as e:
-    logging.error(f"Error loading model: {e}")
+# Function to load the model
+def load_model():
+    global model
+    model_path = 'path/to/your/model.h5'  # Replace with the actual path to your model file
+    if not os.path.exists(model_path):
+        logging.error(f"Model file does not exist at path: {model_path}")
+        return False
+    try:
+        logging.info(f"Loading model from: {model_path}")
+        model = tf.keras.models.load_model(model_path)
+        logging.info("Model loaded successfully.")
+        return True
+    except Exception as e:
+        logging.error(f"Error loading model: {e}")
+        return False
+
+# Load the model when the script starts
+model_loaded = load_model()
 
 # Define the class names
 classes = ['Colon Adenocarcinoma', 'Colon Benign Tissue', 'Lung Adenocarcinoma', 'Lung Benign Tissue', 'Lung Squamous Cell Carcinoma']