Update app.py

app.py

@@ -1,17 +1,23 @@
 import gradio as gr
 import tensorflow as tf
 import numpy as np
-from tensorflow.keras.preprocessing import image
 import cv2
+import os
+
+# Ensure correct class labels (fix folder naming issue if needed)
+class_labels = ["COVID-19", "Normal", "Pneumonia"]  # Ensure class order is correct
 
 # Load the trained model
-model = tf.keras.models.load_model("chest_xray_model.h5")
-class_labels = ["NORMAL", "PNEUMONIA"]  # Update if you have more classes
+model_path = "chest_xray_model.h5"
+if not os.path.exists(model_path):
+    raise FileNotFoundError(f"Model file '{model_path}' not found. Ensure it's uploaded to the Space.")
+
+model = tf.keras.models.load_model(model_path)
 
 # Preprocessing function for uploaded images
 def preprocess_image(img):
     img = cv2.resize(img, (150, 150))  # Resize
-    img = img.astype(np.float32) / 255.0  # Normalize and ensure dtype
+    img = img.astype(np.float32) / 255.0  # Normalize pixel values
     img = np.expand_dims(img, axis=0)  # Add batch dimension
     return img
 
@@ -33,4 +39,4 @@ interface = gr.Interface(
 )
 
 if __name__ == "__main__":
-    interface.launch()
+    interface.launch()