Update app.py

app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 import tensorflow as tf
 import numpy as np
+import os
 
 num_classes = 200
 IMG_HEIGHT = 300
@@ -17,11 +18,13 @@ def normalize_image(img):
 def load_model(model_name):
     # Load the model based on the model_name input
     if model_name == "model1":
-        return tf.keras.models.load_model("model1.h5")
+        return tf.keras.models.load_model("Xception.h5")
     elif model_name == "model2":
-        return tf.keras.models.load_model("model2.h5")
+        return tf.keras.models.load_model("InceptionV3.h5")
     elif model_name == "model3":
-        return tf.keras.models.load_model("model3.h5")
+        return tf.keras.models.load_model("InceptionResNetV2.h5")
+    elif model_name == "model4":
+        return tf.keras.models.load_model("DenseNet201.h5")
     else:
         raise ValueError("Invalid model_name")
 
@@ -46,6 +49,7 @@ interface = gr.Interface(
         gr.inputs.Button(label="Model 1 (Xception)", value="model1"),
         gr.inputs.Button(label="Model 2 (InceptionV3)", value="model2"),
         gr.inputs.Button(label="Model 3 (InceptionResNetV2)", value="model3"),
+        gr.inputs.Button(label="Model 4 (DenseNet201)", value="model4"),
     ],
     outputs='label'
 )