Update app.py

app.py

@@ -144,16 +144,13 @@ model = Sequential([
   layers.Dropout(0.2),
   layers.Flatten(),
   layers.Dense(128, activation='relu'),
-  layers.Dense(num_classes, name="outputs")
+  layers.Dense(num_classes, activation='softmax', name="outputs")  # Use softmax here
 ])
 
-
 model.compile(optimizer='adam',
-              loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),
+              loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=False),  # Change from_logits to False
               metrics=['accuracy'])
 
-
-
 model.summary()
 
 
@@ -165,6 +162,7 @@ history = model.fit(
 )
 
 
+
 import gradio as gr
 import numpy as np
 import tensorflow as tf
@@ -176,7 +174,6 @@ def predict_image(img):
     prediction = model.predict(img_4d)[0]
     return {class_names[i]: float(prediction[i]) for i in range(len(class_names))}
 
-
 image = gr.Image()
 label = gr.Label(num_top_classes=12)