a

app.py

@@ -44,7 +44,7 @@ class Contrastive_Loss_2(tf.keras.losses.Loss):
     tf.debugging.check_numerics(total_loss.numpy(), 'Total contains NaN values.')
     return total_loss
     
-model = tf.keras.models.load_model( filepath='contrastive_model.h5',  custom_objects={'Contrastive_Loss_2': Contrastive_Loss_2})
+model = tf.keras.models.load_model( filepath='contrastive_model.h5',  custom_objects={'Contrastive_Loss_2': Contrastive_Loss_2}, compile=False)
 
 with open("scene_labels.json") as labels_file:
    labels = json.load(labels_file)
@@ -52,7 +52,8 @@ with open("scene_labels.json") as labels_file:
 def classify_image(img):
     img = tf.convert_to_tensor(img, dtype=tf.float32)
     img = tf.expand_dims(img, axis=0)
-    probs = model.predict(img).flatten()
+    # probs = model.predict(img).flatten()
+    probs = (model(img)).flatten()
     return {labels[i]: float(probs[i]) for i in range(len(labels))}
 
 image = gr.inputs.Image(shape=(256, 256))