Update app.py

app.py

@@ -1,11 +1,24 @@
 import gradio as gr
 import tensorflow as tf
 import numpy as np
-import cv2
 from PIL import Image, ImageDraw, ImageFont
 
+# Defina a camada personalizada FixedDropout
+class FixedDropout(tf.keras.layers.Dropout):
+    def _get_noise_shape(self, inputs):
+        if self.noise_shape is None:
+            return self.noise_shape
+        symbolic_shape = tf.shape(inputs)
+        noise_shape = [symbolic_shape[axis] if shape is None else shape
+                       for axis, shape in enumerate(self.noise_shape)]
+        return tuple(noise_shape)
+
+# Registre a camada personalizada FixedDropout
+tf.keras.utils.get_custom_objects()['FixedDropout'] = FixedDropout
+
 # Carregue seu modelo TensorFlow treinado
-model = tf.keras.models.load_model('modelo_treinado.h5')
+with tf.keras.utils.custom_object_scope({'FixedDropout': FixedDropout}):
+    model = tf.keras.models.load_model('modelo_treinado.h5')
 
 # Defina uma função para fazer previsões
 def classify_image(input_image):