commit

app.py

@@ -1,11 +1,11 @@
 
 import streamlit as st
 import tensorflow as tf
-from tf.keras.applications import EfficientNetV2B0
+from tensorflow.keras.applications import EfficientNetV2B0
 from keras.layers import Flatten,Dense,Dropout,GlobalAveragePooling2D
-from tf.keras.models import load_model
-from tf.keras.preprocessing.image import load_img
-from tf.keras.preprocessing.image import img_to_array
+from tensorflow.keras.models import load_model
+from tensorflow.keras.preprocessing.image import load_img
+from tensorflow.keras.preprocessing.image import img_to_array
 from keras.models import Model
 from transformers import pipeline
 import numpy as np
@@ -16,7 +16,7 @@ model = EfficientNetV2B0(include_top = False,input_shape=img_shape)
 flat_1=GlobalAveragePooling2D()(model.output)
 capa_3 = Dense(1,activation='sigmoid')(flat_1)
 model = Model(inputs=model.inputs,outputs = capa_3)
-model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=1e-4),loss="BinaryCrossentropy", metrics=["accuracy"])
+model.compile(optimizer=tensorflow.keras.optimizers.Adam(learning_rate=1e-4),loss="BinaryCrossentropy", metrics=["accuracy"])
 #Subir los pesos del modelo
 repo_id = "ferferefer/RIM_ONE_Glaucoma"
 filename = "vgg_rim_checkpoint.h5"  # o el path a tu SavedModel