Update app.py

app.py

@@ -1,7 +1,11 @@
-model = tf.keras.models.load_model('densenet.h5')
+import tensorflow as tf 
+from tensorflow.keras.models import Model
+from keras.models import load_model
+import numpy as np 
+model = load_model('densenet.h5')
 model.load_weights("pretrained_model.h5")
 class_names = ['Cardiomegaly', 'Emphysema', 'Effusion', 'Hernia', 'Infiltration', 'Mass', 'Nodule', 'Atelectasis', 'Pneumothorax', 'Pleural_Thickening', 'Pneumonia', 'Fibrosis', 'Edema', 'Consolidation']
-def custom_decode_predictions(predictions, class_labels):
+def custom_decode_predictions(predictions, class_lables):
     
     decoded_predictions = []
     for pred in predictions: