Update app.py

app.py

@@ -8,7 +8,7 @@ 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_lables):
+def custom_decode_predictions(predictions, class_labels):
     
     decoded_predictions = []
     for pred in predictions:
@@ -21,7 +21,7 @@ def custom_decode_predictions(predictions, class_lables):
 
 def classify_image(img):
     img_array = img_to_array(img)
-    img_array = np.expand_dims(img_array, axis=0))
+    img_array = np.expand_dims(img_array, axis=0)
     img_array = preprocess_input(img_array)
     predictions = model.predict(img_array)
     decoded_predictions = custom_decode_predictions(predictions, class_names)