Update app.py

app.py

@@ -7,14 +7,14 @@ from tensorflow.keras.preprocessing import image
 from keras.preprocessing.image import img_to_array
 from tensorflow.keras.applications.mobilenet_v2 import MobileNetV2,preprocess_input as mobilenet_v2_preprocess_input
 
-cnnmodel4 = tf.keras.models.load_model("saved_model/cnn_brain_model_9_11.h5")
+cnn = tf.keras.models.load_model("saved_model/cnn_brain_model_9_11.h5")
 resnet = tf.keras.models.load_model("saved_model/resnet_brain_model_9_11.h5")
 vgg = tf.keras.models.load_model("saved_model/vgg_brain_model_9_11.h5")
 
 ### load file
 uploaded_file = st.file_uploader("Choose a image file", type="jpg")
 
-map_dict = {0: 'moderate demented',
+map_dict = {0: 'demented',
             1: 'glioma',
             2: 'healthy',
             3: 'meningioma',
@@ -40,7 +40,7 @@ if uploaded_file is not None:
     
     Genrate_pred = st.button("Generate Prediction")    
     if Genrate_pred:
-        prediction = cnnmodel4.predict(img[0]).argmax()
+        prediction = cnn.predict(img[0]).argmax()
         st.title("Predicted Label for the image by cnn model is {}".format(map_dict [prediction]))
         prediction = resnet.predict(img[0]).argmax()
         st.title("Predicted Label for the image by resnet model is {}".format(map_dict [prediction]))