Update app.py

app.py

@@ -21,15 +21,15 @@ from tensorflow.keras.applications.resnet import preprocess_input
 
 
 ResNet152Model=ResNet152(include_top=False, weights='imagenet',input_shape=(224,224,3), pooling='avg')
-with open("pickle_files/words_dict_40.pkl","rb") as f:
+with open("pickle_files/words_dict_nepali_sc_40.pkl","rb") as f:
     words_dict=pickle.load(f)
 
 
-vocab_size = 5611
-# vocab_size=6031  # 40 epoch all data
+# vocab_size = 5611
+vocab_size=6031  # 40 epoch all data
 
-MAX_LEN=192
-# MAX_LEN=210 # 40 epoch all data
+# MAX_LEN=192
+MAX_LEN=210 # 40 epoch all data
 inv_dict = {v:k for k, v in words_dict.items()}
 
 
@@ -52,7 +52,7 @@ outputs = Dense(vocab_size, activation='softmax')(decoder2)
 model = Model(inputs=[inputs1, inputs2], outputs=outputs)
 # compile model
 model.compile(loss='categorical_crossentropy', optimizer='adam',metrics=['accuracy'])
-model.load_weights("LSTM/resnet152_lstm_model_weights_45epoch.h5")
+model.load_weights("LSTM/resnet152_lstm_model_weights_40epoch.h5")
 #
 print("LSTM model  loaded successfully")