Update cnn-rnn.py

cnn-rnn.py

@@ -33,6 +33,8 @@ from nltk.translate.bleu_score import sentence_bleu
 
 
 def getModel():
+    embedding_matrix_vocab = np.load('my_embedding_matrix.npy')
+
     input1 = Input(shape=(2048), name='Image_input')
     dense1 = Dense(256, kernel_initializer=tf.keras.initializers.glorot_uniform(seed = 56), name='dense_encoder')(input1)
 
@@ -89,9 +91,6 @@ def getModel():
 
 def greedysearch(image):
     # Open the pickle file for reading
-    with open('/content/Image_features_ecoder_decoder.pickle', 'rb') as f:
-        Xnet_features = pickle.load(f)
-
     encoder_model, decoder_model = getModel()
     input_ = 'startseq'
     image_features = encoder_model.predict(image)