Keras FER-2013 model predict for a single image - tensorflow

Question

i'm pretty new to machine learning. I followed a tutorial to classify if the user is similing or not. I created this code:
def get_model(input_size, classes=7):
model = Sequential()
model.add(Conv2D(32, kernel_size=(3, 3), padding='same', activation='relu', input_shape =input_size))
model.add(Conv2D(64, kernel_size=(3, 3), activation='relu', padding='same'))
model.add(BatchNormalization())
model.add(MaxPooling2D(2, 2))
model.add(Dropout(0.25))
model.add(Conv2D(128, kernel_size=(3, 3), activation='relu', padding='same', kernel_regularizer=regularizers.l2(0.01)))
model.add(Conv2D(256, kernel_size=(3, 3), activation='relu', kernel_regularizer=regularizers.l2(0.01)))
model.add(BatchNormalization())
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.25))
model.add(Flatten())
model.add(Dense(1024, activation='relu'))
model.add(Dropout(0.5))
model.add(Dense(classes, activation='softmax'))
#Compliling the model
model.compile(optimizer=Adam(lr=0.0001, decay=1e-6),
loss='categorical_crossentropy',
metrics=['accuracy'])
return model
if i try to predict an array from flow_from_directory its working fine but i would like to predict it using the following code:
final_image = cv2.imread('./tesimg.jpeg')
final_image = np.expand_dims(final_image, axis=0)
final_image = final_image/255.0
The problem is that i'm getting this error:
UnimplementedError: Graph execution error: