input_image = caffe.io.load_image(IMAGE_FILE)
input_image = input_image
label_index = int(label_index) - 1
caffeLabel = np.zeros((1, 1000, 1, 1))
caffeLabel[0, label_index, 0, 0] = 1;

net = caffe.Classifier(imagenetModelFile, imagenetTrainedModel,                            mean=np.load(imagenetMeanFile).mean(1).mean(1),
                           channel_swap=(2, 1, 0),
                           raw_scale=255,
                           image_dims=(256, 256))

pred = net.predict([input_image])
bw = net.backward(**{net.outputs[0]: caffeLabel})