由于是使用的终端，plt.plot函数不能用，采用的思路是不显示图像，直接保存要显示的图像。（红色字体为实现代码）

import numpy as np
import matplotlib  
matplotlib.use('Agg')
import matplotlib.pyplot as plt




# Make sure that caffe is on the python path:
caffe_root = '/public/home/zhkfu/zhkfu/caffe-master/'  # this file is expected to be in {caffe_root}/examples
import sys
sys.path.insert(0, caffe_root + 'python')


import caffe


# Set the right path to your model definition file, pretrained model weights,
# and the image you would like to classify.
MODEL_FILE = caffe_root +  'models/bvlc_reference_caffenet/deploy.prototxt'
PRETRAINED = caffe_root + 'models/bvlc_reference_caffenet/bvlc_reference_caffenet.caffemodel'
IMAGE_FILE = caffe_root + 'examples/images/cat.jpg'  


import os
if not os.path.isfile(PRETRAINED):
    print("Downloading pre-trained CaffeNet model...")
   
caffe.set_mode_cpu()
net = caffe.Classifier(MODEL_FILE, PRETRAINED,
                       mean=np.load(caffe_root + 'python/caffe/imagenet/ilsvrc_2012_mean.npy').mean(1).mean(1),
                       channel_swap=(2,1,0),
                       raw_scale=255,
                       image_dims=(256, 256))
                       
input_image = caffe.io.load_image(IMAGE_FILE)
#plt.imshow(input_image)
prediction = net.predict([input_image])  # predict takes any number of images, and formats them for the Caffe net automatically
plt.plot(prediction[0])
plt.savefig("prediction.png")