

In [1]:

    
import os
import argparse
import numpy as np
import six
import six.moves.cPickle as pickle
import matplotlib.pyplot as plt



In [2]:

    
%matplotlib inline



In [3]:

    
dpath=os.path.abspath("")
foldername = "/result"

raw_relu = np.load(dpath+foldername+"/rawimage.npy")
truth_relu = np.load(dpath+foldername+"/groundtruth.npy")
predict_relu = np.load(dpath+foldername+"/predict.npy")



In [4]:

    
raw_sig = np.load(dpath+foldername+"/rawimage_sig3.npy")
truth_sig = np.load(dpath+foldername+"/groundtruth_sig3.npy")
predict_sig = np.load(dpath+foldername+"/predict_sig3.npy")

View result



In [5]:

    
num=69 #0~99

relu_result



In [6]:

    
plt.subplot(131)
plt.imshow(raw_relu[num,0,:],cmap = plt.get_cmap('gray'))
plt.subplot(132)
plt.imshow(truth_relu[num,0,:],cmap = plt.get_cmap('gray'))
plt.subplot(133)
plt.imshow(predict_relu[num,0,:],cmap = plt.get_cmap('gray'))









    Out[6]:





<matplotlib.image.AxesImage at 0x10f7bb590>

sigmoid_result



In [7]:

    
plt.subplot(131)
plt.imshow(raw_sig[num,0,:],cmap = plt.get_cmap('gray'))
plt.subplot(132)
plt.imshow(truth_sig[num,0,:],cmap = plt.get_cmap('gray'))
plt.subplot(133)
plt.imshow(predict_sig[num,0,:],cmap = plt.get_cmap('gray'))









    Out[7]:





<matplotlib.image.AxesImage at 0x110252310>



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