#!/usr/bin/env python

import caffe
import numpy as np
import cv2
import sys
import Image
import matplotlib.pyplot as plt

model = '/home/lhu/Documents/soft/caffe-1.0/examples/mnist/lenet.prototxt';
weights = '/home/lhu/Documents/soft/caffe-1.0/examples/mnist/lenet_iter_10000.caffemodel';
net = caffe.Net(model,weights,caffe.TEST);
caffe.set_mode_cpu()
#img = caffe.io.load_image(sys.argv[1], color=False)
img = cv2.imread(sys.argv[1],0)
if img.shape != [28,28]:
    img2 = cv2.resize(img,(28,28))
    img = img2.reshape(28,28,-1);
else:
    img = img.reshape(28,28,-1);
#revert the image,and normalize it to 0-1 range
img = 1.0 - img/255.0
out = net.forward_all(data=np.asarray([img.transpose(2,0,1)]))

print out['prob'][0]
print out['prob'][0].argmax()