some doubts about your code

hi,dear author recently,i have read this paper,and luckily i have found your code.but i have some question about it. 1.i guess you wrote your code in python 3.0,because i can’t run it in python2.7，then i changed some codes,and succeed. 2.i have some doubts about your codes in reconstruction your low solution image. the following are some codes of you: [angle,strength,coherence] = hashTable(patch,Qangle,Qstrenth,Qcoherence) f = H[angle,strength,coherence] patch = patch.reshape(1,-1) LRImage[jPixel,iPixel] = patch*np.matrix(f).T jPixel = jPixel+1

in google’s paper,after we classified our patches into buckets,there may be no patch or a little patches in buckets because there are often many more horizontal and vertical structures in imagery,and flat regions are common,but i can’t see what solution you make in your paper.

为了表述更清楚，我下面使用中文（见笑）：在谷歌论文分桶的时候，有些结构经常出现有些出现得少使得桶子里面的图像块数非常少，你是怎样处理这个的？

my email is ：[e-mail] i am looking forward your reply!

[binerone]

hi, dear author! i am a student now, today i run this program in my computer and find it took more than 10 minutes to test, is this normal?

and in hashTable.py strength = np.floor(strength/(1/Qstrenth)-1) coherence = np.floor(coherence/(1/Qcoherence)-1) When running to these two sentences, will be given: cannot convert float infinity to integer. i print the ‘strength’ and ‘coherence’ and get ‘inf’, i donot kown where am i wrong.

So I temporarily change these two words: strength = np.floor(strengthQstrenth-1) coherence = np.floor(coherenceQcoherence-1) I know it might be wrong to do so，but i have no idea now. I hope you can help me about it. very thanks.

[MKFMIKU]

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