ocr handwriting recognition

it is named by law: Const,const_1,const_2,const_3, ...If tensor is a variable, then it is named by law: Variable,variable_1,variable_2,variable_3, ... Second, how to restore the parameters to the refactoring network As far as I know, the restore parameter should be reconstructed with the same structure as the trained network. If you can recover parameters without refactoring, please contact me about how you did it. Restore is simple enough to define a direct restore after saver (there is no tra

Preface In this paper, how to use the KNN,SVM algorithm in Scikit learn library for handwriting recognition. Data Description: The data has 785 columns, the first column is label, and the remaining 784 columns of data store the pixel values of the grayscale image (0~255) 28*28=784 installation Scikit Learn library See a lot of installation tutorials, have not been installed successfully. Finally refer to t

-Sortedclasscount = sorted (Classcount.items (), Key=operator.itemgetter (1), reverse=True) - returnSortedclasscount[0][0] - + - defimg2vector (filename): +f =open (filename) AReturnvect = Zeros ((1,1024)) at forIinchRange (32): -line =F.readline () - forJinchRange (32): -RETURNVECT[0,I*32+J] =Int (line[j]) - returnReturnvect - in - defhandwritingclasstest (): toFileList = Os.listdir ('trainingdigits') +m =Len (fileList) -Traingmat = Zeros ((M, 1024)) theHwlabels = []